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2 CPS Principles, Foundations, System Characteristics, and Complementary Skills
Pages 24-33

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From page 24...
... Drawing on these principles, this chapter identified six foundations for a CPS curriculum: basic computing concepts, computing for the physical world, discrete and continuous mathematics, cross-cutting applications, modeling, and CPS system development. The chapter turns next to a discussion of system characteristics such as scale, complexity, and safety criticality.
From page 25...
... The required principles of signal processing include linear signals and systems theory, analog and digital filtering, time and frequency domain analysis, convolution, linear transforms like the discrete Fourier transform and fast Fourier transform, noise and statistical characterization of signals, machine learning, and decision and sensor fusion. In CPS, considerations of the implementations of these signal processing techniques on embedded CPUs, running in real time and with safety critical implications, are necessary, as is the topic of sensor reliability.
From page 26...
... The distributed and networked nature of CPS in many of the applications of interest should be included in CPS education. Even though distributed systems and networking are covered in traditional engineering or computer science curricula, these courses often do not address CPS issues.
From page 27...
... cannot be achieved with only one or two programming classes; it can only be attained with solid training in computing. The basic computing concepts listed below should be taught using examples and case studies from the physical domain.
From page 28...
... Knowledge of control, signal processing, and embedded software design and implementation are at the core of this foundational principle. Concepts will include the following: • Control principles including linear and nonlinear systems, stochastic sys tems, adaptive control, system identification, hybrid control; • Optimization and optimal control of dynamic systems;
From page 29...
... Modeling of Heterogeneous and Dynamic Systems Integrating Control, Computing, and Communication CPS modeling requires a complete picture of control, communications, and computing with emphasis on representing and accounts for modularity, abstraction, uncertainty, and heterogeneity. Relevant techniques include linear and nonlinear models, stochastic models, and discrete-event and hybrid models, and associated design methodologies based on optimization, probability theory, and dynamic programming are needed.
From page 30...
... Concepts that transcend the entire life cycle include safety, resilience, security, and privacy. SYSTEM CHARACTERISTICS Building systems that operate with increased confidence in the presence of uncertainty and with acceptable levels of risk requires an understanding of how to address relevant design aspects (i.e., security, reliability, and dependability)
From page 31...
... The compact size and autonomous operation of some CPS components make energy management a critical engineering design priority. • Safety.
From page 32...
... Engineers are going to have to accept responsibility for their own continual reeducation, and engineering schools are going to have to prepare engineers to do so by teaching them how to learn.1 This observation is especially apt for an emerging and rapidly changing area like CPS, and suggests that CPS courses and programs need to emphasize ongoing learning and critical thinking about technology as well as specific techniques and methods. The NAE report also takes note of the growing scale and complexity of engineering systems, which mean that engineers are increasingly working collaboratively with experts from multiple disciplines.
From page 33...
... Given the potential economic impact of CPS, related areas, and their applications, there is likely to be growing demand for integrating entrepreneurship into CPS engineering education. Entrepreneurship would naturally fit into capstone or other project-based courses.


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