Matrix methods for handling, reducing and analyzing data from a dynamic system are dealt with in this text which also covers techniques for the design of feedback controllers for those systems which can be perfectly modelled. The book also provides techniques for the design of feedback controllers for those systems which cannot be modelled. In addition, it draws attention to the iterative nature of the control design process, and introduces model reduction and concepts of equivalent models, topics not generally covered at this level. Chapters cover mathematical preliminaries, models of dynamic systems, properties of state space realizations, controllability and observability, equivalent realizations and model reduction, stability, optimal control of time-variant systems, state estimation, and model error concepts and compensation.
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This text deals with matrix methods for handling, reducing, and analyzing data from a dynamic system, and covers techniques for the design of feedback controllers for those systems which can be perfectly modeled. Unlike other texts at this level, this book also provides techniques for the design of feedback controllers for those systems which cannot be perfectly modeled. In addition, presentation draws attention to the iterative nature of the control design process, and introduces model reduction and concepts of equivalent models, topics not generally covered at this level. Chapters cover mathematical preliminaries, models of dynamic systems, properties of state space realizations, controllability and observability, equivalent realizations and model reduction, stability, optimal control of time-variant systems, state estimation, and model error concepts and compensation. Extensive appendixes cover the requisite mathematics.
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