Fuzzy modeling and control for general 2D nonlinear systems

Li, Lizhen; Wang, Weiqun

doi:10.1016/j.fss.2012.04.002

Cited by 48 publications

(13 citation statements)

References 28 publications

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“…Specifically, due to the inevitable nonlinearity, the Takagi‐Sugeno (T‐S) fuzzy model has been widely employed in modeling and control problems of 2D nonlinear systems. The stability and stabilization of 2D T‐S fuzzy systems have been studied in References 4‐12. And there has been a flurry of research on H ∞ control of 2D T‐S fuzzy systems, 10,13‐15 including 2D fuzzy systems with stochastic perturbation 14 and that with time‐delays and missing measurements 15 …”

Section: Introductionmentioning

confidence: 99%

H_∞ tracking control of two‐dimensional fuzzy networked systems

Tanaka

Chai

et al. 2020

Optim Control Appl Methods

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Summary In this article, the H∞ tracking control problem is first considered for two‐dimensional fuzzy networked control systems. The system is described by fuzzy blending of the so‐called second Fornasini‐Marchesini local linear state‐space model. Based on the fuzzy model, an observer‐based state feedback controller is employed to guarantee the H∞ tracking performance. The separation property is established in the case of observer‐based H∞ tracking control framework, that is, the controller gains and observer gains can be simultaneously obtained by solving two sets of linear matrix inequalities. A simulation example is given to illustrate the effectiveness of the proposed method.

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Section: Introductionmentioning

confidence: 99%

H_∞ tracking control of two‐dimensional fuzzy networked systems

Tanaka

Chai

et al. 2020

Optim Control Appl Methods

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“…The stability and stabilization of 2-D T-S fuzzy systems have been studied in [1], [2]. The modeling and ∞ control for 2-D T-S fuzzy systems are studied in [3].…”

Section: Introductionmentioning

confidence: 99%

Observer-based H∞ reliable control for 2-D fuzzy systems

Lin

2015

2015 10th International Conference on Information, Communications and Signal Processing (ICICS)

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This paper develops a method of fuzzy observerbased ∞ reliable controller design for two-dimensional (2-D) discrete Takagi-Sugeno (T-S) fuzzy systems. The LMI-based conditions are proposed to guarantee an ∞ noise attenuation of the whole system under both normal operation and in the presence of some actuator faults. Owing to the introduction of free matrices, the presented design method has a wider range of application and can guarantee a better ∞ performance of the closed-loop fuzzy control system. Simulation results have demonstrated the effectiveness of the proposed method.Keywords-Two-dimensional (2-D) fuzzy system, observerbased ∞ reliable control, linear matrix inequality(LMI).

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“…Many applications of one dimensional (1D) fuzzy control have been realized in practical industrial fields , for example, steam engine control , robot control and power plants . For 2D or multi‐dimensional fuzzy case, in the past decades, a lot of results have been obtained . Among these results, considered a three‐dimensional fuzzy control methodology for a class of distributed parameter systems and the authors in presented the convergent stabilization conditions of discrete‐time 2D T‐S fuzzy systems via improved homogeneous polynomial techniques.…”

Section: Introductionmentioning

confidence: 99%

“…Among these results, considered a three‐dimensional fuzzy control methodology for a class of distributed parameter systems and the authors in presented the convergent stabilization conditions of discrete‐time 2D T‐S fuzzy systems via improved homogeneous polynomial techniques. As many results on 2D fuzzy systems are based on the 2D fuzzy model, which usually is not able to sufficiently consider the spatial and structural nature of 2D systems, the authors of proposed a new fuzzy modeling method for general 2D nonlinear systems. Using this new modeling method, the number of fuzzy rules will not increase at an exponential rate as it usually does.…”

Section: Introductionmentioning

confidence: 99%

H_∞ Fault Detection for Two‐Dimensional T‐S Fuzzy Systems in FM Second Model

Wang¹,

Wang²

2014

Asian Journal of Control

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This paper investigates the H∞ fault detection problem for two-dimensional (2D) Takagi-Sugeno (T-S) fuzzy systems in a Fornasini-Marchesini second (FM II) state-space model. Our aim is to develop fault detection filters for the 2D T-S fuzzy system both in the non-fuzzy case and the fuzzy case. Attention is focused on the design of the above two kinds of fault detection filters, which guarantee the fault detection system to be asymptotically stable and to have a prescribed H∞ performance. Sufficient conditions are derived for the existence of such filters in terms of linear matrix inequalities (LMIs), and the corresponding filter synthesis problem then is solved both of the kinds of fault detection filters. Numerical examples are used to demonstrate the effectiveness of the proposed method. Moreover, simulation results show that, under the conditions of reaching the same optimal H∞ performance level and feasible region, the fault detection filter we designed for the fuzzy case has better sensitivity to the fault signal than the one designed for the non-fuzzy case.

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Fuzzy modeling and control for general 2D nonlinear systems

Cited by 48 publications

References 28 publications

H_∞ tracking control of two‐dimensional fuzzy networked systems

H_∞ tracking control of two‐dimensional fuzzy networked systems

Observer-based H∞ reliable control for 2-D fuzzy systems

H_∞ Fault Detection for Two‐Dimensional T‐S Fuzzy Systems in FM Second Model

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Fuzzy modeling and control for general 2D nonlinear systems

Cited by 48 publications

References 28 publications

H∞ tracking control of two‐dimensional fuzzy networked systems

H∞ tracking control of two‐dimensional fuzzy networked systems

Observer-based H∞ reliable control for 2-D fuzzy systems

H∞ Fault Detection for Two‐Dimensional T‐S Fuzzy Systems in FM Second Model

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Product

Resources

About

H_∞ tracking control of two‐dimensional fuzzy networked systems

H_∞ tracking control of two‐dimensional fuzzy networked systems

H_∞ Fault Detection for Two‐Dimensional T‐S Fuzzy Systems in FM Second Model