An enhanced input-delay approach to sampled-data stabilization of T–S fuzzy systems via mixed convex combination

Summary This paper investigates the strictly dissipative stabilization problem for multiple‐memory Markov jump systems with network communication protocol. Firstly, for reducing data transmission, we put forward a novel mode‐dependent event‐triggered communication scheme based on aperiodically sampled data. Secondly, a Markov jump system with general transition rates is considered to make the result more applicable, where the transition rates of some jumping modes allow to be completely known, or partially known, or even completely unknown. Thirdly, a less restrictive Lyapunov‐Krasovskii functional, which is only required to be positive definite at end points of each subinterval of the holding intervals, is first introduced for event‐triggered control issue. Based on the above methods, a sufficient condition with less conservatism is obtained to ensure the stochastic stability and dissipativity of the resulting closed‐loop system. Meanwhile, an explicit design method of the desired controller is achieved. Finally, two numerical examples are presented to demonstrate the effectiveness and advantage of the proposed method.

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“…According to Lemma 2 in the work of Yang et al, 49 for any appropriate dimensional matrix G 6 , the following inequality holds:…”

Section: Appendixmentioning

confidence: 99%

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Xie

Zhang

Zeng

et al. 2020

Intl J Robust & Nonlinear

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“…Since the Takagi-Sugeno (T-S) fuzzy model [1] can approximate and describe complex nonlinear systems in terms of local linear systems through fuzzy sets and fuzzy membership functions, it becomes a very popular and effective tool to control nonlinear systems. So far, in the fuzzy control design, similar to the hot research of the adaptive fuzzy control [2][3][4][5], the problem of the stability analysis and control synthesis of nonlinear systems via T-S fuzzy model approach has been extensively investigated and lots of work on this issue has been reported [6][7][8][9][10][11][12][13][14][15][16][17][18][19][20]. For example, less conservative stabilization conditions and nonfragile H ∞ filtering for T-S fuzzy systems are obtained in [12] and [14], respectively.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Output‐Feedback Control for T‐S Fuzzy Systems with Input Time‐Varying Delay

Zhang

Lin

2016

Asian Journal of Control

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This paper considers the problem of the H ∞ control for T-S fuzzy systems with input time-varying delay via dynamic output feedback. Firstly, by applying the reciprocally convex approach, new delay-dependent sufficient condition for H ∞ performance analysis is obtained. Then, a less conservative condition for the existence of the H ∞ controllers is given in terms of linear matrix inequalities (LMIs). Moreover, in the considered system, the time-delay term is included in the measured output. This results in the difficulty in designing the controllers being increased and the obtained results being applied to a wider class of fuzzy systems than the most existing ones. The main contribution of this work lies in the application of the reciprocally convex inequality and the time-delay term included in the measured output. Finally, the advantages and effectiveness of the present results are shown by several numerical examples.

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“…Moreover, choosing proper sampling interval in sampled-data control systems is more important for designing suitable controllers. Consequently, sampled-data systems have been investigated extensively [21][22][23][24][25][26][27][28][29][30][31]. In [22], sampled-data control problem of linear systems has been investigated by using input delay method.…”

Section: Introductionmentioning

confidence: 99%

“…In [30], the synchronization problem of neural networks with time-varying delay under sampled-data control has been studied. After that, the sampled-data control has been investigated for T-S fuzzy systems with aperiodic sampling interval in [21]. In [25], the sampled-data synchronization control has been investigated for complex networks with time-varying coupling delay based on input delay approach.…”

Section: Introductionmentioning

confidence: 99%

Sampled-data synchronization for complex networks based on discontinuous LKF and mixed convex combination

Wang

Zhang

Wang

2015

Journal of the Franklin Institute

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An enhanced input-delay approach to sampled-data stabilization of T–S fuzzy systems via mixed convex combination

Cited by 70 publications

References 32 publications

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Strictly dissipative stabilization of multiple‐memory Markov jump systems with general transition rates: A novel event‐triggered control strategy

Dynamic Output‐Feedback Control for T‐S Fuzzy Systems with Input Time‐Varying Delay

Sampled-data synchronization for complex networks based on discontinuous LKF and mixed convex combination

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