Stabilization of T-S Fuzzy System With Time Delay Under Sampled-Data Control Using a New Looped-Functional

Chen, Hua; Wu, Shuangshuang; Guan, Xinping

doi:10.1109/tfuzz.2019.2906040

Cited by 126 publications

(39 citation statements)

References 37 publications

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“…x (35) where l = 2.8, L = 5.5, v = −1.0ã = 0.7,t = 2.0, t 0 = 0.5, w(t) is the external disturbance.…”

Section: Simulation Examplesmentioning

confidence: 99%

“…Moreover, in practical systems, the phenomenon of time delay leads to oscillations and instability frequently. In [9], [10], [14], [16], [34], [35], some fuzzy sampleddata control schemes were designed for nonlinear dynamical systems with delay behavior. The control performance design was described clearly in [9].…”

Section: Introductionmentioning

confidence: 99%

“…For T-S fuzzy systems with time delay and parametric uncertainties, a robust guaranteed cost sampled-data fuzzy control design method was proposed in [34]. In [35], the stabilization of a T-S fuzzy system with time delay was explored, in which the designed fuzzy controller of sampleddata contained both the current and delayed state information. In addition, if the H 2 performance and H ∞ performance can be optimized simultaneously, the control system will show a better performance.…”

Section: Introductionmentioning

confidence: 99%

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New Results of Fuzzy Sampled-Data Control for Nonlinear Time-Delay Systems

Zhang

2020

IEEE Access

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In the manuscript, synthesis and stability analysis for fuzzy H 2 /H ∞ sampled-data control of dynamical systems with delay behavior are studied by employing the input delay method. By using Lyapunov theory, a new H 2 /H ∞ standard is derived and the fuzzy sampled-data controller is proposed to ensure H ∞ performance and H 2 performance simultaneously. Meanwhile, the control design is verified by two practical examples. Furthermore, experimental results also indicate that the H 2 /H ∞ sampled-data control has a better performance. INDEX TERMS Dynamical systems, delay behavior, fuzzy sampled-data control, H 2 /H ∞ control.

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“…x (35) where l = 2.8, L = 5.5, v = −1.0ã = 0.7,t = 2.0, t 0 = 0.5, w(t) is the external disturbance.…”

Section: Simulation Examplesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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New Results of Fuzzy Sampled-Data Control for Nonlinear Time-Delay Systems

Zhang

2020

IEEE Access

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“…However, several realistic problems are shown in the pattern of nonlinear stochastic systems which can be represented by the type of It

ô

stochastic differential equations, for example, mechanical systems, economic systems and biological systems, and so on. For this, the Takagi‐Sugeno (T‐S) fuzzy idea has proven as a well‐organized tool for the different types of nonlinear systems with uncertainty, stochasticity, and time‐delay 9 . The major concept of T‐S fuzzy is to reduce to the bare bones of the considered nonlinear systems (by means of a set of linear input‐output subsystems with corresponding membership functions) for more investigation and synthesis 10 .…”

Section: Introductionmentioning

confidence: 99%

Event‐triggered integral sliding mode control of Takagi‐Sugeno fuzzy stochastic systems

Sharmila

Rakkiyappan

Joo

2021

Adaptive Control & Signal

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This article analyzes the integral sliding mode control (ISMC) problem for the nonlinear stochastic system by employing the fuzzy approach. Firstly, the Takagi‐Sugeno (T‐S) fuzzy stochastic model with unknown nonlinear function and external disturbance has been developed. Based on the fuzzy model, an observer‐based integral sliding mode fuzzy controller is derived under the event‐triggered scheme (ETS). The Lyapunov‐Krasovskii functionals (LKFs) involving double and triple integral terms are considered and evaluated by applying Writinger inequality lemma and reciprocally convex combination lemma. With the help of matrix's singular value decomposition lemma, the stability conditions have been derived which is in terms of linear matrix inequalities (LMIs) and this can be solved by MATLAB LMI toolbox. Two numerical examples are provided to demonstrate the usefulness of our theoretical conclusions.

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“…Since time delay frequently occurs in practical systems and is often the source of instability, there have been many results for stability of delayed systems [3][4][5][6][7][8][9]. Also stabilization [10][11][12], filtering [13], and adaptive control [14] of time-delay systems have received considerable attention. e neutral systems often appear in the study of automatic control, population dynamics, and vibrating masses attached to an elastic bar [15].…”

Section: Introductionmentioning

confidence: 99%

Novel Delay‐Decomposing Approaches to Absolute Stability Criteria for Neutral‐Type Lur’e Systems

Guo

Huang

2019

Mathematical Problems in Engineering

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The problem of absolute stability analysis for neutral-type Lur’e systems with time-varying delays is investigated. Novel delay-decomposing approaches are proposed to divide the variation interval of the delay into three unequal subintervals. Some new augment Lyapunov–Krasovskii functionals (LKFs) are defined on the obtained subintervals. The integral inequality method and the reciprocally convex technique are utilized to deal with the derivative of the LKFs. Several improved delay-dependent criteria are derived in terms of the linear matrix inequalities (LMIs). Compared with some previous criteria, the proposed ones give the results with less conservatism and lower numerical complexity. Two numerical examples are included to illustrate the effectiveness and the improvement of the proposed method.

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Stabilization of T-S Fuzzy System With Time Delay Under Sampled-Data Control Using a New Looped-Functional

Cited by 126 publications

References 37 publications

New Results of Fuzzy Sampled-Data Control for Nonlinear Time-Delay Systems

New Results of Fuzzy Sampled-Data Control for Nonlinear Time-Delay Systems

Event‐triggered integral sliding mode control of Takagi‐Sugeno fuzzy stochastic systems

Novel Delay‐Decomposing Approaches to Absolute Stability Criteria for Neutral‐Type Lur’e Systems

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