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Cyber Physical Systems: The Need for New Models and Design Paradigms
Bruce H. Krogh Carnegie Mellon University
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Cyber-Physical systems
Cyber-Physical Systems (CPS) are integrations of computation and physical processes.1 What’s new? size and power of computational elements pervasive networking sensing technology actuation technology What’s old? modeling and design paradigms 1 Computing Foundations and Practice for Cyber-Physical Systems: A Preliminary Report Technical Report No. UCB/EECS , May 21, 2007 Edward Lee, University of California at Berkeley
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More on Cyber-Physical Systems2
Some defining characteristics: Cyber capability in every physical component Networked at multiple and extreme scales Complex at multiple temporal and spatial scales Dynamically reorganizing/reconfiguring High degrees of automation, control loops must close at all scales Operation must be dependable, certified in some cases Goals of a CPS research program A new science for future engineered and monitored systems (10-20 year perspective) Physical and cyber design that is deeply integrated What cyber-physical systems are not: Not desktop computing Not traditional, post-hoc embedded/real-time systems Not today’s sensor nets 2 CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Example: Health Care and Medicine
National Health Information Network, Electronic Patient Record initiative Medical records at any point of service Hospital, OR, ICU, …, EMT? Home care: monitoring and control Pulse oximeters (oxygen saturation), blood glucose monitors, infusion pumps (insulin), accelerometers (falling, immobility), wearable networks (gait analysis), … Operating Room of the Future (Goldman) Closed loop monitoring and control; multiple treatment stations, plug and play devices; robotic microsurgery (remotely guided?) System coordination challenge Progress in bioinformatics: gene, protein expression; systems biology; disease dynamics, control mechanisms CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University Images thanks to Dr. Julian Goldman, Dr. Fred Pearce
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Example: Electric Power Grid
Current picture: Equipment protection devices trip locally, reactively Cascading failure: August (US/Canada) and October (Europe), 2003 Better future? Real-time cooperative control of protection devices Or -- self-healing -- (re-)aggregate islands of stable bulk power (protection, market motives) Ubiquitous green technologies Issue: standard operational control concerns exhibit wide-area characteristics (bulk power stability and quality, flow control, fault isolation) Technology vectors: FACTS, PMUs Context: market (timing?) behavior, power routing transactions, regulation IT Layer CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University Images thanks to William H. Sanders, Bruce Krogh, and Marija Ilic
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Pervasive Underlying Problems, Not Solved by Current Technologies
How to build predictable real-time, networked systems at all scales with integrated models of the physical world? How to formulate and manage high-confidence, dynamically- configured CPS? How to organize inter-operable “aggregated” systems? How to cooperatively detect and manage interference among systems in real time, avoid cascading failure? How to formulate an evidential (synthetic and analytic) basis for trusting systems? CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Impending Technical Challenges
Shift FROM compartmentalized designs of physical systems, control subsystems and software architecture lack of knowledge on the cyber side of engineering principles and physical laws (and vice-versa) cyclic executives + human- and information-centric operation centralized separation in time and space TO integrated and optimized design CPS-awareness and expertise to highly-automated, autonomous, coordinated frameworks to federated, decentralized, open and configurable multi-scale systems, mixed synchronous/reactive systems Still real-time (perhaps wide-area, time-critical), still safety- and security-critical, require certification CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Recent Workshops on Cyber-Physical Systems
“High Confidence Medical Device Software and Systems (HCMDSS)”, June 2 - 3, 2005, Philadelphia, PA “Aviation Software Systems: Design for Certifiably Dependable Systems”, October 5-6, 2006, Alexandria NSF Workshop on “Cyber-Physical Systems”, October 16-17, 2006, Austin, “Beyond SCADA: Networked Embedded Control for Cyber Physical Systems (NEC4CPS)”, November 8 & 9, 2006, Pittsburgh “High-Confidence Software Platforms for Cyber-Physical Systems (HCSP-CPS), November 30 – December 1, 2006, Alexandria CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Industry Round-Table on CPS NSF, May 17, 2007
Health-Care Doug Busch, VP and CTO of Digital Health Group, Intel David R. Jones, Director Quality Assurance, Regulatory Affairs and Philips Business Excellence, Philips Consumer Healthcare Solutions Automotive Systems Nady Boules, Director, Electrical and Controls Integration, General Motors Venkatesh Prasad, Director, Ford Building and Process Controls J. Michael McQuade, Senior VP, Science and Technology, United Technologies Steve Schilling, VP, Emerson Process Control Defense and Aviation Systems John Borgese , VP of Advanced Technology Center, Rockwell Collins Gary Hafen, Director of Software Engineering, Lockheed Martin Corporate Headquarters Peter Tufano, VP of Engineering for Network Enabled Systems, BAE Don Winter, VP of Engineering and Information Technology, Boeing PhantomWorks Critical Infrastructure Guido Bartels, Director, IBM Global Energy and Utility Solutions Henry Kluepfel, Vice-President, SAIC Venture Capital David Tennenhouse, General Partner, New Venture Partners CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Design of Embedded Control Systems
Traditional approach: Separation of Concerns Control-theoretic design of continuous dynamic feedback loops ignore implementation details: mode switching, fault detection, real- time constraints, implementation platform, etc. Event-based design to supervise real-time control loops ignore continuous dynamics: stability, transient response, parametric variations, etc.
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Design of Embedded Control Systems
Traditional approach: Separation of Concerns Control-theoretic design of continuous dynamic feedback loops ignore implementation details: mode switching, fault detection, real- time constraints, implementation platform, etc. Event-based design to supervise real-time control loops ignore continuous dynamics: stability, transient response, parametric variations, etc. This works in most cases, BUT ...
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Demands from Emerging Applications
New challenges increasingly complex applications safety critical systems autonomy multi-agent increasingly complex solutions heterogeneous, distributed platforms sophisticated numerical control algorithms Implications engineering insight is inadequate testing-based V&V is insufficient move toward model-based design
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Tools for Design & Implementation of Embedded Control Systems
Control Implementation: Discrete State/Events Lyapunov functions, eigenspace analysis, etc. Analytical Tools MATLAB, MatrixX, VisSim, etc., Software Tools Control Design: Continuous State differential equations, transfer functions, etc. Models automata, Petri nets, statecharts, etc. Boolean algebra, formal logics, recursion, etc. SCADE, Statemate, SMV, SAT, etc.
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Limitations of Conventional Control System Design (CCSD)
Inputs/outputs are not intrinsic From following commands to implementing intent Human-system interaction Deeply embedded CPS
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Inputs/outputs are not intrinsic
CCSD assumes an I/O structure. In CPS, the identity of input/output signals is context dependent (at best). steer-by-wire temperature door closer (J. C. Willems)
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Inputs/outputs are not intrinsic
CCSD assumes an I/O structure. In CPS, the identity of input/output signals is context dependent (at best). steer-by-wire Model context-dependence as hybrid systems w/ mode switching temperature door closer (J. C. Willems)
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Inputs/outputs are not intrinsic
CCSD assumes an I/O structure. In CPS, the identity of input/output signals is context dependent (at best). steer-by-wire Physical modeling “languages”: bond graphs Omola/Dymola SimMechanics temperature door closer (J. C. Willems)
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From following commands to realizing intent
CCSD assumes command-following performance measures. CPS will realize the intent of the user. ABS Automated External Defibrillator power grid?
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From following commands to realizing intent
CCSD assumes command-following performance measures. CPS will realize the intent of the user. ABS Integration of logic/rules/events with continuous/timed feedback control (hybrid systems) Automated External Defibrillator power grid?
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From following commands to realizing intent
CCSD assumes command-following performance measures. CPS will realize the intent of the user. ABS Automate system operation under stressed conditions. Automated External Defibrillator power grid?
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Human-system interaction
CCSD assumes only information feedback. CPS will include physical feedback. building control? aircraft ABS Boeing 777 Airbus 380
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Human-system interaction
CCSD assumes only information feedback. CPS will include physical feedback. Haptic systems design building control? aircraft ABS Boeing 777 Airbus 380
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Human-system interaction
CCSD assumes only information feedback. CPS will include physical feedback. building control? aircraft ABS Integrate human behavior into the control loop (e.g., make it uncomfortable so they will open the windows) Boeing 777 Airbus 380
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Deeply embedded CPS In CCSD embedded components close local “inner” feedback loops. CPS will enhance and leverage nature physical feedback at all levels.
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E.g., medical implants that work with the natural healing processes
Deeply embedded CPS In CCSD embedded components close local “inner” feedback loops. CPS will enhance and leverage nature physical feedback at all levels. E.g., medical implants that work with the natural healing processes
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Physical is central to CPS:
We need new cross-cutting paradigms new architectures CPS will lead to more rapid transition of science/technology to critical applications
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Possible Grand Challenges3
Zero automotive traffic fatalities, injuries minimized, and significantly reduced traffic congestion and delays Blackout-free electricity generation and distribution Reduce testing and integration time and costs of complex CPS systems (e.g. avionics) by one to two orders of magnitude Perpetual life assistants for busy, older or disabled people Extreme-yield agriculture Energy-aware buildings Location-independent access to world-class medicine Physical critical infrastructure that calls for preventive maintenance Self-correcting and self-certifying cyber-physical systems for “one-off” applications 3 Industry Roundtable on Cyber-Physical Systems NSF, May 17, 2007 Raj Rajkumar, Carnegie Mellon University
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Cyber Physical Systems or Cyber for Physical Systems
How should the requirements for control (and other) physical applications influence “cyber” research? Will the standard separation of concerns approach (applications vs. computing infrastructure) continue to work well?
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Issues in Education computer science domain experts (engineers)
focuses on discrete mathematics little emphasis on numerical methods limits the understanding of physical systems domain experts (engineers) focuses on mathematics for analysis and design little exposure to embed and real-time computing limits the understanding of real-time implementation We need to re-think how we educate domain experts and computer scientists if we are going to realize sustainable CPS.
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Core CPS Programmatic Themes
Scientific foundations for building verifiably correct and safe cyber-physical systems Scalable infrastructure and components with which cyber-physical systems can be deployed Tools and Experimental Testbed Education that encompasses both the cyber and the physical domains CPS Briefing NSF, May 10, 2007 Raj Rajkumar, Carnegie Mellon University
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Long-Term CPS Goal Transform how we interact with the physical world just like the internet transformed how we interact with one another. Convergence of embedded systems, control theory, hybrid systems, microcontrollers, sensors, actuators, wireless networks, wide area networks, distributed systems, operating systems, advances in structures, … Seek scientific foundations and technologies to integrate cyber-concepts with the dynamics of physical and engineered systems. Industry Roundtable on Cyber-Physical Systems NSF, May 17, 2007 Raj Rajkumar, Carnegie Mellon University
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