*banner
 

Cyber-Physical Systems, A Fundamental Intellectual Challenge
Edward A. Lee

Citation
Edward A. Lee. "Cyber-Physical Systems, A Fundamental Intellectual Challenge". Talk or presentation, 11, December, 2013; Invited Talk, College de France, Paris, France.

Abstract
The term cyber-physical systems (CPS) refers to the integration of computation and networking with physical processes. CPS is firmly established as a buzzword du jour. Yet many of its elements are familiar and not altogether new. Is CPS just a rehash of old problems designed to attract new funding? In this talk, I will argue that quite to the contrary, CPS is pushing hard at the frontiers of engineering knowledge, putting severe stress on the abstractions and techniques that have proven so effective in the separate spaces of cyber systems (information and computing technology) and physical systems (the rest of engineering). My argument will center on the role of models, and I will show that questions about semantics of models become extremely challenging when the models are required to conjoin the cyber and the physical worlds.

A key challenge is that the notion of dynamics differs in the engineering abstractions used for the cyber and physical sides of the problem. On the physical side, dynamics refers to the change of state of a system over time, where time plays a central role. Many of the core abstractions used in the engineering of such systems explicitly refer to time. For example, ordinary differential equations (ODEs) are frequently used to describe the motion of mechanical parts and the dynamics of electrical circuits. In contrast, on the cyber side, the notions of computation dating back to Turing and Church make no reference to time, modeling dynamics as sequences of discrete state changes. These abstractions are fundamentally algorithmic, step-by-step operations, where the time it takes to perform a step is irrelevant.

The engineering abstractions used in both the cyber and physical spaces are key enablers of the high-tech revolution of the 20th century. On the cyber side, the ability to execute algorithms repeatedly, quickly, and essentially flawlessly underlies much of the information technology revolution. On the physical side, the ability to design stable and robust control systems accounts for the extraordinary reliability and efficiency of vehicles and transportation systems.

A central feature of these abstractions is determinism, where, once the inputs are defined, the behavior of a model of the system is unique and well-defined. Exactly one behavior is correct. Such determinism makes these models very powerful, because analyses of the models acquire the strength of mathematical theorems. Moreover, the models correspond well with the actual behavior of physical realizations. For example, a modern microprocessor can correctly execute a program with extremely high reliability. A mechanical feedback coupling can closely emulate the ODEs used to model it. The combination of expressiveness of the models, the fidelity of the models to the physical realization, and determinism is extremely powerful.

But when cyber and physical abstractions are combined, with today's abstractions, we lose determinism. The interaction between an algorithm and a physical dynamics is not well defined, because the modeling semantics of the algorithms eschews time, whereas the modeling semantics of the ODE embraces time. So instead of building models with deterministic abstractions, engineers today build cyber-physical systems by separately designing the cyber and physical parts, and then discovering the dynamics when they put the two realizations together.

To solve this problem, we can endow the cyber parts with physical abstractions (cyberizing the physical), for example by introducing time in the semantics. Or we can endow the physical parts with cyber abstractions (physicalizing the cyber), for example by enabling database queries over sensor networks. Both approaches have value and are necessary for the full realization of the vision of cyber-physical systems.

Electronic downloads

Citation formats  
  • HTML
    Edward A. Lee. <a
    href="http://chess.eecs.berkeley.edu/pubs/1045.html"
    ><i>Cyber-Physical Systems, A Fundamental
    Intellectual Challenge</i></a>, Talk or
    presentation,  11, December, 2013; <i>Invited
    Talk</i>, College de France, Paris, France.
  • Plain text
    Edward A. Lee. "Cyber-Physical Systems, A Fundamental
    Intellectual Challenge". Talk or presentation,  11,
    December, 2013; <i>Invited Talk</i>, College de
    France, Paris, France.
  • BibTeX
    @presentation{Lee13_CyberPhysicalSystemsFundamentalIntellectualChallenge,
        author = {Edward A. Lee},
        title = {Cyber-Physical Systems, A Fundamental Intellectual
                  Challenge},
        day = {11},
        month = {December},
        year = {2013},
        note = {<i>Invited Talk</i>, College de France, Paris,
                  France.},
        abstract = {The term cyber-physical systems (CPS) refers to
                  the integration of computation and networking with
                  physical processes. CPS is firmly established as a
                  buzzword du jour. Yet many of its elements are
                  familiar and not altogether new. Is CPS just a
                  rehash of old problems designed to attract new
                  funding? In this talk, I will argue that quite to
                  the contrary, CPS is pushing hard at the frontiers
                  of engineering knowledge, putting severe stress on
                  the abstractions and techniques that have proven
                  so effective in the separate spaces of cyber
                  systems (information and computing technology) and
                  physical systems (the rest of engineering). My
                  argument will center on the role of models, and I
                  will show that questions about semantics of models
                  become extremely challenging when the models are
                  required to conjoin the cyber and the physical
                  worlds. <p> A key challenge is that the notion of
                  dynamics differs in the engineering abstractions
                  used for the cyber and physical sides of the
                  problem. On the physical side, dynamics refers to
                  the change of state of a system over time, where
                  time plays a central role. Many of the core
                  abstractions used in the engineering of such
                  systems explicitly refer to time. For example,
                  ordinary differential equations (ODEs) are
                  frequently used to describe the motion of
                  mechanical parts and the dynamics of electrical
                  circuits. In contrast, on the cyber side, the
                  notions of computation dating back to Turing and
                  Church make no reference to time, modeling
                  dynamics as sequences of discrete state changes.
                  These abstractions are fundamentally algorithmic,
                  step-by-step operations, where the time it takes
                  to perform a step is irrelevant. <p> The
                  engineering abstractions used in both the cyber
                  and physical spaces are key enablers of the
                  high-tech revolution of the 20th century. On the
                  cyber side, the ability to execute algorithms
                  repeatedly, quickly, and essentially flawlessly
                  underlies much of the information technology
                  revolution. On the physical side, the ability to
                  design stable and robust control systems accounts
                  for the extraordinary reliability and efficiency
                  of vehicles and transportation systems. <p> A
                  central feature of these abstractions is
                  determinism, where, once the inputs are defined,
                  the behavior of a model of the system is unique
                  and well-defined. Exactly one behavior is correct.
                  Such determinism makes these models very powerful,
                  because analyses of the models acquire the
                  strength of mathematical theorems. Moreover, the
                  models correspond well with the actual behavior of
                  physical realizations. For example, a modern
                  microprocessor can correctly execute a program
                  with extremely high reliability. A mechanical
                  feedback coupling can closely emulate the ODEs
                  used to model it. The combination of
                  expressiveness of the models, the fidelity of the
                  models to the physical realization, and
                  determinism is extremely powerful. <p> But when
                  cyber and physical abstractions are combined, with
                  today's abstractions, we lose determinism. The
                  interaction between an algorithm and a physical
                  dynamics is not well defined, because the modeling
                  semantics of the algorithms eschews time, whereas
                  the modeling semantics of the ODE embraces time.
                  So instead of building models with deterministic
                  abstractions, engineers today build cyber-physical
                  systems by separately designing the cyber and
                  physical parts, and then discovering the dynamics
                  when they put the two realizations together. <p>
                  To solve this problem, we can endow the cyber
                  parts with physical abstractions (cyberizing the
                  physical), for example by introducing time in the
                  semantics. Or we can endow the physical parts with
                  cyber abstractions (physicalizing the cyber), for
                  example by enabling database queries over sensor
                  networks. Both approaches have value and are
                  necessary for the full realization of the vision
                  of cyber-physical systems. },
        URL = {http://chess.eecs.berkeley.edu/pubs/1045.html}
    }
    

Posted by Mary Stewart on 2 Jan 2014.
For additional information, see the Publications FAQ or contact webmaster at chess eecs berkeley edu.

Notice: This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright.

You are not logged in 
©2002-2017 Chess