Titlebook: Control of Discrete-Time Descriptor Systems; An Anisotropy-Based Alexey A. Belov,Olga G. Andrianova,Alexander P. Ku Book 2018 Springer Int

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https://doi.org/10.1007/978-3-658-36887-6of mean anisotropy of Gaussian random sequences and anisotropic norms for linear systems are introduced in?[., ., .] and briefly described below. This chapter deals with generalization of anisotropy-based analysis of the class of descriptor systems using generalized algebraic Riccati equations and c

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Begrifflichkeiten und Einordnung,lems. The solution of the first is based on generalized discrete-time algebraic Riccati equations (GDARE). The solution of the second is based on a two-stage control procedure that consists of causalization and stabilization.

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Vermittlung von BIM in der HochschullehreThe problem may be formulated as follows: to find such control law that the closed-loop system is admissible, and its anisotropic norm is bounded by a given positive value. A similar problem for normal discrete-time systems is solved in?[.]. The conditions of anisotropic norm boundedness for descrip

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https://doi.org/10.1007/978-3-658-37005-3ynamical systems. Uncertainties in such systems are often causes of instability and bad performance. It is known that control of uncertain descriptor systems is much more complicated than that of the normal ones. The aim of this chapter is to provide conditions of anisotropic norm boundedness for de

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https://doi.org/10.1007/978-3-658-36959-0nition of mean anisotropy of the Gaussian nonzero-mean sequence, generated by the shaping filter in descriptor form. We also develop an anisotropic norm computation procedure in the frequency domain when the input signal has nonzero mean.

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Book 2018retic representation. It describes the random input signal more precisely, and the anisotropic norm minimization included in the book enables readers to tune their controllers better through the mathematical methods provided. The book contains numerous examples of practical applications of descripto

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Anisotropy-Based Analysis for LDTI Descriptor Systems with Nonzero-Mean Input Signals,nition of mean anisotropy of the Gaussian nonzero-mean sequence, generated by the shaping filter in descriptor form. We also develop an anisotropic norm computation procedure in the frequency domain when the input signal has nonzero mean.