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Three problem areas associated with the design of linear sampled-data systems are considered. The first arises from having the transition and distribution matrices of the system be random variables, i.e., the random parameter problem; the second from having multiplicative noise at the input to the system, this being a special case of the first problem area; and the third from being unable to measure the state vector of the system exactly. In each of these 3 areas, the performance of the system is measured by using either a generalized sum-squared-error, a final-value, or a minimum-time criterion. The design procedures are based either upon minimizing the expected value of the performance index or upon minimiz'ng the performance index in the presence of worst-case variations within the system, e.g., minimizing the expected value of the sumsquared-error. In general, the results are in the form of feedback coefficients which relate the value of the optimum input to the value of the state vector of the system. (Author).
Engineering systems operate through actuators, most of which will exhibit phenomena such as saturation or zones of no operation, commonly known as dead zones. These are examples of piecewise-affine characteristics, and they can have a considerable impact on the stability and performance of engineering systems. This book targets controller design for piecewise affine systems, fulfilling both stability and performance requirements. The authors present a unified computational methodology for the analysis and synthesis of piecewise affine controllers, taking an approach that is capable of handling sliding modes, sampled-data, and networked systems. They introduce algorithms that will be applicable to nonlinear systems approximated by piecewise affine systems, and they feature several examples from areas such as switching electronic circuits, autonomous vehicles, neural networks, and aerospace applications. Piecewise Affine Control: Continuous-Time, Sampled-Data, and Networked Systems is intended for graduate students, advanced senior undergraduate students, and researchers in academia and industry. It is also appropriate for engineers working on applications where switched linear and affine models are important.