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Nonlinear Control and Filtering for Stochastic Networked Systems

Nonlinear Control and Filtering for Stochastic Networked Systems

          
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About the Book

In this book, control and filtering problems for several classes of stochastic networked systems are discussed. In each chapter, the stability, robustness, reliability, consensus performance, and/or disturbance attenuation levels are investigated within a unified theoretical framework. The aim is to derive the sufficient conditions such that the resulting systems achieve the prescribed design requirements despite all the network-induced phenomena. Further, novel notions such as randomly occurring sensor failures and consensus in probability are discussed. Finally, the theories/techniques developed are applied to emerging research areas.

Key Features

  • Unifies existing and emerging concepts concerning stochastic control/filtering and distributed control/filtering with an emphasis on a variety of network-induced complexities
  • Includes concepts like randomly occurring sensor failures and consensus in probability (with respect to time-varying stochastic multi-agent systems)
  • Exploits the recursive linear matrix inequality approach, completing the square method, Hamilton-Jacobi inequality approach, and parameter-dependent matrix inequality approach to handle the emerging mathematical/computational challenges
  • Captures recent advances of theories, techniques, and applications of stochastic control as well as filtering from an engineering-oriented perspective
  • Gives simulation examples in each chapter to reflect the engineering practice


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Product Details
  • ISBN-13: 9780367656867
  • Publisher: Taylor and Francis
  • Publisher Imprint: CRC Press
  • Height: 234 mm
  • No of Pages: 226
  • Spine Width: 13 mm
  • Width: 156 mm
  • ISBN-10: 0367656868
  • Publisher Date: 02 Oct 2020
  • Binding: Paperback
  • Language: English
  • Returnable: N
  • Weight: 349 gr


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Nonlinear Control and Filtering for Stochastic Networked Systems
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Nonlinear Control and Filtering for Stochastic Networked Systems
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