Network-Based Quantized Control for Fuzzy Singularly Perturbed Semi-Markov Jump Systems and its Application

This paper deals with the quantized control problem for nonlinear semi-Markov jump systems subject to singular perturbation under a network-based framework. The nonlinearity of the system is well solved by applying Takagi-Sugeno (T-S) fuzzy theory. The semi-Markov jump process with the memory matrix...

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Veröffentlicht in:IEEE transactions on circuits and systems. I, Regular papers Jg. 66; H. 3; S. 1130 - 1140
Hauptverfasser: Shen, Hao, Men, Yunzhe, Wu, Zheng-Guang, Cao, Jinde, Lu, Guoping
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York IEEE 01.03.2019
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Collective intelligence
Control stability
Control systems
Control systems design
D C motors
Data models
Electric motors
Fuzzy control
Fuzzy systems
Markov processes
networked control systems
Nonlinear control
Nonlinear systems
Nonlinearity
packet dropouts
Quantization (signal)
Semi-Markov jump systems
signal quantization
Singular perturbation
singularly perturbed systems
Stability analysis
T-S fuzzy control
Transition probabilities
Upper bounds
ISSN:1549-8328, 1558-0806
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Zusammenfassung:This paper deals with the quantized control problem for nonlinear semi-Markov jump systems subject to singular perturbation under a network-based framework. The nonlinearity of the system is well solved by applying Takagi-Sugeno (T-S) fuzzy theory. The semi-Markov jump process with the memory matrix of transition probability is introduced, for which the obtained results are more reasonable and less limiting. In addition, the packet dropouts governed by a Bernoulli variable and the signal quantization associated with a logarithmic quantizer are deeply studied. The major goal is to devise a fuzzy controller, which not only assures the mean-square σ̅-error stability of the corresponding system but also allows a higher upper bound of the singularly perturbed parameter. Sufficient conditions are developed to make sure that the applicable controller could be found. The further examination to demonstrate the feasibility of the presented method is given by designing a controller of a series DC motor model.
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ISSN:1549-8328
1558-0806
DOI:10.1109/TCSI.2018.2876937