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Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems - Project Overview -. Janos Sztipanovits ISIS-Vanderbilt University. MURI Year 3 Review Meeting Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems

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slide1

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems - Project Overview -

Janos Sztipanovits

ISIS-Vanderbilt University

MURI Year 3 Review Meeting

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems

UC Berkeley, Berkeley, CA

December 2, 2009

slide2
Team
  • Vanderbilt
    • Sztipanovits (PI), Karsai, Kottenstette, NeemaPorter, Hemingway, Nile
  • UC Berkeley
    • Tomlin (PI), Lee, Sastry, Ding, Gillula, Gonzales, Huang, Leung, Lickly, Mahdl, Latronico, Shelton, Tripakis, Vitus
  • CMU
    • Krogh (PI), Clarke, PlatzerJain, Lerda, Bhave, Maka
  • Stanford
    • Boyd (PI)Wang
slide3

Objectives

  • Development of a theory of deep composition of hybrid control systems with attributes of computational and communication platforms
  • Development of foundations for model-based software design for high-confidence, networked embedded systems applications.
  • Composable tool architecture that enables tool reusability in domain-specific tool chains
  • Experimental research

Long-Term PAYOFF:

Decrease the V&V cost of distributed embedded control systems

slide4

Agenda

9:00 – 9:05 am Introductions

9:05 - 9:15 am Project Overview Janos Sztipanovits

9:15 – 10:00 am Overview of Hybrid Control Design Challenges and Solutions Claire Tomlin and Shankar Sastry

10:00 – 10:45am Model-Integrated Tool Chain for High Confidence Design

Gabor Karsai, Joe Porter, Graham Hemingway and Janos Sztipanovits

10:45 - 11:00am Break

11:00 – 11:45 am Correctly Composing Components: Ontologies and Modal Behaviors

Edward Lee

11:45 – 12:45pm Model-based Testing and Verification Edmund Clarke, Bruce Krogh, Andre Platzer

12:45 – 1:45pm Lunch

1:45 – 2:15 pm Performance Bounds and Suboptimal Policies for Linear Stochastic Control Yang Wang and Stephen Boyd

2:15 – 2:45 pm Constructive Non-linear Control Design With Applications to Quad-Rotor and Fixed-Wing Aircraft Nicholas Kottenstette

2:45 – 3:30 pm Starmac Experimental Platform Demo Claire Tomlin and Shankar Sastry

3:30 – 3:45 pm Plans for Year 4&5Janos Sztipanovits

3:45 - 4:00 pm Break

4:00 – 4:30 pm Government Caucus

4:30 – 4:45 pm Feedback to the Research Team

overall undertaking
Overall Undertaking

Plant Models and Requirements

Scope of the Project:

  • Development of component technologies in selected areas
  • Development of model-based design methods
  • Incrementally building and refining a tool chain for an experimental domain (micro UAV control)
  • Demonstration of control software development with the tool chain
  • Experiments

SW Architecture Modeling

Code

Model-Based Design

Controller Modeling

System-Level

Modeling

Deployment

Modeling

Expensive

Intractable

Fragile

X

slide6

Composition Inside Abstraction Layers

  • Dynamics:
  • Properties: stability, safety, performance
  • Abstractions: continuous time, functions, signals, flows,…

Plant Dynamics

Models

Controller Models

Physical design

Assumption: Effects of digital implementation can be neglected

  • Software :
  • Properties: deadlock, invariants, security,…
  • Abstractions: logical-time, concurrency, atomicity, ideal communication,..

Software

Architecture

Models

Software Component Code

Software design

Assumption: Effects of platform properties can be neglected

System

Architecture Models

Resource

Management

Models

  • Systems :
  • Properties: timing, power, security, fault tolerance
  • Abstractions: discrete-time, delays, resources, scheduling,

System/Platform Design

slide7

Composition Inside Abstraction Layers

Controller dynamics is developed

without considering implementation

uncertainties (e.g. word length, clock accuracy ) optimizing performance.

Plant Dynamics

Models

Controller Models

Physical design

X

Assumption: Effects of digital implementation can be neglected

Software architecture models are developed without explicitly considering

systems platform characteristics, even

though key behavioral properties

depend on it.

Software

Architecture

Models

Software Component Code

Software design

X

Assumption: Effects of platform properties can be neglected

Platform architectruedefines platform configuration, resource management, networking,. Uncertainties introduce time variant delays that may require re-verification of key properties on all levels.

System

Architecture Models

Resource

Management

Models

System/Platform Design

improve robustness of controllers against implementation uncertainties
Improve Robustness of Controllers Against Implementation Uncertainties

Plant Models and Requirements

  • How should we increase robustness in controller design?
    • Robust hybrid and embedded systems design (Tomlin, Sastry)
    • Performance bounds for constrained linear stochastic control (Boyd, Wang)
    • Constructive nonlinear control design (Kottenstette, Porter)

SW Architecture Modeling

Code

Controller Design

Model-Based Design

Funcion (Controller) Modeling

System-Level

Modeling

Deployment

Modeling

verification and testing
Verification and Testing

Plant Models and Requirements

  • How can we exploit heterogeneous abstractions in verification and test generation?
    • Model-based testing and verification of embedded systems implementations (Clarke, Platzer)
    • Statistical Probabilistic Model Checking (Zuliani, Clarke)

SW Architecture Modeling

Code

V&V

Model-Based Design

Funcion (Controller) Modeling

System-Level

Modeling

Deployment

Modeling

model based code generation 2008
Model-based code generation (2008)

Plant Models and Requirements

SW Architecture Modeling

Code

From Models

To Code

Model-Based Design

Funcion (Controller) Modeling

System-Level

Modeling

Deployment

Modeling

  • How to design high-confidence software and systems?
    • Model-based code generation with partial evaluation (Zhou, Leung, Lee)
    • Model-based code generation with graph transformation (Karsai)
    • (Last year results, they are built in the tools.)
progress towards integrated model based design flow
Progress towards integrated model-based design flow

AIRES

Meta-Model

ESML

 AIF

CFGMeta-Model

ECSL-DP

Meta-Model

ESML-

 CFG

PRISM

ESML

PRISM

Meta-Model

Model-Based Design

Plant Models and Requirements

  • How can we integrate model-based design flows?
    • Correctly composing components (Lee)
    • Model-integrated tool chain for high confidence design (Karsai, Porter, Hemingway, DeBusk and Sztipanovits)
    • StarMac Experimental platform (Tomlin, Sastry)

SW Architecture Modeling

Code

Model-Based Design

Funcion (Controller) Modeling

System-Level

Modeling

Deployment

Modeling

starmac experimental platform quadrotor aircraft developed by co pi claire tomlin
Starmac Experimental PlatformQuadrotor aircraft developed by co-PI Claire Tomlin

Requires integration of legacy and custom components.

experimental set up
Experimental Set Up
  • A mobile sensor network:
    • A set of vehicles, each with a set of sensors for its own navigation and control, as well as for sensing its environment (such as target range or bearing)
    • Computation is distributed, and limited to the processors on board the vehicles (no central computer)
    • Communication between subsets of vehicles (limited by range or geography) available
    • Collision avoidance needed between vehicles
    • Humans share control with automation
  • Focus on algorithms for autonomous search:
    • Unexploded ordinance detection
    • Beacon tracking scenarios
    • RFID tracking
    • Survey of disaster areas
    • Search and rescue
    • Biological studies, animal monitoring
accomplishment highlights 1 2
Accomplishment Highlights 1/2
  • New results in hybrid control system design using reachable set analysis. Methodology for computing reachable sets using quantized inputs over discrete time steps has been developed and implemented for an aircraft collision avoidance example. (Tomlin, Sastry)
  • Use of reachable set analysis in complex control law design. (Tomlin)
  • We have extended our approach for integrated software model checking in the loop to the case of nonlinear dynamic plant models using the concept of bisimulation functions for nonlinear systems (Krogh) (not presented at the review)
  • New algorithm for the formal verification of curved flight collision avoidance (Clarke, Platzer)
  • New algorithm and method for statistical probabilistic model checking and its application to Simulink/Stateflow models (Clarke, Zuliani)
  • Extension of passivity based approach for controller design to fixed-wing aircrafts. (Kottenstette)
accomplishment highlights 2 2
Accomplishment Highlights 2/2
  • New results in introducing ontology information using Hindley-Milner type theories in modeling environments (Lee)
  • New results in handling time in hierarchical modal models (Lee)
  • Integrated tool chain for model-based generation of embedded flight controller on distributed computing platform. Guaranteed stability against implementation induced timing uncertainties and verified schedulability on time-triggered platform.
  • Demonstration of roundtrip engineering between physical and implementation layers: physical models are used for code generation and implementation models are used for updating physical models.
  • Demonstration of practical use of reachable set analysis in acrobatic maneuver design and multi-vehicle collision avoidance for the STARMAC quadrotor helicopter testbed.
collaboration
Collaboration
  • The team members work together extensively in many areas in this project and outside of the project
  • Many examples for joint work among research teams
  • Forms of collaborations:
    • Bi-weekly/monthly telecons
    • Researcher and graduate student visits
    • Free flow of ideas, methods and tools
transitioning
Transitioning
  • The Ptolemy II source tree now is available via CVS. The team actively works on transitioning research results to the following companies :
    • Lockheed Martin
    • National Instrument
  • Vanderbilt’s MIC tool suite (GME, GReAT, UDM, OTIF) had a major release in 2009. GME supports now large scale model management and concurrent modeling. The releases are available through the ISIS download site.
    • Vanderbilt continued working with GM, Raytheon, LM and BAE Systems research groups on transitioning model-based design technologies into programs.
    • Vanderbilt continued working with Boeing’s FCS program on applying the MIC tools for precise architecture modeling and systems integration.
    • Active collaboration with TTTech, University of Vienna.
    • Collaboration started with VERIMAG.on integrating BIP in the tool chain.
  • UC Berkeley’s reachable set tools are transitioned to the following institutions:
    • Microsoft Research
    • NASA Ames
plans for years 4 5
Plans for Years 4&5
  • Networked Control System Design
    • Distributed control/multi agent systems
    • Dynamic state estimation and mode switching
    • Robustness against network effects
    • More realistic channel models
    • Managing effects from network layer
  • Verification and Testing
    • Generation of formal representations from models
    • Order reduction using hybrid bisimulation
    • Compositional specification of heterogeneous components
  • Tools
    • Integrated, heterogeneous tool chains
    • Complete path from virtual prototyping to physical implementation
    • Additional design aspects: fault management, bridge to security
  • Experiments
    • Extension of scope and complexity
slide19

Frameworks and Tools for High-Confidence Design of Adaptive, Distributed Embedded Control Systems

  • Long-Term PAYOFF: Decrease the V&V cost of distributed embedded control systems
  • OBJECTIVES
  • Development of a theory of deep composition of hybrid control systems with attributes of computational and communication platforms
  • Development of foundations for model-based software design for high-confidence, networked embedded systems applications.
  • Composable tool architecture that enables tol reusability in domain-specific tool chains
  • Experimental research

Control Design

Implementation

Design

Modeling Languages

Models

Model

Transformation

Model Translators

Model-based Code Generators

if (inactiveInterval != -1) {

int thisInterval =

(int)(System.currentTimeMillis() - lastAccessed) / 1000;

if (thisInterval > inactiveInterval) {

invalidate();

ServerSessionManager ssm =

ServerSessionManager.getManager();

ssm.removeSession(this);

}

}

}

private long lastAccessedTime = creationTime;

/**

* Return the last time the client sent a

Analysis tools

Platforms

  • APPROACH/TECHNICAL CHALLENGES
  • Guaranteed behavior of distributed control software using the following approaches: (1) extension of robust controller design to selected implementation error categories (2) providing “certificate of correctness” for the controller implementation (3) development of semantic foundation for tool chain composition (4) introducing safe computation models that provide behavior guarantees
  • ACCOMPLISHMENTS/RESULTS
  • See Presentations
  • FUNDING ($K)—Show all funding contributing to this project
  • FY06FY07FY08FY09FY10FY11
  • AFOSR Funds 479 986 989 547
  • Option 465 995 529
  • TRANSITIONS
  • Strong link to industry: Boeing, BAE Systems, Raytheon, GM, MathWorks, National Instruments, TTTech
  • Industry affiliate programs: CHESS, ESCHER, GMLab.
  • STUDENTS, POST-DOCS
  • 9 graduate students (MURI) + student groups from other projects
  • LABORATORY POINT OF CONTACT
  • Dr William M. McEneaney, AFRL/AFOSR
  • Dr Fariba Fahroo, AFRL/AFOSR
  • Dr. David B. Homan , Civ AFRL/RBCC, WPAFB, OH
starmac platform
Starmac Platform

LIDAR

URG-04LX

10 Hz ranges

RS232

115 kbps

PC/104

Pentium M1GB RAM, 1.8GHz

Est. & control

WiFi

802.11g+

≤ 54 Mbps

USB 2

480 Mbps

Stereo Cam

Videre STOC

30 fps 320x240

Firewire

480 Mbps

RS232

GPS

Superstar II

10 Hz

UART

19.2 kbps

Stargate 1.0

Intel PXA25564MB RAM, 400MHz

Supervisor, GPS

WiFi

802.11b

≤ 5 Mbps

CF

100 Mbps

UART115 Kbps

UART

IMU

3DMG-X1

76 or 100 Hz

UART

115 kbps

Start with controller

Robostix

Atmega128

Low level control

Ranger

SRF08

13 Hz Altitude

I2C

400 kbps

PPM100 Hz

Analog

Expand to supervisor

Ranger

Mini-AE

10-50 Hz Altitude

Beacon

Tracker/DTS

1 Hz

ESC & Motors

Phoenix-25, Axi 2208/26

Finally to host

Timing/Analog

platform extensions
Platform Extensions

Gumstix

TTTech

Soekris

Linux w/ 3xEthernet

TT Virtual Machine on standard UDP and Linux

No fault tolerance (yet)

  • MPC 555 micros
  • TTP/C comm
  • TTTech Software tools
  • Fault-tolerance
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