The Experts below are selected from a list of 4560 Experts worldwide ranked by ideXlab platform

Jin Bae Park - One of the best experts on this subject based on the ideXlab platform.

  • decentralized fuzzy observer based output feedback control for nonlinear large scale systems an lmi approach
    IEEE Transactions on Fuzzy Systems, 2014
    Co-Authors: Jin Bae Park
    Abstract:

    This paper presents a decentralized fuzzy control problem for asymptotic stabilization of a class of nonlinear large-scale systems that use an observer-based output-feedback scheme. A Takagi-Sugeno (T-S) fuzzy model is adopted for the nonlinear large-scale system, which has unknown interconnection terms, and a fuzzy controller is separately considered for measurable and nonmeasurable Premise Variable cases. Sufficient conditions are derived for both asymptotic stabilization and optimization of a maximum bound of interconnection and are formulated in terms of linear matrix inequalities. Finally, numerical examples are provided to verify the effectiveness of the proposed techniques.

  • digitalizing a fuzzy observer based output feedback control intelligent digital redesign approach
    IEEE Transactions on Fuzzy Systems, 2005
    Co-Authors: Jin Bae Park
    Abstract:

    This paper concerns an intelligent digital redesign (IDR) technique for a Takagi-Sugeno fuzzy observer-based output-feedback control (FOBOFC) system. The term IDR involves converting an existing analog control into an equivalent digital counterpart in the sense of state-matching. The IDR problem is herein viewed as a minimization problem of the norm distances between nonlinearly interpolated linear operators to be matched. Its constructive condition with global rather than local state-matching is formulated in terms of bilinear matrix inequalities. The main features of the proposed method are that the state estimation error in the plant dynamics is considered in the IDR condition that plays a crucial role in the performance improvement; the stability property is preserved by the proposed IDR algorithm; the separation principle is shown when the Premise Variables are measurable; finally, the IDR condition for a more general FOBOFC-an estimated Premise Variable case is conducted. A numerical example is demonstrated to visualize the feasibility of the developed methodology

  • intelligent digital redesign of fuzzy observer controller estimated Premise Variable case
    Society of Instrument and Control Engineers of Japan, 2004
    Co-Authors: Ho Jae Lee, Young Hoon Joo, Jin Bae Park
    Abstract:

    An intelligent digital redesign (IDR) technique for the Takagi-Sugeno fuzzy observer-based output-feedback (FOBOFC) control system with estimated Premise Variables is developed. The IDR condition is parameterized as a numerical minimization problem of the norm distances between linear operators to be matched. The exponential stabilizability by the redesigned digital FOBOFC is proved. This method can be used as an efficient design tool for a reliable nonlinear sampled-data output-feedback control.

Jun Yoneyama - One of the best experts on this subject based on the ideXlab platform.

  • h output feedback control for fuzzy systems with immeasurable Premise Variables discrete time case
    Applied Soft Computing, 2008
    Co-Authors: Jun Yoneyama
    Abstract:

    This paper discusses H"~ output feedback control of discrete-time Takagi-Sugeno fuzzy systems with immeasurable Premise Variables. When we consider the output feedback control of Takagi-Sugeno fuzzy systems, the selection of Premise Variables plays an important role. If the Premise Variable is the state of the system, then a fuzzy system describes a wide class of nonlinear systems. However, the state is not measurable in the output feedback control problem. In this case, a control design of the underlying nonlinear system based on parallel distributed compensation is infeasible because a controller depends on the immeasurable state Variable. In this paper, we introduce a new method to treat fuzzy systems with immeasurable Premise Variables and consider a design method of H"~ output feedback control problem. We formulate this fuzzy control problem as a robust H"~ control of an uncertain system. Numerical examples are given to illustrate our methods.

Tassio Melo Linhares - One of the best experts on this subject based on the ideXlab platform.

  • dynamic output feedback controller design for uncertain takagi sugeno fuzzy systems a Premise Variable selection approach
    IEEE Transactions on Fuzzy Systems, 2021
    Co-Authors: Eduardo S Tognetti, Tassio Melo Linhares
    Abstract:

    This article presents new design conditions of full-order dynamic output feedback controllers for continuous-time Takagi–Sugeno (T–S) fuzzy systems allowing the selection of Premise Variables to be used in the control law. The fuzzy output controller is allowed to have a different number of fuzzy rules and a different set of membership functions from the T–S model. This includes the cases of complete or partial immeasurable Premise Variables. The main aspect of the proposed methodology is to present conditions such that the control gains are independent of the Premise Variables that cannot be measured allowing flexibility for the designer in a realistic output feedback context. For this purpose, the design conditions are expressed as linear matrix inequality relaxations combined with scalar parameters that provide extra degrees of freedom. The proposed control methodology also deals with model uncertainties and the use of fuzzy Lyapunov functions. The effectiveness and applicability of the methodology are shown through numerical examples.

Peng Shi - One of the best experts on this subject based on the ideXlab platform.

  • robust h output feedback control design for fuzzy dynamic systems with quadratic d stability constraints an lmi approach
    Information Sciences, 2006
    Co-Authors: Sing Kiong Nguang, Peng Shi
    Abstract:

    This paper addresses the problem of designing a robust output feedback controller for a class of fuzzy uncertain dynamic systems that guarantees (i) the L"2-gain from an exogenous input to a regulated output is less or equal to a prescribed value and (ii) the closed-loop fuzzy system to be quadratically stable within a pre-specified LMI stability region. Based on an LMI approach, solutions to the problem are derived in terms of a family of linear matrix inequalities. In contrast to most existing results, the controller's Premise Variable is allowed to be different from the fuzzy model's Premise Variable. The chaotic Lorenz system is used to illustrate the effectiveness of the proposed design techniques.

Lizeth Torres - One of the best experts on this subject based on the ideXlab platform.

  • observer synthesis for a class of takagi sugeno descriptor system with unmeasurable Premise Variable application to fault diagnosis
    International Journal of Systems Science, 2017
    Co-Authors: F R Lopezestrada, C M Astorgazaragoza, Didier Theilliol, Jeanchristophe Ponsart, G Valenciapalomo, Lizeth Torres
    Abstract:

    This paper proposes a methodology to design a Takagi–Sugeno (TS) descriptor observer for a class of TS descriptor systems. Unlike the popular approach that considers measurable Premise Variables, this paper considers the Premise Variables depending on unmeasurable vectors, e.g. the system states. This consideration covers a large class of nonlinear systems and represents a real challenge for the observer synthesis. Sufficient conditions to guarantee robustness against the unmeasurable Premise Variables and asymptotic convergence of the TS descriptor observer are obtained based on the H∞ approach together with the Lyapunov method. As a result, the designing conditions are given in terms of linear matrix inequalities (LMIs). In addition, sensor fault detection and isolation are performed by means of a generalised observer bank. Two numerical experiments, an electrical circuit and a rolling disc system, are presented in order to illustrate the effectiveness of the proposed method.