This book presents up-to-date research developments and novel methodologies on semi-Markovian jump systems (S-MJS). It presents solutions to a series of problems with new approaches for the control and filtering of S-MJS, including stability analysis, sliding mode control, dynamic output feedback control, robust filter design, and fault detection. A set of newly developed techniques such as piecewise analysis method, positively invariant set approach, event-triggered method, and cone complementary linearization approaches are presented. Control and Filtering for Semi-Markovian Jump Systems is a comprehensive reference for researcher and practitioners working in control engineering, system sciences and applied mathematics, and is also a useful source of information for senior undergraduates and graduates in these areas. The readers will benefit from some new concepts, new models and new methodologies with practical significance in control engineering and signal processing.

Introduces the research background and significance as well as recent research in Markovian jump systems and semi-Markovian jump systems Focuses on the stability analysis and control design for some classes of semi-Markovian jump systems (S-MJS), as well as on the fault detection and filtering of S-MJS Provides valuable reference material for researchers who wish to explore the area of S-MJS Includes supplementary material: sn.pub/extras

Inhalt
Introduction.- Stochastic Stability of Semi-Markovian Jump Systems.- Constrained Regulation of Singular Semi-Markovian Jump Systems.- State Estimation and Sliding Mode Control for Semi-Markovian Jump Systems.- Quantized Output Feedback Control of Nonlinear Semi-Markovian Jump Systems.- Passive Filtering for Delayed Neutral-Type Semi-Markovian Jump Systems.- Event-Triggered Fault Detection for Semi-Markovian Jump Systems.- Fuzzy Fault Detection Filtering for Semi-Markovian Jump Systems.- Fault Detection for Underactuated Manipulators Modeled by MJS.- Conclusion and Further Work.