fpga_tutorial_iecon06_em_mc (1).pdf

1FPGAs used in Industrial Control Systems

Prof. Eric Monmasson, Cergy-Pontoise University, Cergy-Pontoise, France

Email: [email protected]. Marcian Cirstea,

Anglia Ruskin University, Cambridge, UKEmail: [email protected]

2

z Introduction, Presentation of the Current Trends (30 min, MC, EM)z Description of FPGAs (30 min, EM)z Holistic Modelling/Design Methodology (30 min, MC)z Main Design Rules (30 min, EM)

Refinement of Control Algorithms by Simulation Algorithm Architecture Adequation Reusability, VHDL Coding Hardware-In-the-Loop (HIL) Validation

Coffee break --------------------------------------------------------------------------------------

z 1st case studies series: FPGA-based Current Controllers for AC Drives (40 min, EM) Quasi-Analog Hysteresis Controller Delta Modulator PI SVM Controller Predictive Controller

z 2nd case studies series: FPGA-based Intelligent Controllers for AC Drives and AC Generators (40 min, MC)

Induction Motor Control Using Neural Networks Stand Alone Generator Set Using Fuzzy-Logic and PWM

z Conclusions and Perspectives (10 min, EM, MC)z Hands on practical demonstration on two simple examples (30 min, EM, MC)

Overview

ELECTRONIC SYSTEMS ON CHIPTechnical Committee of IEEE Industrial

Electronics Society http://vega.unitbv.ro/~ieee

Mission Statement:This Committee aims to promote professional activities in the area of low power electronics used in the modern industry, with an important focus on the design, development, simulation, verification and testing of digital and analogue circuits integrated as Systems on Programmable Chips, targeting Field Programmable Gate Arrays / Application Specific Integrated Circuits for implementation, and including the use of Hardware Description Languages or high level programming languages hardware compilers, as well as embedded electronic systems and associated software.

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Chair: Dr. Marcian Cirstea, Head of Department of Design & Technology, Anglia Ruskin University, Cambridge, UK.

Email: [email protected]

z Special conference sessions organisations subcommitteez Coordinator and Committee Vice-Chair: Dr. Manus Henry, Deputy

Director, Invensys University Technology Centre for Advanced Instrumentation at the Department of Engineering Science, the University of Oxford, UK.

z Dr.Vito Nardi, University of Cassino, Italy.

z Special Issues / Sections of Journals subcommitteez Coordinator: Prof. Eric Monmasson, Head of the Institut Universitaire

Professionnalis de Gnie Electrique et dInformatique Industrielle (IUP GEII), University of Cergy-Pontoise (UCP), France.

z Prof. Josep M. Guerrero, Universitat Politcnica de Catalunya (UPC), Barcelona, Spain.

z Dr. Jeen G. Khor, Senior Design Engineer, INTEL, Penang, Malaysia.

z Web page subcommitteez Coordinator: Dr. Andrei Dinu, Goodrich Engine Control Systems,

Electromagnetic Systems Technical Centre, Birmingham, UK. z Dr. Otilia Boaghe, Phillips Semiconductors, Zurich, Switzerland.

5z Conferences / transactions papers review subcommitteez Coordinator: Prof. Dan Nicula, Transilvania University Brasov,

Romania.

z Prof. Bogdan Dan Willamowski, Past President of the Industrial Electronics Society, Auburn University, AL, USA.

z Dr. Jeroen Van Den Keybus, Catholic University of Leuven, Belgium.

z Dr. Yasuhiro Ota, Partner Robot Development Division, Toyota Motor Corporation, Aichi, Japan.

z Prof. Chin-Long Wey, Dean of College of Electrical Engineering and Computer Science, National Central University, Chung-Li, Taiwan.

z Dr.Robert Seliga, Electronics Design Engineer, Newage AVK SEG, Stamford, UK.

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Activity Plan 20079 Website development to support & promote committees work and to

provide a point of reference on topics of interest. Guest-Editorship of a special issue of the Transactions on Industrial

Electronics: FPGAs used in Industrial Control Systems. Dr. Eric Monmasson and Dr. Marcian Cirstea are joint Guest Editors.

Organisation of a best paper prize of $500 for this Special Issue Organisation of special sessions at the forthcoming IEEE IES

Conference: ISIE07. Organising ISIE08 in Cambridge Refereeing of IEEE Transactions and Conference papers. Contributing to the organisation of other IES conferences by chairing

Technical Tracks, refereeing papers, etc. Presenting tutorials Printing materials to advertise the committee, as well as its technical

activities, as posters / leaflets.

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Traditionally, mathematical models were used to functionally evaluate engineering systems. The development of each system component used then to be separately addressed, often involving the use of other CAD tools and/or different software platforms.

Traditional methods are not able to cope with increased complexity and demands of higher levels of systems integration / faster time to market. Recent advances in CAD methodologies/languages has brought the systemsfunctional description and hardware implementation closer.

Modern Electronic Design Automation (EDA) tools are used to model, simulate and verify a complex engineering system fast, with high confidencein right first time correct operation, without producing a prototype.

High performance electronic controllers can also be implemented.

The presentation reveals recent work that was carried out in the area of holistic modelling of engineering systems using HDLs.

Introduction

8

Traditionally, mathematical models were used to functionally evaluate engineering systems. The development of each system component used then to be separately addressed, often involving the use of other CAD tools and/or different software platforms.

Traditional methods are not able to cope with increased complexity and demands of higher levels of systems integration / faster time to market. Recent advances in CAD methodologies/languages has brought the systemsfunctional description and hardware implementation closer.

Modern Electronic Design Automation (EDA) tools are used to model, simulate and verify a complex engineering system fast, with high confidencein right first time correct operation, without producing a prototype.

High performance electronic controllers can also be implemented.

The presentation reveals recent work that was carried out in the area of holistic modelling of engineering systems using HDLs.

Introduction

9Integrated Circuitsz Off-the-Shelf Logic - Function pre-set.

z PROM, PAL, FPLA - Programmed by fusible links / charge storage.

z FPGAs - User programmable Field Programmable Gate-Arrays.

z Gate Array Device - Function set at manufacture in the final stage of production (metallization).

z Cell Based Device - Function set at manufacture using CAD to speed up design and a library of optimised standard functions.

z Full Custom Device - Function set at manufacture - every circuit part is optimally designed. Long development time even with CAD.

;More gates / chip ==> reduces cost but requires CAD.10

Comparative Economics Cost

(relative) full-custom

cell -based

system

gate-array SSI / MSI

Volume 10,000 50,000 .100,000

z True cost formula shows that the final unit cost is:cost = D / N + chip + F

where D=total development cost, N=no. of chips manufactured,chip=unit chip costs in production, F=packaging, testing per chip

11

Application Specific Integrated Circuitsz Application Specific Integrated Circuits (ASICs) = any IC designed and built

specifically for a particular application.

z ASICs allow tailoring the design during development stages of an IC. Advantages:. Reduced Size and Cost. High Speed and Accuracy in Information Processing. Compact Structure. High Reliability of Circuit Operation

z Two major ASIC technologies: CMOS and BICMOS - millions gates. z RISC and DSP cores are now offered by chip suppliers. They permit the

design of single chip customised advanced integrated processors.

z Field-Programmable Gate Arrays (FPGAs) are a special class of ASIC'swhich differ from mask-programmed gate arrays in that the programming is done by end-users with no IC masking steps.

12

Introduction

z FPGAs have reached high density rate ( > 10 millions gates)

z Performing Electronic Design Automation (EDA)Tools

z These components allow the programming of specific hardware architecture

z This leads to a flexible and an efficient solution (software development of dedicated hardware architecture that includes parallelism)

z System-on-a-Chip (SoC) scale

13

Introduction

z Many industrial applications Telecom, Video, Signal Processing, Medical Systems, Embedded Systems (Aircraft, Automotive), Electrical Systems:

z PWM inverters, z Power factor correction AC/DC converters, z Multilevel converters, z Matrix converters, z Active filters,z Fault-detection on power grid,z Electrical machines control (induction machine drives, multi-machines

systems, z Neural Network control of induction motors, z Fuzzy Logic control of power generators, z Speed measurement

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z The decrease of the cost An architecture based only on the specific needs of the algorithm to implement, Application of highly advanced and specific methodologies improving implementation

time also called "time to market", Expected development in VLSI design that will allow integrating a full control system

with its analog interface in a single chip, SoC.z The confidentiality

Specific architecture, integrating the know-how of a company, is not easily duplicable.z The embedded systems

Many constraints as in aircraft applications, like limited power consumption, thermal consideration, reliability and Single Event Upset (SEU) protection.

z The improvement of control performance Execution time can be dramatically reduced by designing dedicated parallel architectures,

allowing FPGA-based controllers to reach the level of performance of their analog counterparts without their drawbacks (parameter drifts, lack of flexibility).

FPGA-based controller can also be adapted in run-time to the needs of the plant by dynamically reconfiguring it.

IntroductionAdvantages:

15

Introduction

DSP

FPGA

(a) (b) (c)

(d)

Algorithm Timing constraints

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A specific architecture for each control algorithm16

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(Sensorless operating mode)

Flux & SpeedObservation

(Sensorless operating mode)

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Introduction

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Algorithmic Constraints:

Algorithm Architecture Adequation by means of FPGA

Vector Control Algorithm:

SVPWM Current Regulator Flux Estimator

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Heterogeneous Functions Various Time Scale Various Computing Tasks

17

Introduction

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How to easily implement a control algorithm on an FPGA-based optimized hardware architecture?

Simulink ModelFPGA board

18

This leads to follow up a design methodology

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functional simulation Fixed-point quantization & discrete model

VHDL codingFPGA targetExperimental board

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Introduction

19

Generic FPGA Architecture

C onfigurable Input/O utput

Block

C onfigurable Logic Block

Interconnection Program m able

N etwork

20

Generic FPGA Architecture

Inputs [3:0]

LUT LUT

Chemin Carry Path

Bascule D D

Flip-Flop

Input carry

Clock

Flip-Flop output

Combinatorial output

Output carry

Logic Cell / Logic Element :

21

Head-to-Head

z Xilinx Virtex-5 1v 65nm copper 207,360 logic cells 11.6 Mb RAM 192 48-bit MAC Unit

(25x18 multipliers, 550MHz)

Up to four PowerPC 405 cores

MicroBlaze 32-bit soft core

z Altera Stratix II 1.2v 90nm copper 179,400 logic elements 9.4 Mb RAM 96 36x36 multipliers

(384 18x18 multipliers) 1,170 user I/O pins

Nios II 32-bit soft processor core

22

Head-to-Head Low Cost

z Spartan 3E 1.2v 90nm copper 33,192 logic cells 0.65 Mb RAM 36 18x18 multipliers 376 user I/O pins 8 DCMs

MicroBlaze 32-bit soft processor core

z Altera Cyclone II 1.2v 90nm copper 68,416 logic elements 1.15 Mb RAM 150 18x18 multipliers 622 user I/O pins 4 PLLs

Nios II 32-bit soft processor core

23

Virtex-4 Architecture

1 Gbps SelectIOChipSync Source synch, XCITE Active Termination

Smart RAM New block RAM/FIFO

Xesium ClockingTechnology

500 MHz

PowerPC 405with APU Interface450 MHz, 680 DMIPS

Tri-ModeEthernet MAC

10/100/1000 Mbps

RocketIOMulti-GigabitTransceivers

622 Mbps10.3 Gbps

XtremeDSPTechnology Slices

256 18x18 GMACs

Advanced CLBs200K Logic Cells

24

Virtex IV Platforms

ResourceResource

14K14K200K LCs200K LCsLogic

Memory

DCMs

DSP Slices

SelectIO

RocketIO

PowerPC

Ethernet MAC

LXLX FXFX SXSX

0.90.96 Mb6 Mb

441212

32329696

240240960960

23K23K55K LCs55K LCs

2.32.35.7 Mb5.7 Mb

4488

128128512512

320320640640

12K12K140K LCs140K LCs

0.60.610 Mb10 Mb

442020

3232192192

240240896896

0024 Channels24 Channels

1 or 2 Cores1 or 2 Cores

2 or 4 Cores2 or 4 Cores

N/A

N/A

N/A

N/A

N/A

N/A

25

Altera Stratix

26

Slices and CLBs

z Each Virtex-II CLB contains four slices Local routing provides

feedback between slices in the same CLB, and it provides routing to neighboring CLBs

A switch matrix provides access to general routing resources

CIN

SwitchMatrix

BUFTBUF T

COUTCOUT

Slice S0

Slice S1

Local Routing

Slice S2

Slice S3

CIN

SHIFT

27

Distributed SelectRAM Resources

z Uses a LUT in a slice as memoryz Synchronous writez Asynchronous read

Accompanying flip-flops can be used to create synchronous read

z RAM and ROM are initialized duringconfiguration Data can be written to RAM

after configurationz Emulated dual-port RAM

One read/write port One read-only port

RAM16X1S

O

DWE

WCLKA0A1A2A3

LUTLUT

RAM32X1S

O

DWE

WCLKA0A1A2A3A4

RAM16X1D

SPO

DWE

WCLKA0A1A2A3DPRA0 DPODPRA1DPRA2DPRA3

Slice

LUT

LUT

28

Slice 0

LUTLUT CarryCarry

LUTLUT CarryCarryD QCE

PRE

CLR

DQCE

PRE

CLR

Simplified Slice Structure

z Each slice has four outputs Two registered outputs,

two non-registered outputs Two BUFTs associated

with each CLB, accessible by all 16 CLB outputs

z Carry logic runs vertically, up only Two independent

carry chains per CLB

29

Altera Stratix

30

Logic Array Blocks (LABs)

31

Logic Element

32

Embedded RAM

z Xilinx Block SelectRAM 18Kb dual-port RAM arranged in columns

z Altera TriMatrix Dual-Port RAM M512 512 x 1 M4K 4096 x 1 M-RAM 64K x 8

33

Xilinx: Embedded Multipliers

z 18-bit twos complement signed operationz Optimized to implement Multiply and Accumulate functionsz Multipliers are physically located next to block SelectRAM

memory

18 x 18Multiplier18 x 18Multiplier

Output (36 bits)

Data_A (18 bits)

Data_B (18 bits)

18 x 18signed12 x 12signed8 x 8 signed4 x 4 signed

34

Altera: Embedded DSP Blocks

z Two DSP Block columns per devicez Number varies by height of columnz Can implement:

Eight 9x9 multipliers Four 18x18 multipliers One 36x36 multiplier

z Contains adder/subtracter/accumulatorz Registered inputs can become shift register

35

Altera Multiplier Sub-block

36

Virtex: Active Interconnect

37

Virtex Hierarchical Interconnect

38

Altera: MultiTrack Interconnect

z Direct link between LABs and adjacent blocksz Row interconnects

4, 8, and 24 blocks left or rightz Column interconnects

4, 8, and 16 blocks up or down

39

Stratix: R4 Interconnect

40

MicroBlaze Processor-Based Embedded Design

Flexible Soft IPMicroBlaze32-Bit RISC Core

UART 10/100E-NetMemory

Controller

Off-ChipMemory

FLASH/SRAM

Fast Simplex Link

0,1.7

CustomFunctions

CustomFunctions

BRAM Local Memory

BusD-CacheBRAM

I-CacheBRAM

ConfigurableSizes

A

r

b

i

t

e

r

Processor Local Bus

Instruction Data

PLBBus

Bridge

PowerPC405 Core

Dedicated Hard IP

A

r

b

i

t

e

r

Processor Local Bus

Instruction Data

PLBBus

BridgeBus

Bridge

PowerPC405 Core

Dedicated Hard IP

PowerPC405 Core

Dedicated Hard IP

PowerPC405 Core

Dedicated Hard IPPossible inVirtex-II Pro

Hi-SpeedPeripheral

GB E-Net

e.g.Memory

ControllerHi-Speed

PeripheralHi-Speed

PeripheralGB

E-NetGB

E-Net

e.g.Memory

Controller

e.g.Memory

Controller

A

r

b

i

t

e

r OPBOn-Chip Peripheral Bus

CacheLink

SRAM

41

Embedded DevelopmentTool Flow Overview

Data2MEM

Download CombinedImage to FPGA

Compiled ELF Compiled BIT

RTOS, Board Support Package

EmbeddedDevelopment Kit

Instantiate the System Netlistand Implement

the FPGA

?

HDL Entry

Simulation/Synthesis

Implementation

Download BitstreamInto FPGA

Chipscope

Standard FPGAHW Development Flow

VHDL or Verilog

System NetlistInclude the BSPand Compile theSoftware Image

?

Code Entry

C/C++ Cross Compiler

Linker

Load SoftwareInto FLASH

Debugger

Standard EmbeddedSW Development Flow

C Code

Board SupportPackage

12 3 Compiled BITCompiled ELF

42

Altera Nios II

43

Altera Nios II

44

SoPC Builder

45

Actel Fusion

46

Actel Fusion - ADC

ACMFlash

memory

RTC

Analog multiplexer

AnalogQuad

9

ADC

12 bits

AnalogQuad

8

AnalogQuad

1

AnalogQuad

0

Analog Bloc

ADCSTART

5 bits CHNUMBER[4 :0]

DATAVALIDCALIBRATE

ADCRESULT [11 :0]

AV0AC0AG0

AT0

AV1AC1AG1

AT1

AV8AC8AG8

AT8

AV9AC9AG9

AT9

0143031

Tempratureinterne

Vcc(1.5V)

SYSCLK = 50MHz

ADCCLK

Freq_div

01

6 MHz

CLK

:

47

Actel ProASIC

48

Actel ProASIC

49

NOTHING EASIER !

In trouble with a chip design ?

50

Design Methodologies EDA Tools

Traditional

Modern

Everybody hates EDA tools at some stage !!!

51

Design flow

z Design Entry (schematic,HDL, state diagram).

z Compilationz Apply stimulusz Simulationz Implementation and Layoutz Timing Analysis / Verificationz Download design into siliconz Testing the chip

52

Novel Systems Modelling Method- main features and context -

z Extends the traditional use of Hardware Description Languages (HDLs) for electronic circuits design, to encompass holistic modelling of more complex engineering systems.

z Outcome: design environment that allows all aspects of the system to be simultaneously considered, therefore maximising performance.

z Proposed approach correlated with powerful international movement/leading edge research, directed towards system level modelling/design.

z The international EDA community, united under ACCELLERA (2000) (http://www.accellera.org/index.html), assumed the mission to drive the worldwide development and use of standards required by systems, semiconductors & design tools.

z Clear proof of the internationally identified need for the development of holistic models for complex engineering systems.

z Proposed for engineering systems holistic modelling: VHDL = Very high speed integrated circuit Hardware Description Language. (IEEE, 1993).

53

Specific Advantages Offered by VHDL

z Allows the functional/behavioural description of an engineering system to be combined with a detailed electronic design, on the same CAD platform.

z The mathematical aspects of systems and the electronic hardware design are simultaneously addressed, in a unique environment.

z It is supported by all major Computer Aided Design platforms

z Ability to handle all levels of abstraction. The system can be simulated as an overall model during all stages of the electronic controller design, which can be subsequently targeted for system on a chip silicon implementation.

z Fast implementation & relatively short time to market of new designs.

z Hardware Implementation of Artificial Intelligence is facilitated.

z Versatile reusable models / design modules are generated, in accordance with modern principles of design reuse.

54

Advantages of FPGA Controller Prototyping

z A cheap & fast VHDL code validation is via a prototype board containing re-programmable devices - Field Programmable Gate Arrays (FPGAs).

z Allows electronic controllers hardware validation that provides significant information before the decision is taken to invest in an Application Specific Integrated Circuit (ASIC) = IC dedicated specifically to an application.

z It shortens the time to correct any design problem and it ensures an error free design before permanent ASIC implementation.

z The prototype board can be used for hardware testing other system components.

z The general benefits of holistic modelling of systems, combined with the advantages of VHDL and FPGAs, enable the efficient investigation of new engineering system topologies employing complex electronic controllers.

55

Engineering Systems Modelling Approach Summary

Modelling / Development: VHDLElectronic Controller Hardware Prototyping: FPGAAdvantages of using VHDL Efficient design process Single environment for modelling, simulation & electronic controller design. Easy modifications and system integration of designs EDA platform independence of VHDL designs (ASCII files) Reusable IP block modelling/design style becomes possibleAdvantages of using FPGAs Small, compact design Fast, relatively cheap Reusable hardware framework for testing a design Short time to market of product, rapid prototyping 56

Top-Down Designz VHDL allows the designer to develop and simulate ideas fast, without

getting caught-up in the details of implementation.

z As the design evolves to completion, the language is able to support a complex detailed digital system description.

z Top-down design begins with modelling an idea at an abstract level, and proceeds through the iterative steps necessary to further refine this into a detailed system.

z A test environment is developed early in the design cycle. Concepts are tested before investment is made in implementation.

z As design evolves to new levels of detail, the test environment will check compliance with the original specification.

57

VHDL Description

z Evolution of the VHDL language began in 1980's and resulted in the adoption of the VHDL's IEEE Standard (1993).

z Due to increased demands of higher levels of integration / faster time-to-market, a standard language, that referenced a higher level of design abstraction was needed. This stand-alone specification is not dependent on any specific tool.

z An entire system, once consisting of many components/circuit boards, can be replaced by one/two integrated circuits.

z VHDL's flexibility and choice of modelling styles enable a natural progression from idea to implementation, giving the designer the ability to quickly create, simulate, and verify an abstract model.

z Thus, design concepts can be tested before the investment is made in the hardware implementation.

z A major feature of VHDL is its inherent ability to handle all levels of abstraction. The designer requires the use of only a single language, as well as a single simulator for all phases of design. 58

Design UnitsEntity: describes the interface between the outside world and the

design. The connection points (PORTs) to the design, the direction and type of data that flows through these points are defined here.

z For example, an AND gate with 3 connection points, 2 inputs and 1 output and data type bit (values '0' or '1') might look like:

ENTITY and2 IS

PORT (in1,in2: IN bit;

outp: OUT bit);

END and2;

Architecture: defines an entity's behaviour from a simulation point of view. It depends upon the information declared within an entity.

59

z A behavioural architecture example for the and2 entity is:ARCHITECTURE arch1 OF and2 ISBEGIN

output in1, sig2=> in2, sig3 => internal);u2:and2 PORT MAP(sig1=>in3, sig2=>internal, sig3=>output);END struct; 60

Behavioural Designz In VHDL behavioural descriptions there is no reference to submodules within a

specific VHDL architecture. z This does not preclude the use of subprograms within VHDL descriptions, but

precludes the use of other VHDL components. z Behavioural descriptions are defining the design functionality. z A behavioural description of a multiply accumulate device (mac) is:

USE WORK.util.ALL;ENTITY mac IS

GENERIC(tco: time := 10 ns);PORT( in1, in2: IN bit_vector(15 DOWNTO 0);

clk, reset: IN bit;out1: OUT bit_vector(31 DOWNTO 0));

END mac;ARCHITECTURE behave OF mac ISBEGIN

PROCESS (clk, reset)VARIABLE reg_in1, reg_in2, reg_mul, accum: integer;

61

BEGIN IF reset = '0' THEN

reg_in1 := 0;reg_in2 := 0;reg_mul := 0;accum := 0;

ELSIF rising_edge(clk) THENaccum := accum + reg_mul;reg_mul := reg_in1 * reg_in2;reg_in1 := vect_to_int(in1);reg_in2 := vect_to_int(in2);

END IF;out1

65

z The VHDL model is converted into a hardware structure with the help of synthesis tools.

z First the VHDL model is mapped to a hardware structure described using cells from a technology library. Then the netlistis placed and routed.

z Usually an optimizer is involved in generating the final result based on silicon area minimisation or speed considerations.

z The VHDL code has to be written in a style that is implementable and generates reliable circuits.

z Synchronous circuits are preferred.

VHDL Design for Synthesis

66

Flip-flop Output Driving the Clock Input of Another Flip-Flop

d q

> c k q b

d q

> c k q b

Clock Signal Situations

Avoiding Gated Clock by Using a Clock Enable

67

Clock Bufferingz In FPGAs the clock tree is already designed and the clock distribution is dealt

with automatically be the synthesis tool.z For ASIC design it may be necessary to design the clock tree manually.z It is important to avoid: Clock skew generated by unequal depth of clock buffering. Unequal load-dependent delays generated by unbalanced clock buffers fan-out. Slow clock edges due to excessive buffer loading.

Incorrect Clock Buffering

68

Correct Clock Buffering

z The circuit provides the same buffering depth at all clocked points;

z All buffers have the same fan-out;

z The buffers are lightly loaded (less than 50% of maximum fan-out).

69

Shift Registers and Clock Bufferingz Shift registers are particularly sensitive to clock skew. The register

operation could be incorrect due to set-up and hold problems.

clk

dd q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

clk

dd q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

d q

>ck qb

70

Situations to be Avoided when Operating with the Asynchronous Reset

zIt is recommended to avoid driving the asynchronous reset input of one flip-flop using the output of the other.

d q

>ck qb

d q

>ck qb r

clk

d q

>ck qb

clk

CombinationalLogic

d q

>ck qb r

71

The Recommended Solution for flip-flops with Synchronous Reset

c lk

d q

>ck qb r

d q

>ck qb r

d q

>ck qb r

d q

>ck qb r

rese t

zA signal conflict may arise at the interface between a synchronous circuit and an external asynchronous input. It is recommended to synchronize an asynchronous input by passing it through one or more flip-flops.

Synchronizing Asynchronous Inputs

d q

> c k q b

d q

> c k q b

d (e x te rn a l) d ( in te rn a l)

c lk ( in te rn a l)

72

Adders and Multiplexersarchitecture arch of entity1 isbeginoutp

73

Optimised Adder and Multiplexer Circuit

process (sel, a, b, c)variable in_add : std_logic_vector(5 downto 0);

beginif sel = '0' thenin_add

77

Design Methodology

9 To ensure a more automated and less intuitive approach for the design of FPGA-based control systems

Objectives

9 Reduction of the development time

9 Development of a specific library of reusable modules dedicatedto the control of electrical systems

9 First attempt success guarantee of the designed architecture

78

Modular partitioningof the algorithm

Simulation procedure

Optimization of theconsumed resources

Architecture design

Validation of the architecture

Design Methodology

Different steps

79

Modle continu

Discrete Model

Per Unit Dicrete Model

Example : dX/dt (X[k+1]-X[k])/Ts

X/Xb

Continuous Model

Design Methodology

Reduction of the development time Extraction of reusable modulesModular partitioning of the algorithm

80

Design Methodology

Continuous Model of a FOC Estimator

81

sq = Lsisq

ddq/dt = wdq

sd = Lsisd + (Lm/Lr)r

Cem = (3/2)p(Lm/Lr) r isq

Wdq = w + Lmisq/(Trr)

r = Lm/(1+Trs) isd

isq =2/3(sin(+150) is1 + cos() is2)isd =2/3(sin(+60) is1 + sin() is2)

Continuous Model of a FOC Estimator

Design Methodology

Simplification

82

Continuous Model

Discrete Model

Per Unit Discrete Model

Design Methodology

Euler: dX/dt (X[k+1]-X[k])/Ts

83

sq [k] = a9 isq [k]dq [k] = dq [k-1] + a10 wdq [k-1]

sd [k] = a7 isd [k] + a8 r [k]Cem [k] = a6 r [k] isq [k]

Wdq [k] =a4 w [k] + a5 isq [k] /r [k]r[k]=a2 isd [k-1]+ a3 r[k-1]

isq[k]=a1(sin([k]+150) is1[k] + cos([k]) is2[k])isd[k]=a0(sin([k]+60) is1[k] + sin([k]) is2[k])Digital Model of a FOC Estimator

a0 = 2/3 a1 = 2/3a2 = Lm Te/Tra3 = 1 - Te/Tra4 = 1a5 = Lm/Tra6 =(3/2)pLm/Lra7 = Ls a8 = Lm/Lra9 = Ls a10 = Te

Design Methodology

84

Continuous Model

Discrete Model

Per Unit Discrete Model

Design Methodology

85

sq[k] = A9 isq[k]

dq[k] = dq[k-1] + A10wdq[k-1]

sd[k] = A7 isd[k] + A8 r[k]

Cem[k] = A6r[k] isq[k]

Wdq[k] = A4 w[k] + A5 isq[k]/r[k]

r[k] = A2 isd [k-1] + A3 r[k-1]isq[k] =A1(sin([k]+150) is1[k] + cos([k]) is2[k])isd[k] =A0(sin([k]+60) is1[k] + sin([k]) is2[k])

Per Unit Digital Model of a FOC Estimator A0 = a0A1 = a1A2 = a2Ib/bA3 = a3A4 = a4wb/wdqbA5 = a5Ib/(wdqbb)A6 = a6A7 = a7Ib/ bA8 = a8A9 = a9Ib/bA10 = a10wdqb

Design Methodology

86

abc to dqTransformation

(1)

Low PassFilter

(2)

dq, TL, sd et sqEstimator

(3)Integrator

(4)

is1

is2

isd

isq

r

dq

isd

dq

TL sd sq

Design Methodology

Example 1 : FOC Estimator algorithm

Library

Modular partitioning of the algorithm

87

Table(1)

TL*Isd*

Isq*dq to abc

Transformation(2)

HysteresisController

(3)

is1*

is2*

is3*

SaSbSc

is1 is2 is3

Design Methodology

Example 2 : Sliding Mode Torque Control algorithm

Creation of a specific Electrical System dedicated library

Library


88

Design Methodology

Current Control, Torque Control Speed Control,

Full Control AlgorithmsLevel 3Level 3

PI, PID, PPI, Hysteresis controller,

Regulation

PWM, SVM,

Modulation

abc-to-, -to-abc, abc-to-dq, dq-to-abc

Vector Operators

PLL, Torque Estimator, Flux EstimatorEstimation

Level2Level2

Level 1Level 1Registers, multiplexers,

demultiplexers,

Basic Operators

Adder, multiplier, sine-cosine, cordic,

Arithmetic Operators

89

Design Methodology / Web Site

90

Library of IP modules dedicated to the Control of Electrical Systems

9 VHDL Programs9Matlab Simulink Models9 Data-sheets

Design Methodology

91

Design Methodology

Verification of the algorithm functionalitySimulation procedure


Choice of the suitable sampling period and fixed-point format

92

Design Methodology

Induction motor

IFO Controller +

VSI

Estimator algorithm

Example 1 : Per Unit FOC Estimator functional model

1) Development of a continuous functional continuous model

Verification of the algorithm functionality

93

Design Methodology

Torque control algorithm

VSI SM

Example 2 : Per Unit Sliding Mode Torque Control functional model

94

Design Methodology

Choice of the sampling period and fixed-point format of the digital algorithm

2) Development of a discrete fixed-point specification model

Example1 : FOC Estimator specification model

95

Design Methodology

Example2 : Sliding Mode Torque Control specification model

96

Design Methodology

Example2 : Sliding Mode Torque Control specification model

97

Design Methodology

dq-to-abc transformation specification model

Dq-to-abc transformation Data Flow Graph (DFG)

+ +

5/6 /3

+

/2

Sin Sin Sin

x x

Sin

x x

isa[k] isb[k]

dq[k]

+ +

x x

A0A1

isd[k]isq[k]

U[p/Q0]

U[p/Q0]

U[p/Q0] U[p/Q0] U[p/Q0]

U[p/Q0] U[p/Q0]

S[n/Qn-1]S[n/Qn-1] S[n/Qn-1] S[n/Qn-1]

S[n/Qn-2]S[n/Qn-2] S[n/Qn-2]

S[n/Qn-2] S[n/Qn-2] S[n/Qn-2]S[n/Qn-2]

S[n/Qn-1] S[n/Qn-1]

Lots of possibilities in terms of parallelism 98

Design Methodology

Reduction of the consumed resources



Optimization procedure

99

Design Methodology

A1A2

x1x2

y

S[n/Qn-1]

S[n/Qn-1] x

+

F F

J

S[n/Qn-1]

S[n/Qn-1]S[n/Qn-1] S[n/Qn-1]

S[n/Qn-1]

S[n/Qn-1]S[n/Qn-1]

S[n/Qn-1]

Factorization Hardware resources Execution time

Defactorization Hardware resources Execution time

S[n/Qn-1]

x1 A1 A2 x2

S[n/Qn-1]S[n/Qn-1]

S[n/Qn-1]S[n/Qn-1]

S[n/Qn-1]

y

x x

+

100

Design Methodology

Generation of optimized hardware architecture (A3 methodology)

FF0 : Factorization Frontier 0

FF1 : Factorization Frontier 1

14Sine

16Multiplication

35Addition

FDFGDFGOprations

abc-to-dq transformation Factorized Data Flow Graph (FDFG)

F

0/3/25/6

+

SinFD

A0A1

D

x F D

F

J

+ +

isa[k]

isb[k]

dq[k]

isd[k]isq[k]

FF0

FF1

S[n/Qn-1]

U[p/Q0]

S[n/Qn-1]

U[p/Q0]

S[n/Qn-2]

U[p/Q0]

U[p/Q0] S[n/Qn-1]

S[n/Qn-2] S[n/Qn-1]

S[n/Qn-2]

101

Design Methodology




Architecture Design

102

Design Methodology

1) Modular Hardware Architecture Design

Inputs[k] Inputs [k+1] Inputs [k+2]

StartInput Data

Outputs [k] Outputs [k+1] Outputs [k+2]

EndOutput Data

Clk

TClkLatency*TClk

Data-path

Control unit

S1

Module name

Input Data Output Data

Start End

ClkReset

S2S3

S3

Generic Second Level Module Architecture

Generic Timing Diagram

Specific Library

103

Design Methodology

InputData

Global Data-path

OutputData

Module Name

Sub-Module 1

Start1 Start2 Start3 StartnEnd1 End2 End3 Endn

Start End

Clk

Sub-Module 3

Sub-Module 2

Reset

Sub-Module n

Global Control UnitSel en

Third Level Module Architecture

2) Design of the whole algorithm architecture

Specific Library

104

Design Methodology

Sequencer

Data-path

LP_Filter

isa

isb

isd

isq

r

dq

isddq dq, TL, sd and sqEstimator

Sequencer

Data-pathabc-to-dq

transformation

Sequencer

Data-path

Integrator

Sequencer

Data-path

TL sd sqGlobal data-path

Global sequencer

FOC Estimator Architecture

Example : FOC Estimator algorithm architecture

105

Design Methodology

3) VHDL coding of the architecture

106

System Level

Behavioral Level

RTL or Synthesis Level

Physical Level

Simulation Simulation

Synthesis

Behavioral HDL

Circuit Specifications

Simulation Simulation

Analog HDL

Test Bench

Mixed Simulation Environment

FPGA

ASIC

Design Methodology

3) VHDL coding TOP DOWN Approach

107

Reuse and IP Behavioral Model

Blocks

LibraryLibrary

RTL or Synthesize Level

Physical Level

Behavioral Level

System Level

LibraryLibrary Reuse and IP RTL or Synthesize Model Blocks

Design Methodology

3) VHDL coding - Reusability

108

Design Methodology




Architecture Design

Validation of the architecture

109

Design Methodology

FPGA Target

Configuration process

Stimuli Patterns

TxRx

Architecture to be tested

Serial interface

Host-PC Results Comparison Results

Reception

Simulation Results Hardware in the loop Results

First attempt success guarantee

Functional model simulation

1) Hardware in the loop test

110

Design Methodology

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35-5

-4

-3

-2

-1

0

1

2

3

4

5

isd

isq

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35-5

-4

-3

-2

-1

0

1

2

3

4

5

isd

isq

Simulation results (isd(A) and isq(A)) Hardware in the loop results (isd(A) and isq(A))

time(s) time(s)

Example : Hardware in the loop results of the FOC Estimator

Start-up and a speed reversal at 0.27s of a 1 Kw induction machine controlled by a classical Indirect Field Oriented Strategy.

111

Design Methodology

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35-8

-6

-4

-2

0

2

4

6

8

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35-8

-6

-4

-2

0

2

4

6

8

Simulation results (T(Nm)) Hardware in the loop results (T(Nm))

time(s) time(s)

112

Design Methodology

Simulation results r(Wb)

time(s)0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Hardware in the loop results r(Wb)

time(s)0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0

0.1

0.2

0.3

0.4

0.5

0.6

0.7

0.8

0.9

1

Slight difference between simulation and hardware in the loop results

113

Design Methodology

2) Experimental test

FPGA (Actel Fusion) 114

Design Methodology

FPGA (Actel Fusion)

115

Conclusion

Algorithm Hardwarearchitecture

Design Methodology

Advantages :

Less intuitive and more automatic approach

Reduction of the development time

Optimization of the consumed resources

Reusability of the design

Development of a specific library

First attempt success guarantee116

FPGA-Based Current Controllers for

Synchronous Machine Drive

Advantages & Features

1st Case Studies Series:

117

Control Algorithm Execution Time

(a)

(b)

(c)

(k-1)Ts (k)Ts (k+1)Ts

(k-1)Ts

TADC

(k)Ts

(k+1)Ts

(k+1)Ts

TC

(k)Ts

(a)

(b)

(c)

(k-1)Ts (k)Ts (k+1)Ts

(k-1)Ts

TADC

(k)Ts

(k+1)Ts

(k+1)Ts

TC

(k)Ts

(a) General purpose microcontroller:- c limitations !

(b) DSPcontroller:- VSI limitations

(c) FPGA-based controller:- Quasi-analog behavior

118

Experimental Set-up

InterfaceInterface

Vf

Amplification

Electrical SupplyElectrical Supply

ADC

Controlled Controlled InverterInverter

Synchronous MachineSynchronous Machine

Encoder

isbisb

FPGAFPGA

Controller

Serial Interface

ADC Interface

isa

Sa Sb Sc

ReferencesRS232

isa isbADC Control

Host PC

isbisa

Encoder Interface

dq

119

Voltage Source Inverter

Encoder

Current sensors

SM

Experimental Set-up

120

Experimental Set-up

FPGA Spartan3

400.000 GatesAD Conversion Board

VSI Interface

Board

121

Current Controllers Based on ON-OFF Regulators

122

Current Controllers Based on ON-OFF regulators

9 Simplest current regulation schemes

Tow Main groups

Variable switching frequency ON-OFF regulators

Limited switching frequency ON-OFF regulators

9Well adapted for analog controls 9Well adapted for analog & digitalcontrols

123

Variable Switching Frequency ON-OFF regulators

9 Example 1 : Independent three phase free running hysteresis regulators

Sa

Vrd

SM

SbSc

isa*

isb*isc*

isa isb isc

isd*

isq*

Encoder

dq

dq-to-abc

p

E

124



wait

Start_AD=1wait

End=1

Start_OO=1

Start=1

Reset

End_AD=1

Global control unit FSMGlobal control unit

ADInterface

dq-to-abc2 level hysteresis

comparators

isa*

isb*

isc*isd*

isq*

Algorithm control unit

Start End

SaSbSc

isaADisbAD

AD Control

Clk Clk

ON-OFF Current controllerClk

dq

Clk

isaisbiscClk

End_ADStart_AD

Start_OO End_OO

H

Hardware Architecture

9 TS = TAD = 2.4 s

9 Tex= TAD+ tIP+ tH2 = 2.74 sController computation time

Ts

Tex

Application Sa,b,c[k-1]

tAD tIP tH2tAD tIP tH2

tAD tIP tH2

Application Sa,b,c[k] Application

Sa,b,c[k+1]

Sample isa[k-1]isb[k-1] dq[k-1]

Sample isa[k]isb[k] dq[k]

Sample isa[k+1]isb[k+1] dq[k+1]

125


Low execution time

Effects of sampling and delays are very negligible

H

isaisa

isaisa

H

Execution time = 50 Execution time = 50 ss Execution time = 2.74 Execution time = 2.74 ss

H

isaisa

H

isaisa

126


Low execution time


H

isa

isaisb


H

isa

isaisb

H

isb

H

isb

127


Sa

Vrd

SM

SbSc

isa*isb*isc*

isaisb isc

isd*

isq*

Encoder

dq

dq-to-abc

p

E

Table

abc-to-

abc-to-+-

+-

is*

is*

isis

isis

isb

129


Low execution time


H

isis

isis

H


H

isis

H

isis

130


Low execution time


H

isis

isis

H


H

isis

H

is is

131

Limited Switching Frequency ON-OFF regulators


Sa

Vrd

SM

SbSc

isa*isb*isc*

isa isb isc

isd*

isq*

Encoder

dq

dq-to-abc

p

ETs

132



wait

Start_AD=1wait

End=1

Start_OO=1

Start=1

Reset

End_AD=1

Global control unit FSM

9 TS = tAD = 100 s

9 Tex= tAD+ tIP+ tH2 = 2.74 sController computation time

Application Sa,b,c[k]

Sampleisa[k]isb[k] dq[k]

Ts

FsStart

Tex

tAD tIP tH2 tAD tIP tH2

Ts

Sampleisa[k+1]isb[k+1] dq[k+1]

Application Sa,b,c[k+1]

Global control unit

ADInterface

dq-to-abc2 level hysteresis

comparators

isa*

isb*

isc*isd*

isq*

Algorithm control unit

Start End

SaSbSc

isaADisbAD

AD Control

Clk Clk

ON-OFF Current controllerClk

dq

Clk

isaisbiscClk

End_ADStart_AD

Start_OO End_OO

H

Hardware Architecture

133


Low execution time


isa


isa

THD=14.9% THD=8.9%

Square current vector error (is+is) Square current vector error (is+is)

134


9 Example 2 : Space vector based regulator with three level hysteresis comparators and look-up table working in the - reference frame

Vrd

SM

isa*isb*isc*

isaisb isc

isd*

isq*

Encoder

dq

dq-to-abc

p

E

Table

abc-to-

abc-to-+-

+-

is*

is*

isis

isis

isb

137

Current Controller Based on PI Controllers

138


Sa

Vrd

SM

SbSc

Vsa*Vsb*Vsc*

isa isb isc

Vsd*

Vsq*

Encoder

dq

dq-to-abc

p

E

PWM Modulator

dq-to-abc

isd

isq

isd *

isq *

+-

+-

139


abc-to-dq

isd*

isq*

AD Interfaceis1AD

is2AD

AD Control

Global control unit

Algorithm controller

StartEnd

Clk

Clk

Clk

Vector current controller

isaisb

Clk

Start_VC End_VC

End_ADStart_AD

PIClk

Clk

PI

dq-to-abc

Clk

Vsd*

Vsq*PWM

Vsa*

Vsb*

Vsc*

Clk

dq

Sa

Sb

Sb

isqisd

Hardware Architecture140


9 Case 1 : Synchronized PWM

Application Vsa,b,c*[k]


tPWM/2Tex tPWM/2

Carrier

Start

End_VC

Ts = tPWM/2

tAD tVC tAD tVC tAD tVC

Application Vsa,b,c*[k+1]


Application Vsa,b,c*[k+2]


9 TS = TPWM / 2 9 Tex= tAD+ tVC = 3.28 sVector Control computation time

141


9 Case 1 : Synchronized PWM

11 >

2 >

1) Ch 1: 200 mVolt 250 us 2) Ch 2: 2 Volt 250 us

Carrier

Ts

11 >

2 > 1) Ch 1: 200 mVolt 10 us 2) Ch 2: 2 Volt 10 us

1 >

2 > 1) Ch 1: 200 mVolt 10 us 2) Ch 2: 2 Volt 10 us

Carrier vertex

Start End_VCTex Start End_VCTex

Carrier vertex

142


9 Case 2 : Non Synchronized PWM

Application Vsa,b,c*[k]


tk tk+1 tk+2 tk+m tk+m+1 tk+m+2

Tex

Carrier

Ts

Application Vsa,b,c*[k+m]

Sampleisa[k+m]isb[k+m] dq[k+m]

11 >

2 >

1) Ch 1: 200 mVolt 2.5 us 2) Ch 2: 1 Volt 2.5 us

Start End_VC

Carrier

Ts Tex

9 TS = 5 s 9 Tex= tAD+ tVC = 3.28 sVector Control computation time

143


isa

THD=11.1%

isbCarrier Frequency = 1KHz

Carrier Frequency = 1KHz

THD=11.1%

isa

Carrier Frequency = 3KHz

isa

isb

isa

isb

9Experimental Results

THD=4.1%

144


9Experimental Results

11 >

2 >

1) Ch 1: 1 Volt 25 ms 2) Ch 2: 1 Volt 25 ms

isd

isq

Vsa

Vsb

145

Predictive Current Controller

146


+

=

rd

sq

sd

dqsq

sr

sq

sd

sq

sd

sqdq

sq

sd

dqsq

sd

sd

sq

sd

iVV

tLM

L

Lii

Tt

LL

tLL

T

dtdidt

di

)(10

001

1)(

)(1

9 Sate model of the synchronous machine in the dq rotor reference frame

9 Digital Prediction Equations

+==

+=+

+=+

][][][][][][][][

][)1(])[][(]1[

][)1(])[][(]1[

kikMkikLkekikLke

where

kiTT

kekVLT

ki

kiTT

kekVLT

ki

rddqsrsddqsdsq

sqdqsqsd

sqsq

ssqsq

sq

ssq

sdsd

ssdsd

sd

ssd

147


=

js

js

dqdq

dqdqj

sq

jsd

VV

VV

)cos()sin()sin()cos(

7 different stator voltage vectors Vsdqj=[Vsdj Vsqj]t (j=0..7)

7 different directions tj(j=0..7) and errors j(j=0..7)

+==

+=+

+=+

][][][][][][][][

][)1(])[][(]1[

][)1(])[][(]1[

kikMkikLkekikLke

where

kiTTkekV

LTki

kiTTkekV

LTki

rddqsrsddqsdsq

sqdqsqsd

sqsq

ssq

jsq

sq

sjsq

sdsd

ssd

jsd

sd

sjsd

]1[][]1[ * +=+ kikiki jsdqsdqjsdqrrr

][]1[][ kikikt sdqj

sdqj

rrr +=

148


d

q

isdq[k]

isdq*[k]t0,7 t4

t5

t6t2

t3

t1

isdq1[k+1]isdq1[k+1]

isdq[k]isdqj[k+1]

isdq*[k]

isdqj[k+1]tj[k]

Predicted current error vector Predicted current error vector isdqisdqjj Example of different prediction possibilitiesExample of different prediction possibilities

149


SM

Vrd

dq

Optimization

E

isd*

isd

isq

esd esq

dq

(isdqj)(j=0..7)SaSbSc

Prediction

Couplingterms

isq*

pm

d/dt

isa

isbabc-to-dq

9 Predictive Controller Principle

150


9 Hardware architecture

wait

Start_AD=1wait

End=1

Start_OO=1

Start=1

Reset

End_AD=1

Global control unit FSM

9 TS = 100 s

9 Tex= tAD+ tPr = 4.52 sPredictive Controller computation time

AD Interface

isaADisbAD

AD Control

SaSbSc

Global control unit

Algorithm controller

Start End

Clk

ClkPredictive current controller

Start_Pr End_Pr

End_ADStart_AD

EAD

abc-to-dq

Clk

Couplingterms

Clk

Prediction& optimization

Clk

isd*isq*

E

isdisq

esdesq

Clk

Speed Estimator

Clk

p

offset

dq++

m

isa

isb

dq


Sampleisa[k] isb[k] dq[k]

FsStart

Ts

Tex TstAD tPr tAD tPr



151


9 Experimental Results

isa

THD=8.8% isb

THD=8.8%

isa

isa

isb

Vsa

Vsb

152



+ Isn

- Isn

+ Isn

- Isnisd

isq

isd

isq

153

FPGA-Based speed control for

Synchronous Machine Drive using PPI controller

154

Problem Positioning

Objective : Development of a high performance FPGA-based speed controller

Most important criteria for the speed control

9 Fast speed dynamic

9 Accurate speed response

9 Quick speed recovery from disturbances

155

Speed Controller Design

Vsd

isd

Vrd

ird

Vsqisq d

q

dq Sa

dq

sqsd

sdssd dtd

iRV +=

sdsq

sqssq dtd

iRV ++=rdsrsdsdsd iMiL +=

sqsqsq iL=

sdsrrdrdrd iMiL +=)(

23

sdsqsqsde iipT =

9 Synchronous machine model

156


9 Current controller

Sa

Vrd

SM

SbSc

isa*

isb*

isc*

isa isb isc

isd*

isq*

Encoder

dq

dq-to-abc

p

E

157


9 Current controllerCurrent Controller Timing Diagram

TAD TCC TAD TCC

Ts=100 s Ts=100 s

tk tk+1

Tex=2.74s

Sample isa,b[k]dq[k]

tk+Tex


tk+1+Tex

Sample isa,b[k+1]dq[k+1]


time

isa isb

isa

isb

isq

isd

Isn

- Isn

158


9 Speed controller synthesis

Current Control Loop

Speed Control LoopInternal Loop (Proportional controller)

External Loop (PI controller)

isq1

1+sT isqKvPI*

+-

+-

i isq*

pMsrird-+

fJsp+

Tr

159



Internal Loop (Proportional Controller)Impose the controlled system poles at the desired positions

Internal speed control loop transfer function

isq

rdsrv

isq

isq

rdsrv

i

JTiMpKs

Ts

JTiMpK

5.11

5.1

++=

=1

Proportional Gain

2)2

1(

1

isq

i

Ts +

=

Re

Im

=1

Roots Locus 160



PI* +-

2)2

1(

1

isqTs +

External Loop (PI Controller)- Zero steady-state error

- Impose the shape and the dynamic of the speed response

External speed control loop transfer function

isq

rdsrvp

isq

isq

rdsrvp

JTiMpKK

sT

s

JTiMpKK

5.12

1

5.1

*

++=

isq1

1+sT isqKvPI*

+-

+-

i isq*

pMsrird-+

fJsp+

Tr

2n n2

161



Current Controller

Speed ControllerSa

400V/50Hz

Vrd

SM

SbSc

isa*

isb*

isc*

isa isb isc

isd*0isq*Kv

Encoderd/dt

Speed Estimator

dq

dq-to-abc+

-

+

-*

Internal Loop

External Loop

162


9 Speed estimator design

)]1[][

(1024

4][T

kkk mm =

SM1024 points

Absolute Encoder

10 bits(P9 P8..P1 P0)

Backward difference

Variable sampling periodOperating mode synchronized with state changes of the LSB of theencoder

+ 1

kTSensek 1

10244][ =

Denotes the time spent for one unit displacement of the encoder

Determined via the state changes of the two LSB P0 and P1

163



P0Counter 0 1 2 nk 0 1 2 nk+1

Tk T(k+1)

1/Fc

c

kk F

nT =

Tk ComputationSense Computation

-1(negative)1011

+1(positive)0011

-1(negative)0110

+1(positive)1110

-1(negative)0001

+1(positive)1001

-1(negative)1100

+1(positive)0100

SenseP1[k+1]P0[k+1]P1[k]P0[k]

kTSensek 1

10244][ =

Denotes the time spent for one unit displacement of the encoder

Determined via the state changes of the two LSB P0 and P1

164



Speed Estimator Hardware ArchitectureSpeed Estimator Hardware Architecture

Compteur

nk

Fcompt

Rc

- +

0en2

en3

en0

en1

en0

en1

Sense Computation

XORd0

P0 P1

ETAT0

ETAT1en0=1

ETAT2Fcompt=1

S

||-||

ETAT3en2=1

ETAT4en3=1

ETAT5en1=1Rc=1

Reset

Clk Start=1

Clk

Clk

Clk d0=0

d0=1

Clk

Clk

Clk

kTSensek 1

10244][ =

Data-Path

Control Unit

165


9 Speed controller architecture

Speed Controller Timing Diagram

TAD TCC TAD TCC

Ts=100 s Ts=100 s

tk tk+1

Tex=3.45s

Sample isa,b[k]dq[k]

tk+Tex


tk+1+Tex

Sample isa,b[k+1]dq[k+1]


time

FPGA-based Speed controller

Global control unit

Speed controller control unit

AD InterfaceP-PI

(dq/123)3 Phases hysteresis controller

Speed estimator

m

offset

Clk Clk Clk Clk

Clk

C1C2C3

Clk

Clk

isd*=0

*

Start End

is1 is2 is3

is1_ADis2_ADAD

control

isq*

is1*

is2*

is3*

TSCTSC

Note : The speed estimator works independently from the other modules and is synchronized to the state changes of the LSB of the encoder

166


InterfaceInterface

Vrd

Amplification A/DEncoder

isbisc

dq

FPGAFPGA

Speed Controller

Serial Interface

AD Interface

isa

Sa Sb Sc

ReferencesRS232

isa isbAD Control

Host-PC

isaisb

Spartan3 Xc3s400 (400.000 gates)

400V/50Hz

9 Experimental Set-up

167


9 Experimental ResultsStep Speed Response Speed tracking performance

=200 rad/s

=0 rad/s

=-200 rad/s

=200 rad/s

=-200 rad/s

=200 rad/s

=200 rad/s

=0 rad/s

168



isa

isb

Current waveforms

isa

isb

Current waveforms for a reversal speed operation

Response to a step of a rated load torque

TL=5Nm

169

Conclusions

A full FPGA-based speed controller for SM drive has been presented

A very efficient P-PI speed regulator has been synthesized

An original speed estimator has been developed, it allows to obtain the best accuracy

An original speed estimator has been developed, it allows to obtain the best accuracy

The obtained experimental results give proof of the ability of the developed speed control system to achieve an efficient and robust speed control under different operating conditions

170

Induction Motor Experimental Set-up

IMIM400V/50Hz

LOAD

Encoder

10

AD Control

ReferencesRS232

12

12

Gate pulses

AD Interface

UART

isaisbisc

FPGA

ADcontrolleralgorithm

VSI Interface


VSIInterface

and Control Boards

IM

L E

Laboratoire Systmes lectriques172


VSI Interface

Board

AD Converters Board

FPGA Spartan 2

100.000 Gates

173


Load Incremental Encoder

Induction Machine

Load Control VSI

University of Aleppo

174


VSI Interface Board

ADC Board

FPGA Spartan 3 400.000 Gates

175

2nd Case Studies Series:

FPGA-based Intelligent Controllers for AC Drives and AC Generators:

* A PWM control system modelling / design / FPGA implementation using VHDL

9 Modelling an induction motor drive system using an FPGA PWM neural controller

9 Modelling a diesel driven generator employing fuzzy-logic/PWM FPGA control

176

* PWM Control System Design Using VHDL

SYNCHRONISATION: (Carrier-triangular / M odulator-sinusoidal)Counter output bus

Triangular waveform generator M ax_count

M ax_count Clock (Reversible up-down counter)

Start Reset OUT_SIGNAL CONTROL COM PARATOR

Clock (PW M )

Next Address M emory generator

(Sinewave)

177

Three-Phase Sinusoidal PWM Pattern Generation

178

Block diagram of the 3-phase PWM circuit

179

Complete VHDL Code - 1 Phase PWM Generatorlibrary ieee;use ieee.std_logic_1164.all;entity pwm is

port(out_signal: out std_logic;clock,start: in std_logic;Max_count: in integer);

end pwm;architecture behav of pwm is

signal counter_out_bus : integer;signal next_pulse,reset: std_logic;signal val_max, adr, data: integer;

begincounter_rev: process(clock,reset)

variable direction: std_logic :='1';variable v: integer :=0;

beginif reset'event and reset='1' then

v:=1;elsif clock'event and clock='1' then

if direction='1' thenif v-val_max thenv:=v-1;

elsev:=v+1;direction:='1';

end if;end if;

end if; counter_out_bus=0 and adr

181

architecture arch_test of test iscomponent pwm

port(out_signal : out std_logic;clock,start: in std_logic;Max_count: in integer);

end component;signal clock: std_logic :='0';signal start: std_logic := '0';signal Max_count: integer;signal out_signal: std_logic;

beginMax_countMax_count,

out_signal=>out_signal);end arch_test;configuration conf_test of test is

for arch_testend for;

end conf_test;

reset

185

The RLe Equivalent Circuit of the Induction Motor

( )[ ] ( )

==

+=++==

=

s

s

srer

srr

r

mssm

srrer

srr

r

m

s

r

2mrs

iiuu

jiRLLiLiLjiR

LLe

RRL

LLLL

186

The Neural PWM Controller

187

Speed Control PrincipleszThe control is achieved in polar coordinates (module and angle).zThe rotor speed is controlled by compensating the slip frequency.zSlip frequency is kept constant for any load torque & any rotor speed.zThe slip frequency depends on the angle between e and is,,, controlled

by means of:* stator frequency* stator current amplitude

zThe current amplitude Is is corrected according to the position of vector ein the complex plane.zThe stator frequency fs follows the reference speed profile. zVery fast stator frequency changes have to be avoided because they cause

slow transient response.

188

Basic Control Algorithm

Improved Control Algorithm

Simulation

189

Neural PWM Controller VHDL Design for Implementation

190

Simulation /Test Results PWM Neural Controller

191

Test Results - Motor

Speed control at step torque riseControlled versus natural torque characteristic

192

Achievements

zInduction motor drives can be controlled using neural algorithms, implying a smaller number of calculations than vector control.

zThe proposed speed control algorithm can be expressed as a set of mathematical equations written in polar co-ordinates.

zThe angle and sector calculations are carried out by hardware implemented neural networks.

zThe entire control scheme has been modelled and designed in VHDL, synthesised and implemented into Xilinx XC4010 FPGA.

zThe implementation offers a cost-effective solution for industrial applications without high dynamic requirements.

zTest results have confirmed correct operation of the controller.

193

2. MODELLING A STAND ALONE DIESEL DRIVEN GENERATOR SET USING

FUZZY-LOGIC AND PWM CONTROL

SynchronousGenerator

Diesel Engine

PWM ControlPWM ControlFuzzyFuzzy ControlControl

VDC

Fuel Control

RECTIFIER PWM INVERTER

C

STAND-ALONE

GENERATOR

3 phaseoutput

FPGA FPGA ControllerController

194

Project BackgroundIn a given synchronous machine the operational speed is dependent onthe desired output frequency.

Variable speed operation of generators increases design freedom: speedis not determined by the desired electrical frequency.

It allows engine-generators systems to be operated at speeds whichoptimise desired parameters such as noise, vibrations, fuel efficiency, engine emissions.

The research aim is to design and build a control system for a stand alone variable speed PM synchronous generator.

This has been developed on the basis of fuzzy logic, using VHDL and is implemented in Xilinx FPGA.

195

PWM Inverter Simulation Results

-300

0

300

600Vout

Vdc

time [ms]196

Fuzzy Variable Speed Governor Fuzzy Variable Speed Governor (FVSG) - controller based on fuzzy logic.

Designed using VHDL for easy correction and future integration with othercomponents to extend the system.

System configuration allows variable speed operation of the generator.

valve engine generator rectifier inverter

Fuzzifier

FuzzyInferenceMachine

Fuzzy Rule Base

Defuzzifier

xx 11

xx 22

a.c.output

FVSGFVSG

PWMControl

ddt

197

DC Voltage Fuzzy Controlled Response to Load Current Step Increase

0

200

400

600

800

1000

1200

1400

1 21 41 61 81 101 121 141 161 181 201 221 241 261 281 301 321 341 361 381

ILOAD =10A

ILOAD =20A

DC Voltage (Normalised to 1000)Load Current

Reference Voltage

time (sampling units)

Voltage (normalised)

198

050

100150200250300350

0 5 10 15 20 25 30 35 40 45

time [sec]

d

.

c

.

v

o

l

t

a

g

e

[

v

o

l

t

]

Experimental Test Results

050

100150200250300350

0 5 10 15 20 25 30 35 40 45

time [sec]

d

.

c

.

v

o

l

t

a

g

e

[

v

o

l

t

]

Without controller With controller

Step Change in a.c. Load Current d.c. Voltage response

199

AchievementsPWM controller

voltage control using PWM is a simple and effective strategy forobtaining and maintaining the desired output voltage parameters.

Fuzzy logican effective design solution for the speed governor.able to produce a competent control system without the need for a precise mathematical model of the plant.the controller is reconfigurable by changing the rule base.design can be easily extended to include more parameters.

VHDLdesign, modelling & simulation performed on a single platformthe same design tool can be used for hardware implementationreusable design modules are producednew developments of the design can easily be performed

200

General ConclusionsA novel modelling technique is proposed for the holistic investigation of engineering systems. This is based on Hardware Description Languages (VHDL).

The sample systems were developed from idea, through modelling / simulation, to complete systems commissioning, in short time, giving further advantages: 9easy integration of electronic controllers in complex engineering system models. 9 reliable framework for design verification9high confidence in correct first time operation 9allows rapid FPGA prototyping of electronic controllers9gives multiple choices for controllers final implementation technology9high degree of flexibility

A CAD platform independent model & design are developed and therefore valuable IPs can be produced, in co-relation with the modern principles of design reuse.

Concurrent engineering basic rules (unique EDA environment and common design database) are fulfilled.

Estimation: HDL based holistic modelling methodologies will be increasingly used in the future and expanded to encompass other areas of engineering systems.

201

Recent DevelopmentsHandelHandel--CC a novel compiler for Hardware-Software co-design from Celoxica.

C/C++ System ModelHandel-C compiler Assembly code compiler

VHDL hardware description Microprocessor software code

RosettaRosetta is a language for modelling/describing engineering systems Presently the focus is on complex electronic systems -> SOC Being explored for complex mechanical systems Defines systems by writing and composing models with respect to domains. Consists of a syntax (a set of legal descriptions) and a semantics (a meaning

associated with each description)

MilleniumMillenium MachineMachine new EPSRC (UK) funding initiative for holistic modelling of engineering systems (systems of systems). 202

General Conclusions

The simultaneous increase of the control algorithm complexity and the chip density implies the use an efficient design methodology. A modeling technique is proposed for the holistic investigation of power electronic systems. This is based on System Level Modeling Languages or HDL and allows rapid FPGA prototyping of the control systems. Three main design rules are presented.

the algorithm refinement, the modularity, the systematic search for the best compromise between the control performances and the architectural constraints (see A3 section).

Full and timely examples are presented to illustrate the benefits of FPGA implementation when using the proposed design approach. It is demonstrated that in both cases a low cost FPGA-based controller can greatly improve the control performance, especially due to the reduction of execution time, while keeping a high level of flexibility.

203

Perspectives In the near future, the complexity of the control systems will continue to grow.

The tasks devoted to the control algorithm will no longer be limited to regulation but will have to manage diagnosis and fault-adaptive on line control.

The research effort on the theory and the applications of dynamic reconfiguration is crucial.

Network-on-a-Chip (NoC) SoC design that can include digital control and its analog interface (sensors, ADC, power drivers, etc.).

Co-design issue must be addressed, since the borders between software and hardware are rapidly vanishing. The main problem in this case is to propose automatic rules of partitioning, based on relevant

quantitative indicators.

Another interesting direction of research is based on the following observation: a control algorithm, when implemented in an FPGA, can have a very short execution time due to the high degree of parallelism of its architecture. At the same time, the constraints imposed by the power electronic components imply a sampling period that is much higher than the execution time. The resulting wasted time could be advantageously employed.

Several examples of relevant FPGA utilizations in this context were presented. They consist of predictive control, over-sampling strategies, multi-plants control, etc. All these very promising control paradigms must still be improved.

204

BibliographyM.N. Cirstea, A. Dinu, J. Khor, M. McCormick, "Neural and Fuzzy Logic Control of Drives and Power Systems", Elsevier Science Ltd., 2002.M.N. Cirstea, A. Dinu, D. Nicula: "A Practical Guide to VHDL Design", EdituraTehnica, Bucharest, Romania, 2001, ISBN: 9733115398.A. Dinu: "FPGA Neural Controller for Three Phase Sensorless Induction Motor Drive Systems", PhD Thesis, De Montfort University, 2000.J. Khor, "Intelligent Fuzzy Logic Control of Generators", PhD Thesis, De Montfort University, UK, 1999.A. Zregh: Holistic Modelling of Stand Alone Generators, MPhil thesis, De Montfort University, UK, 2003. B.K Bose: Modern Power Electronics & AC Drives, Prentice Hall, 2002.M. P. Kazmierkowski, R. Krishnan, F. Blaabjerg, J. D. Irwin (Editors): Control in Power Electronics: Selected Problems, Academic Press, 2002. D.L. Perry: "VHDL", McGraw-Hill, 1998.Xilinx home page: http://www.xilinx.com/Celoxica home page: http://www.celoxica.com/Rosetta home page: http://www.sldl.org/

205

Bibliography F. Ricci, H. Le-Huy, An FPGA-based rapid prototyping platform for variable-speed drives, in Proc. IEEE IECON02 Conf., 2002, pp. 1156-1161. L. Charabi, E. Monmasson, I. Slama-Belkhodja, Presentation of an efficient design methodology for FPGA implementation of control system application to the design of an antiwindup PI controller, in Proc. IEEE IECON02 Conf., 2002, pp. 1942-1947. R. Andraka, A survey of CORDIC algorithms for FPGAs, in Proc. ACM/SIGDA Conf., 1998, pp. 191-200. S.A. White, Applications of Distributed Arithmetic to Digital Signal Processing: A Tutorial Review, IEEE ASSP Mag., pp. 4-21, July 1989. F. Zhengwei, J.E. Carletta, R.J. Veillette, A methodology for FPGA-based control implementation, IEEE Trans. Control Systems Technology, Vol. 13, n6, pp. 977-987, Nov. 2005. D. Menard and O. Sentieys. Automatic Evaluation of the Accuracy of Fixed-point Algorithms, in Proc. IEEE/ACM Conference on Design, Automation and Test in Europe, 2002, CD-ROM. K. Kebbati, Y.A. Chapuis, F. Braun, IP modules for motor control FPGA/ASIC integration, in Proc. IFIP Conf., 2001, pp. 385-390. Texas Instruments DSC Group, A software modularity strategy for Digital Control System motor, SPRU485A, August 2001,Revised October 2003. T. Grandpierre, C Lavrenne and Y. Sorel, Optimized rapid prototyping for real-time embedded heterogeneous multiprocessor, in Proc. CODES99 7th International Workshop on Hardware/ Software Co-Design Conf., 1999, CD-ROM. E. Monmasson, J.C. Hapiot, M. Granpierre "Analysis of a current controller for AC drives entirely based on FPGAs," in Proc. ICEM, Conf., Sept. 1994, vol. 3, pp. 1-5. S. Berto, A. Paccagnella, M. Ceschia, S. Bolognani, M. Zigliotto, Potentials and pitfalls of FPGA application in inverter drives - a case study, in Proc. IEEE ICIT Conf., 2003, Vol. 1, pp. 500-505. Y.A. Chapuis, J.P. Blonde, F. Braun, FPGA Implementation by Modular Design Reuse Mode to Optimize Hardware Architecture and Performance of AC Motor Controller Algorithm, in Proc. of 11th EPE-PEMC Conf., 2004, CD-ROM. K.V. Ling, S.P. Yue and J.M. Maciejowski, Model Predictive Control on a Chip, in Proc. IEEE ACC Conf., 2006, CD-ROM. A. Fratta, G. Griffero, S. Nieddu, Comparative analysis among DSP and FPGA-based control capabilities in PWM power converters, in Proc. IEEE IECON Conf., 2004, Vol. 1, pp. 257-262. F. Blaabjerg, P.C. Kjaer, P.O. Rasmussen, C. Cossar, Improved digital current control methods in switched reluctance motor drives, IEEE Trans. Power Electron., vol. 14, n3, pp. 563-572, May 1999. O. Garcia, P. Zumel, A. de Castro, J.A. Cobos, J. Uceda, An automotive 16 phases DC-DC converter, in Proc. IEEE PESC Conf., 2004, Vol. 1, pp. 350-355. J. Chen; P.C. Tang, A sliding mode current control scheme for PWM brushless DC motor drives, IEEE Trans. Power Electron., vol. 14, n3, pp. 541-551, May 1999. C. Attaianese, V. Nardi, G. Tomasso, A Novel SVM Strategy for VSI Dead-Time-Effect Reduction, IEEE Trans. Indus. Appl., vol. 41, pp.1667-1674, Nov/Dec 2005.

206

K. Bondalapati, V.K. Prasanna, Reconfigurable computing systems, Proceedings of the IEEE , Vol. 90, pp. 1201-1217, Jul. 2002. E. Monmasson; B. Robyns; E. Mendes, B. De Fornel, Dynamic reconfiguration of control and estimation algorithms for induction motor drives, in Proc. IEEE ISIE Conf., 2002, pp. 828 833. Y.Y. Tzou, J.J. Jyang, A programmable Current Vector Control IC for AC Motor Drives, in Proc. IECON99 Conf., 1999, CD-ROM. K. Tazi, E. Monmasson and J.P. Louis, Description of an entirely reconfigurable architecture dedicated to the current vector control of a set of AC machines, in Proc. IEEE-IECON99 Conf., 1999, pp. 1415-1420. E. Monmasson, J.C. Hapiot, M. Granpierre, A digital control system based on field programmable gate array for AC drives, EPE Journal, vol. 3, n 4, Nov. 1993, pp. 227-234. Y-A. Chapuis, C. Girerd, F. Aubpart, J-P. Blond and F. Braun, Quantization problem analysis on ASIC-based Direct Torque Control of an induction machine, in Proc. IEEE-IECON98 Conf., 1998, pp.1527-1532. H.J. Lee; S.K. Kim; Y.A. Kwon; S.J. Kim, ASIC design for DTC based speed control of induction motor, in Proc. IEEE ISIE01 Conf., 2001, pp. 956 961. S.J. Henriksen, R.E. Betz and B.J. Cook, Digital hardware implementation of a current controller for IM variable-speed drives, IEEE Trans. Ind. Appl., vol. 35, pp.1021-1029, Sept./Oct. 1999. A.A. Jerraya, H. Ding, P. Kission, M. Rahmouni, Behavioral Synthesis and Component Reuse with VHDL. Kluwer Academic Publishers, 1998. T. Riesgo, Y. Torroja, E. De la Torre, Design methodologies based on Hardware Description Languages, IEEE Trans. Ind. Electron., vol. 46, pp. 3-12, Feb. 1999.

Bibliography

207

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