simulation tools for wireless automation - aaltogeta.aalto.fi/en/courses/lect11_geta_2009.pdf ·...

TKK | Control Engineering

Simulation Tools for Wireless AutomationSimulation Tools for Wireless Automation

Mikael Björkbom

TKK | Control Engineering AS-74.3199 Wireless Automation

ContentsContents

• Introduction

• Simulators for wireless/networked/embedded control systems

• PiccSIM-simulator

• Case studies


Wireless Automation Solutions

• Communications and control are interconnected!Simply: no data -> no control

• Development of control algorithms that tolerate jitter and losses

Robustness vs. performance

• Development of communication protocols and technologies that reduce jitter

• Need to evaluate different protocols/control methodsImpact on overall system?

Practical issues


Need for CoNeed for Co--Simulation ToolsSimulation Tools

• Complex systems, need simulation to study: PiccSIME.g. Effect of MAC/routing protocol on control performance

Networked and distributed application

• Simulation tools required to support co-design and co-simulation of both wireless and automation


Simulators for wireless/networked/embedded control system design


Categorization

• Asynchronous simulationPtolemy II

• Communication basedNs-2

• Dynamic agents• Control based

Simulink• Truetime

• Co-simulation platformsIntegration of communication and control simulation tools

• Ns-2 + Modelica• Ns-2 + Simulink (PiccSIM)


Ptolemy II

• Dynamic systems and asynchronous eventsDiscrete, asynchronous events

• Not real network modelsNo interference

Distance based radio range

Transmission delay

J. Eker, J.W. Janneck, E.A. Lee, J. Liu, X. Liu, J. Ludvig, S. Neuendorffer, S. Sachs and Y. Xion. Taming heterogeneity—the Ptolemy approach. In Proc. of the IEEE. Vol. 91, no. 1. 2003. pp. 127.144


The Network Simulator, Ns-2• Simulation of wired & wireless networks

Open source platformNew technologies quickly available

• Supported layersMAC, CSMA

• Link layer, RoutingTransport

• TCP, Streaming• Constant bitrate UDP

• PartlyApplication

• Ping, Telnet, FTP, HTTP• Processing at Sender & Receiver• Traffic generation

Physical• Radio propagation models


Ns-2

• Trace simulation eventsAnalyze results

• Network Animator, NAMVisual representation of simulation


Ns-2

• Ns-2 is for communication simulation

• Addition of Agents with dynamic propertiesOrdinary differential equations

Ns-2 ”samples” the Agent and sends the information

M.S. Branicky, V. Liberatore, S.M. Phillips. Networked control system co-simulation for co-design. In Proc. of the American Control Conference, 2003. vol. 4. 4-6 June, 2003. pp. 3341-3346.


TrueTime

• Impemented as S-functions (C-code) in Simulink

• Control engineering approach

• Used mainly for scheduling of CPUs

• Wired and wireless network modelsLAN, WLAN, Bluetooth, ZigBee

Simple network models

Network simulation accuracy questionable

D. Henriksson, A. Cervin and K.-E. Årzén. TrueTime: Simulation of Control Loops Under Shared Computer Resources. In Proc. 15th IFAC World Congress on Automatic Control. Barcelona, Spain. July 2002.


TrueTime

uy

r

TrueTime 1.5 Distributed Wireless Control SystemCopyright (c) 2007

Martin Ohlin , Dan Henriksson and Anton CervinDepartment of Automatic Control , Lund University , Sweden

Please direct questions and bug reports to : truetime @control .lth .se

u

reference

r, y

Wireless Network

snd1

snd2

rcv 1

rcv 2

P1

P2

Node 2(Controller )

A/D

Rcv

P

Snd

Node 1(Sensor /Actuator )

Rcv

A/D

P

D/A

Snd

P2

snd1snd2

P1

rcv2

rcv1[snd1]

[P1]

[snd2]

[rcv2]

[rcv1]

[P2]

Display

DC Servo

1000

s +s2

Clock


Integrated

• Ns-2 + Modelica

• PiccSIM: Ns-2 + Simulink

• Benefits from both fieldsAppropriate tools for comm. & contr. model building

Not complete integration

• Ultimately: fully featured single tool!


Ns-2 + Modelica

• Ns-2 controls simulationBoth on the same machine

• Ns-2 instructs Modelica to run to the next sample time

Exchange of informationNetwork simulation

• DrawbacksNo event based communication

Ns-2 + Modelica: Al-Hammouri, D. Agrawal, V. Liberatore, H. Al-Omari, Z. Al-Qudah, and M. S. Branicky. Demo Abstract: A Co-Simulation Platform for Actuator Networks. Sensys 2007.

Queued packets


PiccSIM simulator


PiccSIM

• Platform for integrated communication and control design simulation, implementation and modelling

• Main developers (@TKK): Mikael Björkbom & Shekar Nethi

• Integrates two widely used simulatorsNs-2: Communications system simulation

MATLAB/Simulink: Control design and simulation

Integration saves the burden of developing a complete simulator from scratch! (maintenance, updates...)

• Aim: to provide the tools and solutions for wireless automation

Communications and control co-design and co-simulation

All the required design tools in one environment


PiccSIM

• Simulink + ns-2• Simulink sends packets through ns-2

Separate computersUDP packetsSimulation time-synchronization between computers

• Application event based communicationSend on thresholdAlarms


PiccSIM: Integration of Simulink and nsPiccSIM: Integration of Simulink and ns--22


PiccSIM architecture

Server, DB

Remote User InterfaceMoCoNet GUI

Process

Simulink orxPC Target

I/O Board

Controller

Sensors

Internet

Ns-2 Network Simulator

Simulation

Configuration and management

PiccSIM ArchitectureLocal User InterfacePiccSIM Toolchain


ToolchainToolchain

• Main GUISimulink model

Ns-2 TCL script

PiccSIM block library

• Access to design toolsControl design

Network design

Code generation tools

• Start/Stop simulationCoordinates simulation

• Simulink and ns-2


PiccSIM Network Design ToolPiccSIM Network Design Tool

• Place wireless nodes

• Define network settingsPhysical, MAC, Routing...

Traffic, Agents...

Simulation settings

• Automatically generate TCL script for ns-2


Control design and simulation, MATLAB / Simulink

• Provides the tools required for versatile control designPID control

Fuzzy control

Neural networks

Model predictive control etc...

• High-level programming environment for simulations

• Almost any modelled plant and designed controller can be simulated in Simulink including

Signal processing components

Filtering

Estimation algorithms etc...

• Supports automatic code generation to implement the controllers on real-time operating systems


Simulink

• Control engineering friendly

Build application with Simulink

• PiccSIMReady made blocks for integration with Ns-2

Time-synchronization between Simulink and ns-2

Any system made with Simulink can be simulated with ns-2 network!


Scope of ToolchainScope of Toolchain

• Simulation ofWireless Networked Control System (WiNCS)

Sensor Network applications

• Application + network

Sensor node

Send to N 1 T 1Node

ID = 0

Reference

Out

Process

Process

Controller node

Timestamps

Data N 0 T 1

Node

ID = 1 Controller

ControllerPID

uy_ref

y


Automatic Code GenerationAutomatic Code Generation

• Simulation -> Implementation and testing on real hardware

• Generic node block in PiccSIM libraryMake implementation in block

• Simulink blocks, Matlab code...

• Radio blocks for communication between nodes

• Matlab Real-Time WorkshopTarget Language Compiler (TLC)

Generate code from Simulink block

• Wrapper main file for Sensinode node hardwareOther wrappers can easily be implemented

Process_interface

AD 0

Radio timestamp 1

Radio recv 1

DA 6

DA 7

Radio send 1


Automatic Code GenerationAutomatic Code Generation

Radio send 1

3

DA 7

2

DA 6

1

Tapped Delay

4Delays

Signal Specification

D:3 Saturation

Rate Transition

Gain 3

2.5

Gain 2

2.5/0.8 Gain 1

90/2.5

DetectChange

U ~= U/z

Data Type Conversion

double

Constant

L

Bias2

u-2.5/2

Bias1

u+0.4

Add

Radio recv 1

3

Radio timestamp 1

2

AD 0

1


PiccSIM – Key features

• Support for powerful control design and implementation tools provided by MATLAB/Simulink

• Capability to simulate any wired/wireless networks readily available in ns-2

• Automatic code generation from Simulink models for real-time execution on real wireless node hardware

• Real-time control of a true or simulated process over a user-specified network

• Easy-to-use network configuration tool and• The platform is accessible over the Internet, i.e. it supports

remote experimenting.


BUILDING AUTOMATION BUILDING AUTOMATION CASE STUDYCASE STUDY


Building Automation CaseBuilding Automation Case

Room

Access point

Wireless sensor

North

Elevator WC

Server

Kitchen

Control Café

Meeting room 1

Meeting room 2

WC1: 4.5x3.2

5: 3.9x4.5

3: 3.9x4.5

4: 3.9x4.5

6: 3.9x4.5

7: 4.5x4.58: 4.5x4 9: 4.5x6

10: 4.5x6

11: 3.9x4.5

12: 3.9x4.5

39: 8x6 38: 8x6 37: 6.8x7 36: 6.8x3.8 35: 6.8x5.2 34: 6.8x5 33: 6.8x5 32: 6.8x5 31: 6.8x4

16: 4.5x5.5

15: 2.5x4.5

14: 2.5x4.5

13: 2.5x4.5

17: 4.5x6 18: 4.5x3 19: 4.5x3

20: 2.5x4.5

21: 3.9x4.5

22: 3.9x4.5

23: 3.9x4.5

24: 4.5x4.5

25: 2.5x4.5

26: 2.7x4.5

27: 3.9x4.5

28: 2.7x4.5

29: 2.7x4.5

30: 3.9x4.52: 4.5x3.2

1: 3.9x4.5 = ID: (N-S)x(W-E)

4.5x3.2

4.5x2

11x1.6

22x1.6

2x60

11x1.6

Plaster wallConcrete wallBrick wall (50% glass windows)


Building Automation CaseBuilding Automation Case

• Temperature and ventilation control of office

• Wireless sensors transmit measurements to central controllerTemperature, CO2, desired temperature

Occupancy messages for lightning

• Controller calculates heating and airflow to each room

• Currently wired, what happens when wireless?


Key Features of CaseKey Features of Case

• Large number of nodes, much traffic

• Time-driven (temperature) + Event driven (people enter the room)

• Static (no node mobility)

• Indoor => reduced communication rangeMultihop

• Slow process dynamics compared to networkPacket drop problems

Transmission time << Process time-constant


Wireless Control LoopWireless Control Loop

Room

Sensor node

Send to N 1 T 1Node

ID = 0

Reference

Out

Process

Process

Controller node

Timestamps

Data N 0 T 1

Node

ID = 1 Controller

ControllerPID

uy_ref

y

Wireless communication

RoomTemperature sensor

Access point


Case studies: Wireless building automation system

• Physical models:Heat balance in rooms (PID control)

CO2 concentration in rooms (relay control)

Event driven signals, lighting (on/off)

• Communication model:Zigbee radio module (15m range)

Ricean indoor propagation channel model

Room

Acces point

Wireless sensorNorth

Elevator WC

Server

Kitchen

Control Café

Meeting room 1

Meeting room 2

WC1: 4.5x3.2

5: 3.9x4.5

3: 3.9x4.5

4: 3.9x4.5

6: 3.9x4.5

7: 4.5x4.5 8: 4.5x4 9: 4.5x6 10: 4.5x6

11: 3.9x4.5

12: 3.9x4.5

39: 8x6 38: 8x6 37: 6.8x7 36: 6.8x3.8 35: 6.8x5.2 34: 6.8x5 33: 6.8x5 32: 6.8x5 31: 6.8x4

16: 4.5x5.5

15: 2.5x4.5

14: 2.5x4.5

13: 2.5x4.5

17: 4.5x6 18: 4.5x3 19: 4.5x3

20: 2.5x4.5

21: 3.9x4.5

22: 3.9x4.5

23: 3.9x4.5

24: 4.5x4.5

25: 2.5x4.5

26: 2.7x4.5

27: 3.9x4.5

28: 2.7x4.5

29: 2.7x4.5

30: 3.9x4.5

2: 4.5x3.2

1: 3.9x4.5 = ID: (N-S)x(W-E)

4.5x3.24.5x2

11x1.6

22x1.6

2x60

11x1.6


Room

Acces point

Wireless sensorNorth

Elevator WC

Server

Kitchen

Control Café

Meeting room 1

Meeting room 2

WC1: 4.5x3.2

5: 3.9x4.5

3: 3.9x4.5

4: 3.9x4.5

6: 3.9x4.5

7: 4.5x4.5 8: 4.5x4 9: 4.5x6 10: 4.5x6

11: 3.9x4.5

12: 3.9x4.5

39: 8x6 38: 8x6 37: 6.8x7 36: 6.8x3.8 35: 6.8x5.2 34: 6.8x5 33: 6.8x5 32: 6.8x5 31: 6.8x4

16: 4.5x5.5

15: 2.5x4.5

14: 2.5x4.5

13: 2.5x4.5

17: 4.5x6 18: 4.5x3 19: 4.5x3

20: 2.5x4.5

21: 3.9x4.5

22: 3.9x4.5

23: 3.9x4.5

24: 4.5x4.5

25: 2.5x4.5

26: 2.7x4.5

27: 3.9x4.5

28: 2.7x4.5

29: 2.7x4.5

30: 3.9x4.5

2: 4.5x3.2

1: 3.9x4.5 = ID: (N-S)x(W-E)

4.5x3.24.5x2

11x1.6

22x1.6

2x60

11x1.6



On the physical model

TzdTz /dt

Tz [C]1roo _a*c_a

-K -

UA_W

-K -

UA _S

-K -

UA _R

-K -

UA _N

-K -

UA _E

-K -

Tw - Tz

Tsa - Tz

Ts - Tz

To - Tz

Tn - Tz

Te - Tz

Product

Integrator

1s

Inflow air temp

-C-

Inflow

-C-

From 1

t_out

Add

1/delta

-K -

Tw [C]4

Te [C]3

Ts [C]2

Tn [C]1


SimulationSimulation


One RoomOne Room

20 40 60 80 100 120 14020

22

24Temperature loop 18

20 40 60 80 100 120 140-1000

0

1000

Temperature Heating

Problems?


Dropped PacketsDropped Packets

1 2

34 5

6

7 8 9 10

1112 13

141516 17 18 19

2021

22

2324

252627282930

313233343536373839

0 11.3 22.5 33.8 45 56.3 67.5 78.8 90


Stability?Stability?

• Network drops packetsNo information => no control?

• Jitter margin, δmaxHow much packet drops can the control loop tolerate

Stability theorem

• Robusness to Transmission delay jitter

Packet drops

Dotted: δmax= 1 packetSolid: δmax = 2 consecutive packets

20 40 60 80 100 120 14020

21

22

23


20 40 60 80 100 120 140-1000

0

1000

Heating

20 40 60 80 100 120 140-1000

-500

0

500

1000

Temperature Heating


Room Far AwayRoom Far Away

20 40 60 80 100 120 14018

20

22


20 40 60 80 100 120 140-1000

0

1000

2000

Temperature Heating

• Almost unstable with δmax = 2

• Need better network Quality of Service• Solution?


Add Another Access PointAdd Another Access Point

• Wired Ethernet between access points

Room

Access point

Wireless sensor

North

Elevator WC

Server

Kitchen

Control Café

Meeting room 1

Meeting room 2

WC1: 4.5x3.2

5: 3.9x4.5

3: 3.9x4.5

4: 3.9x4.5

6: 3.9x4.5

7: 4.5x4.58: 4.5x4 9: 4.5x6

10: 4.5x6

11: 3.9x4.5

12: 3.9x4.5

39: 8x6 38: 8x6 37: 6.8x7 36: 6.8x3.8 35: 6.8x5.2 34: 6.8x5 33: 6.8x5 32: 6.8x5 31: 6.8x4

16: 4.5x5.5

15: 2.5x4.5

14: 2.5x4.5

13: 2.5x4.5

17: 4.5x6 18: 4.5x3 19: 4.5x3

20: 2.5x4.5

21: 3.9x4.5

22: 3.9x4.5

23: 3.9x4.5

24: 4.5x4.5

25: 2.5x4.5

26: 2.7x4.5

27: 3.9x4.5

28: 2.7x4.5

29: 2.7x4.5

30: 3.9x4.52: 4.5x3.2

1: 3.9x4.5 = ID: (N-S)x(W-E)

4.5x3.2

4.5x2

11x1.6

22x1.6

2x60

11x1.6


Ethernet


Far Away RoomFar Away Room

20 40 60 80 100 120 14018

20

22


20 40 60 80 100 120 140-1000

0

1000

2000

Temperature Heating

One access point Two access points

20 40 60 80 100 120 140

20

21

22

Temperature loop 24

20 40 60 80 100 120 140-1000

0

1000

Temperature Heating


Packet drop with two access pointsPacket drop with two access points

1 2

34 5

6

7 8 9 10

1112 13

141516 17 18 19

2021

22

2324

252627282930

313233343536373839

0 11.3 22.5 33.8 45 56.3 67.5 78.8 90


Control Cost, PerformanceControl Cost, Performance

No network One access point Two access points

1 234 5

67 8 9 10

1112 13

141516 17 18 19

2021222324

252627282930

313233343536373839

0 0.0187 0.0375 0.0562 0.075 0.0938 0.112 0.131 0.15

1 234 5

67 8 9 10

1112 13

141516 17 18 19

2021222324

252627282930

313233343536373839

0 0.0187 0.0375 0.0562 0.075 0.0938 0.112 0.131 0.15

1 234 5

67 8 9 10

1112 13

141516 17 18 19

2021222324

252627282930

313233343536373839

0 0.0187 0.0375 0.0562 0.075 0.0938 0.112 0.131 0.15


Conclusions of the BA-case study

• Wireless communication affects controlNeed enough network QoS

• One access point is not enoughNetwork re-design: Add access point

Also other network considerations, later...

• Control stabilityController tuning revised

• Only by simulating both communication and controlAnalyze how system actually works

Reveals problems not otherwise obvious


Target tracking

• A moving robot, whose distance to static nodes is measured

• At least three distance measurements are needed to obtain a position estimate

• Remote control along a predefined route

• AODV (single path) and LMNR (multipath) routing protocols and their effect on the control performance compared


Recorded simulation of target tracking


Results

• Multipath routing establishes the route faster

Shorter delay

Positive impact on control

• Long delays make the position control hard

Error increases

Oscillations and overshoot

• LMNR results in roughly 10 % better position estimation accuracy over AODV 200 300 400 500 600 700 800 900 1000 1100

200

300

400

500

600

700

800

900

1000

Reference trajectorySinglepath routingMultipath routingNo contact


Simulation scenario

• Squad of mobile wireless robots moving in different formations

• Controlled by leader• Assume location based on

e.g.GPSodometer orinertia measurements

• Routing <-> Control performance

Can not be determined beforehand!


Networked robotics - demo

• Circle: desired position

• Ball: robot position

• Red: no connection

• Green: leader

Video


PiccSIM – Researcher’s Interface

• PiccSIM webpage: http://www.control.hut.fi/dev/MoCoNet/PiccSIM.html

• Upload of Simulink model and ns-2 tcl scripts

• Run simulation remotely


Conclusions

• The problems of wireless automation from the control design point-of-view are related to

Asynchronism

Varying time-delays

Packet loss

• The choice of communication methods, network topology and protocols (e.g. routing) greatly affect the QoS experienced by the control system

• Hard to know beforehand how a protocol will affect the control results

• Co-design and co-simulation are required!


ConclusionsConclusions

• Simulator suitable for co-simulation of wireless automationTrueTime

Modelica/ns-2

• PiccSIM provides a relatively easy-to-use tool for researchSimulink + ns-2

Graphical user interfaces: network configuration, radio environment modeling tools

Tools for control design and tuning

simulation tools for wireless automation - aaltogeta.aalto.fi/en/courses/lect11_geta_2009.pdf ·...

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