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Journal ArticleDOI

A New Approach to Stability Analysis and Stabilization of Discrete-Time T-S Fuzzy Time-Varying Delay Systems

01 Feb 2011-Vol. 41, Iss: 1, pp 273-286
TL;DR: This paper investigates the problems of stability analysis and stabilization for a class of discrete-time Takagi-Sugeno fuzzy systems with time-varying state delay with a novel fuzzy Lyapunov-Krasovskii functional and proposes a delay partitioning method.
Abstract: This paper investigates the problems of stability analysis and stabilization for a class of discrete-time Takagi-Sugeno fuzzy systems with time-varying state delay. Based on a novel fuzzy Lyapunov-Krasovskii functional, a delay partitioning method has been developed for the delay-dependent stability analysis of fuzzy time-varying state delay systems. As a result of the novel idea of delay partitioning, the proposed stability condition is much less conservative than most of the existing results. A delay-dependent stabilization approach based on a nonparallel distributed compensation scheme is given for the closed-loop fuzzy systems. The proposed stability and stabilization conditions are formulated in the form of linear matrix inequalities (LMIs), which can be solved readily by using existing LMI optimization techniques. Finally, two illustrative examples are provided to demonstrate the effectiveness of the techniques proposed in this paper.
Citations
More filters
Journal ArticleDOI
TL;DR: A new integral inequality is presented, called a free-matrix-based integral inequality, that further reduces the conservativeness in those methods used to derive delay-dependent criteria for the stability analysis of time-varying-delay systems.
Abstract: The free-weighting matrix and integral-inequality methods are widely used to derive delay-dependent criteria for the stability analysis of time-varying-delay systems because they avoid both the use of a model transformation and the technique of bounding cross terms. This technical note presents a new integral inequality, called a free-matrix-based integral inequality, that further reduces the conservativeness in those methods. It includes well-known integral inequalities as special cases. Using it to investigate the stability of systems with time-varying delays yields less conservative delay-dependent stability criteria, which are given in terms of linear matrix inequalities. Two numerical examples demonstrate the effectiveness and superiority of the method.

637 citations

Journal ArticleDOI
TL;DR: Sufficient conditions for the obtained filtering error system are proposed by applying an input-output approach and a two-term approximation method, which is employed to approximate the time-varying delay.
Abstract: In this paper, the problem of l2- l∞ filtering for a class of discrete-time Takagi-Sugeno (T-S) fuzzy time-varying delay systems is studied. Our attention is focused on the design of full- and reduced-order filters that guarantee the filtering error system to be asymptotically stable with a prescribed H∞ performance. Sufficient conditions for the obtained filtering error system are proposed by applying an input-output approach and a two-term approximation method, which is employed to approximate the time-varying delay. The corresponding full- and reduced-order filter design is cast into a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, simulation examples are provided to illustrate the effectiveness of the proposed approaches.

406 citations


Cites background or result from "A New Approach to Stability Analysi..."

  • ...It can be seen that the methods proposed in this paper are better than the recently published results in [12] and [33]....

    [...]

  • ...which has been considered in [12] and [33]....

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  • ...For different d ̄ d ̄ = 3 d ̄ = 5 d ̄ = 10 d ̄ = 12 Theorem 1 of [12] d̄ = 14 d̄ = 16 d̄ = 20 d̄ = 21 Theorem 3 of [33] d̄ = 23 (m = 3) d̄ = 25 (m = 5) d̄ = 29 (m = 5) d̄ = 32 (m = 3) Corollary 1 d̄ = 100 (m = 3) d̄ = 102 (m = 5) d̄ = 107 (m = 5) d̄ = 109 (m = 3)...

    [...]

Journal ArticleDOI
TL;DR: This paper focuses on analyzing a new model transformation of discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and applying it to dynamic output feedback (DOF) controller design.
Abstract: This paper focuses on analyzing a new model transformation of discrete-time Takagi-Sugeno (T-S) fuzzy systems with time-varying delays and applying it to dynamic output feedback (DOF) controller design. A new comparison model is proposed by employing a new approximation for time-varying delay state, and then, a delay partitioning method is used to analyze the scaled small gain of this comparison model. A sufficient condition on discrete-time T-S fuzzy systems with time-varying delays, which guarantees the corresponding closed-loop system to be asymptotically stable and has an induced l2 disturbance attenuation performance, is derived by employing the scaled small-gain theorem. Then, the solvability condition for the induced l2 DOF control is also established, by which the DOF controller can be solved as linear matrix inequality optimization problems. Finally, examples are provided to illustrate the effectiveness of the proposed approaches.

326 citations


Cites background or methods or result from "A New Approach to Stability Analysi..."

  • ...The results in ([28], [29]) were proved to be less and less conservative as the partitioning becomes increasingly thinner for discrete-time T-S fuzzy systems with time-varying delays....

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  • ...Remark 7: Note that [29] is concerned with the state feedback controller design for discrete-time T-S fuzzy systems with time-varying delays, while this work is mainly focused on the problem of the dynamic output controller design....

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  • ...The comparison results are presented in Table I of Example 1, which clearly shows our results are more effective than the work in [29]....

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  • ...To illustrate the effectiveness of the new model transformation, we compare the result in Corollary 1 with Theorem 2 of [29]....

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  • ...This delay partition approach has been used in Theorem 2 of [29]....

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Journal ArticleDOI
TL;DR: An IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions.
Abstract: This paper focuses on designing interval type-2 (IT2) control for nonlinear systems subject to parameter uncertainties. To facilitate the stability analysis and control synthesis, an IT2 Takagi-Sugeno (T-S) fuzzy model is employed to represent the dynamics of nonlinear systems of which the parameter uncertainties are captured by IT2 membership functions characterized by the lower and upper membership functions. A novel IT2 fuzzy controller is proposed to perform the control process, where the membership functions and number of rules can be freely chosen and different from those of the IT2 T-S fuzzy model. Consequently, the IT2 fuzzy-model-based (FMB) control system is with imperfectly matched membership functions, which hinders the stability analysis. To relax the stability analysis for this class of IT2 FMB control systems, the information of footprint of uncertainties and the lower and upper membership functions are taken into account for the stability analysis. Based on the Lyapunov stability theory, some stability conditions in terms of linear matrix inequalities are obtained to determine the system stability and achieve the control design. Finally, simulation and experimental examples are provided to demonstrate the effectiveness and the merit of the proposed approach.

311 citations

Journal ArticleDOI
TL;DR: In this paper, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures and a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms.
Abstract: In this paper, the problem of reliable filter design with strict dissipativity has been investigated for a class of discrete-time T-S fuzzy time-delay systems. Our attention is focused on the design of a reliable filter to ensure a strictly dissipative performance for the filtering error system. Based on the reciprocally convex approach, firstly, a sufficient condition of reliable dissipativity analysis is proposed for T-S fuzzy systems with time-varying delays and sensor failures. Then, a reliable filter with strict dissipativity is designed by solving a convex optimization problem, which can be efficiently solved by standard numerical algorithms. Finally, numerical examples are provided to illustrate the effectiveness of the developed techniques.

284 citations


Cites background or result from "A New Approach to Stability Analysi..."

  • ...which has been considered in [6] and [35]....

    [...]

  • ...It can be seen that the methods proposed in this paper are better than the results reported recently in [6] and [35]....

    [...]

  • ...Moreover, by comparison of Corollary 1 with some existing ones [6], [26], [35], see Table I in Example 1, it clearly shows our results are more effective than the work in [6], [26], and [35]....

    [...]

  • ...Comparing with the existing results to deal with T-S fuzzy time-delay systems, such as the method of circumventing the utilization of some bounding inequalities [6], the input–output approach [26] and the delay partition approach [35], the advantages of our results are twofold....

    [...]

  • ...The results in [35] were proved to be less and less conservative as the partitioning becomes increasingly thinner for discrete-time T-S fuzzy time-delay systems....

    [...]

References
More filters
Journal ArticleDOI
01 Jan 1985
TL;DR: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented and two applications of the method to industrial processes are discussed: a water cleaning process and a converter in a steel-making process.
Abstract: A mathematical tool to build a fuzzy model of a system where fuzzy implications and reasoning are used is presented. The premise of an implication is the description of fuzzy subspace of inputs and its consequence is a linear input-output relation. The method of identification of a system using its input-output data is then shown. Two applications of the method to industrial processes are also discussed: a water cleaning process and a converter in a steel-making process.

18,803 citations


"A New Approach to Stability Analysi..." refers background or methods in this paper

  • ...It is well known that there has been a turning point in one of the most effective methods in accordance with the advent of the Takagi-Sugeno (T-S) fuzzy model [19], which is among all of models to solve the control of complex nonlinear systems....

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  • ...Thus, considerable attention has been devoted to investigate nonlinear systems with time-delay by the corresponding T-S fuzzy models [19]....

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Book
02 May 2008
TL;DR: Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.
Abstract: From the Publisher: A comprehensive treatment of model-based fuzzy control systems This volume offers full coverage of the systematic framework for the stability and design of nonlinear fuzzy control systems. Building on the Takagi-Sugeno fuzzy model, authors Tanaka and Wang address a number of important issues in fuzzy control systems, including stability analysis, systematic design procedures, incorporation of performance specifications, numerical implementations, and practical applications. Issues that have not been fully treated in existing texts, such as stability analysis, systematic design, and performance analysis, are crucial to the validity and applicability of fuzzy control methodology. Fuzzy Control Systems Design and Analysis addresses these issues in the framework of parallel distributed compensation, a controller structure devised in accordance with the fuzzy model. This balanced treatment features an overview of fuzzy control, modeling, and stability analysis, as well as a section on the use of linear matrix inequalities (LMI) as an approach to fuzzy design and control. It also covers advanced topics in model-based fuzzy control systems, including modeling and control of chaotic systems. Later sections offer practical examples in the form of detailed theoretical and experimental studies of fuzzy control in robotic systems and a discussion of future directions in the field. Fuzzy Control Systems Design and Analysis offers an advanced treatment of fuzzy control that makes a useful reference for researchers and a reliable text for advanced graduate students in the field.

3,183 citations


Additional excerpts

  • ...By using the same procedure as in [20], the nonlinear term θ(2) can be exactly represented as θ(2)(k) = h1 (θ(k)) (−m)θ(k) + h2 (θ(k)) mθ(k)...

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Journal ArticleDOI
TL;DR: A survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models.
Abstract: Fuzzy logic control was originally introduced and developed as a model free control design approach. However, it unfortunately suffers from criticism of lacking of systematic stability analysis and controller design though it has a great success in industry applications. In the past ten years or so, prevailing research efforts on fuzzy logic control have been devoted to model-based fuzzy control systems that guarantee not only stability but also performance of closed-loop fuzzy control systems. This paper presents a survey on recent developments (or state of the art) of analysis and design of model based fuzzy control systems. Attention will be focused on stability analysis and controller design based on the so-called Takagi-Sugeno fuzzy models or fuzzy dynamic models. Perspectives of model based fuzzy control in future are also discussed

1,575 citations

Journal ArticleDOI
TL;DR: This paper proposes different parameterized linear matrix inequality (PLMI) characterizations for fuzzy control systems and these characterizations are relaxed into pure LMI programs, which provides tractable and effective techniques for the design of suboptimal fuzzy control Systems.
Abstract: This paper proposes different parameterized linear matrix inequality (PLMI) characterizations for fuzzy control systems. These PLMI characterizations are, in turn, relaxed into pure LMI programs, which provides tractable and effective techniques for the design of suboptimal fuzzy control systems. The advantages of the proposed methods over earlier ones are then discussed and illustrated through numerical examples and simulations.

1,099 citations


"A New Approach to Stability Analysi..." refers background or result in this paper

  • ...Some of the existing results were usually derived by using a single Lyapunov function method [21], [24], the main drawback of which is that it leads to conservative results....

    [...]

  • ...By using [24], if conditions (33), (34) hold, then (40) is fulfilled....

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  • ...The stability issue of fuzzy control systems has been studied in [8], [21], [24], [26], [29], [30]....

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Journal ArticleDOI
TL;DR: Some new delay-dependent stability criteria are devised by taking the relationship between the terms in the Leibniz-Newton formula into account, which are less conservative than existing ones.

1,069 citations


"A New Approach to Stability Analysi..." refers background in this paper

  • ...Hence, researchers have been paying remarkable attention to the problems of analysis and synthesis for time-delay systems (for example, [1]–[3], [13], [16], [18], [23], [27], [28], [31], [33], [35], [37])....

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  • ...All these existing literatures for stability analysis can be roughly divided into two types: delay-independent results [23] and delay-dependent ones [13], [16], [27], [35], [37]....

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