Litcius/Paper detail

Dissipativity-Based Sampled-Data Control for Fuzzy Switched Markovian Jump Systems

Jianwei Xia, Guoliang Chen, Ju H. Park, Hao Shen, Guangming Zhuang

2020IEEE Transactions on Fuzzy Systems124 citationsDOI

Abstract

In this article, the dissipativity-based sampled-data control problem is studied for the fuzzy switched Markovian jump systems (FSMJSs). By considering the problem of the asynchronous switching caused by the subsystems' switching occurred during the sampling intervals, constructing novel time-dependent Lyapunov functional, and using average dwell time (ADT) approach, sufficient mean-square exponential stability criteria, and strictly ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> )-γ- dissipativity criteria are proposed under the constraints that the maximum sampling period is no larger than the dwell-time between the transition rates switching instants. Meanwhile, a relationship between ADT and sampling period is revealed for FSMJSs. Based on the strictly ( <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Q</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">S</i> , <i xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">R</i> )-γ- dissipativity criteria, the sampled-data controller is designed for FSMJSs. A circuit simulation example is provided to illustrate the effectiveness of the proposed method.

Topics & Concepts

Sampling (signal processing)Controller (irrigation)Dwell timeComputer scienceFuzzy logicAsynchronous communicationMathematicsAlgorithmDiscrete mathematicsApplied mathematicsArtificial intelligenceDetectorClinical psychologyMedicineBiologyAgronomyComputer networkTelecommunicationsStability and Control of Uncertain SystemsNeural Networks Stability and SynchronizationFrequency Control in Power Systems