Integrated Design and Analysis Tools for Software-Based Control Systems

Shankar Sastry (PI)

Tom Henzinger

Edward Lee

University of California, Berkeley

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1. Model building and checking for hybrid systems

2. Embedded code generation from hybrid models

3. Multi-modal, hierarchical, and multi-vehicle control

4. Probabilistic hybrid systems and fault tolerance

5. Experimental rotorcraft platforms

Research Thrusts

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1. From Hybrid Systems Models to Embedded Code

1a. Simulink to Giotto to E code

1b. Ptolemy to Embedded Java

2. Multi-vehicle Cooperative Control

Focus of Presentation/Demos

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Model

Requirements

Platform

Verification

Implementation

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Model

Requirements

Platform

Verification

Implementation

automatic (model checking)

automatic (compilation)

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Model

Requirements

Platform

Verification

Implementation property preserving

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Component

Requirements

Platform

Verification

Implementation

Component

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Component

Requirements

Platform

Verification

Implementation

Composition

Component

no change

no change

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A new paradigm to achieve Verifiability and Compositionality: The FLET (Fixed Logical Execution Time) Assumption

Software Task

read sensor input at time t

write actuator output at time t+d, for fixed d

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Software Task

read sensor input at time t

write actuator output at time t+d, for fixed d

d>0 is the task's "logical execution time"

A new paradigm to achieve Verifiability and Compositionality: The FLET (Fixed Logical Execution Time) Assumption

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High-Confidence, Compositional Embedded Programming

The control engineer specifies sampling rate d and permissible jitter j to solve the control problem at hand.

The compiler ensures that d and j are met on a given platform (hardware resources and performance). If the compiler succeeds, then the code is time safe; otherwise the program is rejected.

No "priority tweaking"!

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time t time t+d

possible physical execution on CPU

buffer output

A new paradigm to achieve Verifiability and Compositionality: The FLET (Fixed Logical Execution Time) Assumption

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output as soon as ready

Contrast the FLET to Standard Practice

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-predictable timing and data behavior (no race conditions, minimal jitter)

-portable, composable code (as long as the platform offers sufficient performance)

Advantages of the FLET

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The E(mbedded) Machine:

a virtual machine that executes tasks in real time under the FLET assumption. E (machine) code can be checked for time safetry.

Giotto:

a structured, high-level language for control applications which is compiled into E code.

Implementations of the FLET

UC Berkeley (Henzinger, Horowitz, Kirsch, Majumdar, Matic, Sanvido).

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UC Berkeley (Horowitz, Liebman, Ma, Koo, Sangiovanni-Vincentelli, Sastry).

A Giotto-Based Flight Control System

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200 Hz400 Hz

200 Hz 1 kHz

A Giotto-Based Flight Control System

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1. Concurrent periodic tasks:

-sensing -control law computation -actuating

2. Multiple modes of operation:

-navigational modes (autopilot, manual, etc.) -maneuver modes (taxi, takeoff, cruise, etc.) -degraded modes (sensor, actuator, CPU failures)

A Giotto-Based Flight Control System

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Mode 1

Mode 4

Mode 3

Mode 2

Task S 400 Hz

Task C 200 Hz

Task A 1 kHz

Task S 400 Hz

Task C 200 Hz

Task A’ 1 kHz

Task C’ 100 Hz

Task A 1 kHz

Task S 400 Hz

Task C 200 Hz

Task A 2 kHz

Task A” 1 kHz

Condition 1.2

Condition 2.1

A Giotto-Based Flight Control System

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Host code e.g. C

Glue code Giotto

Functionality. -Reactivity.

-Concurrency.

Timing and interaction.-No time.

-Sequential.

A Giotto-Based Flight Control System

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The Giotto Tool Chain

Simulink Model

Giotto Program for task timing and interaction

C Functions for tasks

E Code Platform Code

Platform (minimal OS + hardware)

E Machineinvokes

S/G Translator

Giotto Compiler

RTW Embedded Coder

C Compiler

S/G Simulator

performance information

guaranteed conformance

(UC Berkeley, U Salzburg)

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Demo Tomorrow: The Giotto Development Kit

The Giotto Development Kit

1. Giotto Compiler2. Integrated Editor3. E-code Viewer4. E-code Simulator5. Current work:

-E-code analysis for time safety

-E-code optimization

UC Berkeley (Kirsch, Sanvido).

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Demo Tomorrow: Giotto-Based Embedded Control Examples

An elevator controller: A controller for the Caltech vehicles:

Embedded Java Generation from Ptolemy Models

Steve Neuendorffer

Edward Lee

Case Study: Caltech Vehicles

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Caltech Vehicles

Wireless 802.11b Network Datagram with vehicle locations

Controller

RS-232 commands to fans

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A Hierarchical Heterogenous Model

Measured physical parametersDiscrete-event model convenient for events that do not occur at the same time

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A Hierarchical Heterogenous Model

Data formatting

Fan thrust map

Continuous-time model good for physical hardware dynamics

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A Hierarchical Heterogenous Model

Synchronous dataflow model convenient for signal processing and discrete-time aspects

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Stepwise Refinement of Simulation towards Implementation

802.11b

RS-232

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Hardware-in-the-Loop

802.11b

RS-232

Replace hardware-true simulation model with actual vehicle.

Allows validation of hardware model aspects.

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Code Generation

802.11b

RS-232

Replace controller simulation with embedded controller.

Embedded Java Platform

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Directions

Giotto code generation from Ptolemy Verify Giotto programs against hybrid automaton

models Implement Softwalls algorithm on Caltech vehicles

Dynamics similar to 2D aircraft dynamics, but safe for experimentation