Fuzzy-Model-Based Sampled-Data Control of Chaotic Systems: A Fuzzy Time-Dependent Lyapunov–Krasovskii Functional Approach

Wang, Yueying; Xia, Yuanqing; Zhou, Pingfang

doi:10.1109/tfuzz.2016.2617378

Cited by 109 publications

(56 citation statements)

References 44 publications

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“…(i) is discussion for chaotic systems with both fuzzy sampled-data control and semi-Markov jump of generally uncertain transition rates is for the first time to be proposed. e obtained results in practical situation are more applicable than the previous results in [18,[20][21][22][23][24][25][26][27]. (ii) To make more cross terms of vector components in the resulting vector, a novel zero equality is established.…”

Section: Introductionmentioning

confidence: 88%

“…(iii) To take full advantage of the available information with regard to the practical sampling mode, a new augmented time-dependent LKF V 3 (x(t), r t ) is constructed, which is firstly presented for the fuzzy sampled-data semi-Markov chaotic systems. (iv) Compared with the existing stabilization conditions in [21,[24][25][26], our results are not only less computationally complex but also less conservative.…”

Section: Introductionmentioning

confidence: 92%

“…Combining the input delay method with the zero-order holder (ZOH), the sampled-data control system can be transformed as a continuous-time system with time-varying delayed control input. In recent years, according to the input delay method, lots of important stabilization results on chaotic systems with fuzzy sampleddata control were presented [18][19][20][21][22][23][24][25][26][27]. In [18,23,24], by designing fuzzy sampled-data control, the stabilization conditions for chaotic systems have been obtained.…”

Section: Introductionmentioning

confidence: 99%

“…In [19,20], by constructing input-delay-dependent LKFs, less conservative criteria for chaotic system have been studied. Very recently, by utilizing the fuzzy input-delay-dependent LKF approach, fewer constraint conditions for chaotic systems have been established in [25,26]. Most recently, by constructing a new input-delay-dependent LKF, improved results have been established for chaotic systems in [21,27].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, it should be pointed out that the existing works [18][19][20][21][22][23][24][25][26][27] considered how to obtain less conservative stabilization conditions, while they ignored calculation load. Actually, during the application of LMI-based criteria to large-scale physical systems, the computational complexity is a very significant problem [28].…”

Section: Introductionmentioning

confidence: 99%

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New Stabilization Results for Semi‐Markov Chaotic Systems with Fuzzy Sampled‐Data Control

Cao

Xiong

et al. 2019

Complexity

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This paper investigates the problem of stabilization for semi-Markov chaotic systems with fuzzy sampled-data controllers, in which the semi-Markov jump has generally uncertain transition rates. The exponential stability condition is firstly obtained by the following two main techniques: To make full use of the information about the actual sampling pattern, a novel augmented input-delay-dependent Lyapunov–Krasovskii functional (LKF) is firstly introduced. Meanwhile, a new zero-value equation is established to increase the combinations of component vectors of the resulting vector. The corresponding fuzzy sampled-data controllers are designed based on the stability condition. Finally, the validity and merits of the developed theories are shown by two numerical examples.

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Section: Introductionmentioning

confidence: 88%

Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

New Stabilization Results for Semi‐Markov Chaotic Systems with Fuzzy Sampled‐Data Control

Cao

Xiong

et al. 2019

Complexity

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A Robust Backstepping Sensorless Control for Interior Permanent Magnet Synchronous Motor Using a Super‐Twisting Based Torque Observer

Zhang

Chai

2018

Asian Journal of Control

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In order to achieve high-performance speed regulation for sensorless interior permanent magnet synchronous motors (IPMSMS), a robust backstepping sensorless control is presented in this paper. Firstly, instead of a real mechanical sensor, a robust terminal sliding mode observer is used to provide the rotor position. Then, a new super-twisting algorithm (STA) based observer is designed to obtain estimates of load torque and speed. The proposed observer ensures finite-time convergence, maintains robust to uncertainties, and eliminates the common assumption of constant or piece-wise constant load torque. Finally, a sensorless scheme is designed to realize speed control despite parameter uncertainties, by combining the robust backstepping control with sliding mode actions and the presented sliding mode observers. The stability of the observer and controller are verified by using Lyapunov's second method to determine the design gains. Simulation results show the effectiveness of the proposed approach.

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Improved sampled data fuzzy controller for nonlinear system: The event‐triggered approach

Tan

et al. 2021

Asian Journal of Control

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This paper mainly focuses on the stability analysis and sampled data controller synthesis for nonlinear system represented by the Takagi–Sugeno (T‐S) fuzzy model. To avoid network congestion and save control resource, the event‐triggered communication strategy is applied. A novel fuzzy time‐dependent Lyapunov–Krosovskii functional (LKF) is proposed by compromising the fuzzy membership function and the sampling pattern; an improved stability criterion with less conservativeness and the sampled data controller synthesis manner are proposed with the help of the extended reciprocally convex inequality. Besides that, a collaborative algorithm to optimize the corresponding control variables of sampled data control gain and the event‐triggered communication mechanism is established. Finally, the practical applicability and validity as well as the advantage of the proposed method are illustrated in the simulation part.

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Fuzzy-Model-Based Sampled-Data Control of Chaotic Systems: A Fuzzy Time-Dependent Lyapunov–Krasovskii Functional Approach

Cited by 109 publications

References 44 publications

New Stabilization Results for Semi‐Markov Chaotic Systems with Fuzzy Sampled‐Data Control

New Stabilization Results for Semi‐Markov Chaotic Systems with Fuzzy Sampled‐Data Control

A Robust Backstepping Sensorless Control for Interior Permanent Magnet Synchronous Motor Using a Super‐Twisting Based Torque Observer

Improved sampled data fuzzy controller for nonlinear system: The event‐triggered approach

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