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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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2 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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3 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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4 Model Requirements Platform Verification Implementation
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5 Model Requirements Platform Verification Implementation automatic (model checking) automatic (compilation)
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6 Model Requirements Platform Verification Implementation property preserving
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7 Component Requirements Platform Verification Implementation Component
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8 Requirements Platform Verification Implementation Composition Component no change
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9 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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10 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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11 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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12 time ttime 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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13 output as soon as ready Contrast the FLET to Standard Practice
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14 -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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15 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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16 UC Berkeley (Horowitz, Liebman, Ma, Koo, Sangiovanni-Vincentelli, Sastry). A Giotto-Based Flight Control System
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17 200 Hz 400 Hz 200 Hz 1 kHz A Giotto-Based Flight Control System
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18 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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19 Mode 1 Mode 4Mode 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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20 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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21 The Giotto Tool Chain Simulink Model Giotto Program for task timing and interaction C Functions for tasks E CodePlatform Code Platform (minimal OS + hardware) E Machine invokes 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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22 Demo Tomorrow: The Giotto Development Kit The Giotto Development Kit 1.Giotto Compiler 2.Integrated Editor 3.E-code Viewer 4.E-code Simulator 5.Current work: -E-code analysis for time safety -E-code optimization UC Berkeley (Kirsch, Sanvido).
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23 Demo Tomorrow: Giotto-Based Embedded Control Examples An elevator controller: A controller for the Caltech vehicles:
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Embedded Java Generation from Ptolemy Models Steve Neuendorffer Edward Lee Case Study: Caltech Vehicles
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25 Caltech Vehicles Wireless 802.11b Network Datagram with vehicle locations Controller RS-232 commands to fans
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26 A Hierarchical Heterogenous Model Measured physical parameters Discrete-event model convenient for events that do not occur at the same time
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27 A Hierarchical Heterogenous Model Data formatting Fan thrust map Continuous-time model good for physical hardware dynamics
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28 A Hierarchical Heterogenous Model Synchronous dataflow model convenient for signal processing and discrete-time aspects
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29 Stepwise Refinement of Simulation towards Implementation 802.11b RS-232
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30 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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31 Code Generation 802.11b RS-232 Replace controller simulation with embedded controller. Embedded Java Platform
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32 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
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