Journal ArticleDOI
Sliding mode control for semi-Markovian jump systems via output feedback
TLDR
A sliding mode controller is synthesized to drive the underlying closed-loop system onto the sliding surface in finite time, locally for a given sliding region, which also guarantees the stochastic stability of sliding mode dynamical system.About:
This article is published in Automatica.The article was published on 2017-07-01. It has received 242 citations till now. The article focuses on the topics: Sliding mode control & State observer.read more
Citations
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Book ChapterDOI
$$\mathscr {L}_\infty $$ Control
TL;DR: In this paper , the authors focus on the control problem for positive delayed semi-Markov jump systems (S-MJSs) and provide necessary and sufficient conditions for state-feedback controller satisfying boundedness and positivity of the resulting closed-loop system.
Journal ArticleDOI
Adaptive Event-Triggered L2-L∞ Control of Semi-Markov Jump Distributed Parameter Systems
Yu Mei,Guan Wang,Hao Shen +2 more
TL;DR: In this paper , an adaptive event-triggered L 2 − L ∞ control for distributed parameter systems with semi-Markov jump parameters is proposed to decrease the frequency of data transmission.
Book ChapterDOI
Extended Dissipativity-Based Control for Fuzzy Switched Systems with Intermittent Measurements
TL;DR: This chapter investigates the asynchronous output feedback control problem for networked fuzzy switched systems with a desired extended dissipative performance by adopting the HMM principle and applies a stochastic Bernoulli process.
Book ChapterDOI
Robust Finite-Time Stabilization
TL;DR: In this article , robust finite-time stabilization is discussed for positive semi-Markov jump systems (S-MJSs), in which semi-markov process, time-varying delay, external disturbance, and transient performance in finite time level are all considered in a unified framework.
Book ChapterDOI
Quantized Sliding Mode Control
TL;DR: In this paper , the problem of sliding mode control design for nonlinear semi-Markovian switching systems with quantization is discussed and sufficient conditions are obtained for stochastic stability through weak infinitesimal operator theory.
References
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Book
Jump linear systems in automatic control
Abstract: This book is a monograph on hybrid parameter processes that are characterized by the presence of a discrete parameter and continuous variables. The author considers stochastic models in which the future control trajectories and the present solution do not determine completely the future of the system. The special stochastic processes and systems treated by the author are characterized by random transitions between different regimes, and this randomness primarily occurs through its discrete parameters. The book consists of eight chapters and two appendices. The appendices present brief summaries of basic probability, random processes, optima1 filtering, stochastic stability, stochastic maximum principles, matrix maximum principles, and stochastic dynamic programming. Readers might find it useful to consult references on applied probability and Markov processes before reading the eight chapters of this book. The first chapter introduces the reader to hybrid dynamic models by means of examples from target tracking, manufacturing processes, solar thermal receivers, and fault-tolerant control systems. Chapter 2 examines the global controllability and relative and stochastic stability of hybrid parameter systems. Also included in Chapter 2 are the concepts of Liapunov function and Liapunov exponents, observability, and detectability. Chapter 3 considers control optimization, jump linear quadratic regulators derived from maximum principles and dynamic programming, asymptotic behavior of quadratic regulators, suboptima1 solutions, optima1 switching output feedback, and algorithms for the optimization and evaluation of regulators for jump quadratic systems. The robustness, costs and their distribution, bound costs, and minimax solutions of jump linear systems are treated in Chapter 4, while the jump linear quadratic Gaussian problem is analyzed in some detail with Karman filtering and Poisson impulsive disturbances in Chapter 5. Optimal filtering, Wiener-driven oscillations, filter performance, and point-process observations are considered in Chapter 6. Chapter 7 deals with control under regime uncertainty, stability, control optimization, and regime estimation filters. The final chapter, Chapter 8, considers extensions of hybrid systems, non-Markovian processes, wide-band hybrid models, and extensions of the jump linear systems presented in the previous seven chapters. The book contains many theorems and proofs, is well illustrated with examples, and covers the material in depth. It is relatively free of typographical errors except that pages 206 and 207 have been interchanged.
Journal ArticleDOI
Stochastic stability properties of jump linear systems
TL;DR: In this paper, the authors studied stochastic stability properties in jump linear systems and the relationship among various moment and sample path stability properties, and showed that all second moment stability properties are equivalent and are sufficient for almost sure sample path stabilisation.
Journal ArticleDOI
On designing of sliding-mode control for stochastic jump systems
TL;DR: Using Linear matrix inequalities (LMIs) approach, sufficient conditions are proposed to guarantee the stochastic stability of the underlying system and a reaching motion controller is designed such that the resulting closed-loop system can be driven onto the desired sliding surface in a limited time.
Journal ArticleDOI
State Estimation and Sliding-Mode Control of Markovian Jump Singular Systems
Ligang Wu,Peng Shi,Huijun Gao +2 more
TL;DR: A new necessary and sufficient condition is proposed in terms of strict linear matrix inequality (LMI), which guarantees the stochastic admissibility of the unforced Markovian jump singular system.
Journal ArticleDOI
Delay-Dependent $H_{\infty }$ Control and Filtering for Uncertain Markovian Jump Systems With Time-Varying Delays
TL;DR: Improved delay-dependent stochastic stability and bounded real lemma (BRL) for Markovian delay systems are obtained by introducing some slack matrix variables and the conservatism caused by either model transformation or bounding techniques is reduced.