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SICE Annual Conference

作者： Wen-Jer Chang Jian-Hon Sie Cheung-Chieh Ku Department of Marine Engineering National Taiwan Ocean University Keelung Taiwan Department of Electrical Engineering National Taiwan Ocean University Keelung Taiwan

ISBN: (纸本)9784907764302

This paper presents a fuzzy controller design method for the singular nonlinear systems with perturbations via singular affine Takagi-Sugeno (T-S) fuzzy models. The parallel distributed compensation (PDC) technique is applied to design this fuzzy controller for the singular affine T-S fuzzy model. However, the derived stability conditions with the fuzzy controller are bilinear matrix inequality (BMI) problems which cannot be calculated by the optimal convex programming algorithm of linear matrix inequality (LMI) method directly. In order to solve the present design problem, the BMI problems must be transferred into the LMI problems. Hence, an iterative linear matrix inequality (ILMI) algorithm is developed to find the feasible solutions for the stability conditions. Finally, a numerical example is provided to demonstrate the applications and effectiveness of the proposed fuzzy control approach.

关键词： Singular affine T-S fuzzy models parallel distributed compensation Iterative linear matrix inequality fuzzy controller design linear matrix inequalities Interim Local Management Interface Singular Affine In-law FUZZY CONTROLLER Fuzzy shunt compensation Nonlinear systems numerical example

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An Automatic Building Approach To Special Takagi-Sugeno Fuzzy Network For Unknown Plant Modeling And Stable Control

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Asian Journal of Control 2008年第2期5卷

作者： Chia-Feng Juang Department of Electrical Engineering National Chung Hsing University Taichung Taiwan R.O.C.

In previous studies, several stable controller design methods for plants represented by a special Takagi-Sugeno fuzzy network (STSFN) have been proposed. In these studies, the STSFN is, however, derived directly from the mathematical function of the controlled plant. For an unknown plant, there is a problem if STSFN cannot model the plant successfully. In order to address this problem, we have derived a learning algorithm for the construction of STSFN from input-output training data. Based upon the constructed STSFN, existing stable controller design methods can then be applied to an unknown plant. To verify this, stable fuzzy controller design by parallel distributed compensation (PDC) method is adopted. In PDC method, the precondition parts of the designed fuzzy controllers share the same fuzzy rule numbers and fuzzy sets as the STSFN. To reduce the controller rule number, the precondition part of the constructed STSFN is partitioned in a flexible way. Also, similarity measure together with merging operation between each neighboring fuzzy set are performed in each input dimension to eliminate the redundant fuzzy sets. The consequent parts in STSFN are designed by correlation measure to select only the significant input terms to participate in each rule's consequence and reduce the network parameters. Simulation results in the cart-pole balancing system have shown that with the proposed STSFN building approach, we are able to model the controlled plant with high accuracy and, in addition, can design a stable fuzzy controller with small parameter number.

关键词： Neuro-fuzzy systems stable fuzzy control similarity measure parallel distributed compensation

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Observer-based fuzzy covariance control for discrete nonlinear systems

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 2007年第3期15卷 255-264页

作者： Chang, Wen-Jer Yeh, Yi-Lin Natl Taiwan Ocean Univ Dept Marine Engn Chilung 202 Taiwan

In this paper, the practical covariance control theory is applied to incorporate the concept of variance constrained control for the discrete nonlinear systems using T-S fuzzy models. This paper focuses on the control problem of finding observed-state feedback gains for the discrete fuzzy controllers, which can achieve the common state covariance assignment. Finally, a numerical example will be used to show the simulation results of the present fuzzy control method and usefulness of the proposed approach.

关键词： Takagi-Sugeno fuzzy models parallel distributed compensation observed-state feedback gains and covariance control

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A new fuzzy Lyapunov approach to non-quadratic stabilization of Takagi-Sugeno fuzzy models

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INTERNATIONAL JOURNAL OF APPLIED MATHEMATICS AND COMPUTER SCIENCE 2007年第1期17卷 39-51页

作者： Abdelmalek, Ibtissem Goliea, Noureddine Hadjili, Mohamed Laid Batna Univ Dept Elect Batna 05000 Algeria Oum El Bouaghi Univ Inst Elect Engn Oum El Bouaghi 04000 Algeria UCCLE Ecole Promot Social Brussels 1180 Belgium

In this paper, new non-quadratic stability conditions are derived based on the parallel distributed compensation scheme to stabilize Takagi-Sugeno (T-S) fuzzy systems. We use a non-quadratic Lyapunov function as a fuzzy mixture of multiple quadratic Lyapunov functions. The quadratic Lyapunov functions share the same membership functions with the T-S fuzzy model. The stability conditions we propose are less conservative and stabilize also fuzzy systems which do not admit a quadratic stabilization. The proposed approach is based on two, assumptions. The first one relates to a proportional relation between multiple Lyapunov functions and the second one considers an upper bound to the time derivative of the premise membership functions. To illustrate the advantages of our proposal, four examples are given.

关键词： T-S fuzzy systems non-quadratic stability conditions linear matrix inequalities parallel distributed compensation stabilization

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Modeling, H^∞ control and stability analysis for structural systems using takagi-sugeno fuzzy model

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JOURNAL OF VIBRATION AND CONTROL 2007年第11期13卷 1519-1534页

作者： Chen, Cheng-Wu Yeh, Ken Chiang, Wei-Ling Chen, Chen-Yuan Wu, Deh-Juan Shu Te Univ Dept Logist Management Kaohsiung 82445 Taiwan De Lin Inst Technol Dept Civil Engn Taipei Taiwan Natl Cent Univ Dept Civil Engn Chungli 320 Taiwan Yung Ta Inst Technol & Commerce Dept Management Informat Syst Pingtung 909 Taiwan

This article proposes a design method for producing H-infinity control performance for structural systems using the Tagagi-Sugeno (T-S) fuzzy model. A structural system with a tuned mass damper is modeled using a T-S type fuzzy model. Using the parallel distributed compensation (PDC) scheme, we design a nonlinear fuzzy controller for the tuned mass damper system. A sufficient stability condition for the control system is derived in terms of Lyapunov theory and this control problem is reformulated into solving the linear matrix inequalities (LMI) problem. Finally, the tuned mass damper is designed based on the first modal frequency of the control system and a fuzzy controller to stabilize the structural system is then found using the Matlab LMI toolbox. A simulation example is given to show the feasibility of the proposed fuzzy controller design method.

关键词： H-infinity control linear matrix inequality parallel distributed compensation

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T-S fuzzy model with nonlinear consequence and PDC controller for a class of nonlinear control systems

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APPLIED SOFT COMPUTING 2007年第3期7卷 772-782页

作者： Rajesh, R. Kaimal, M. R. Univ Kerala Dept Comp Sci Trivandrum 695581 Kerala India

In this paper a new Takagi-Sugeno ( T-S) fuzzy model with nonlinear consequence ( TSFMNC) is presented which can approximate a class of smooth nonlinear systems, nonlinear dynamical systems and nonlinear control systems. It is also proved that Takagi-Sugeno fuzzy controller with nonlinear consequence ( TSFCNC) can be used to approximate a class of nonlinear state-feedback controllers using the so-called parallel distributed compensation ( PDC) method. The inverted pendulum problem has been simulated with TSFCNC and compared with Takagi-Sugeno fuzzy controller with linear consequence ( TSFCLC) and the results show that TSFCNC performs better than TSFCLC. A real-life example of dynamic positioning of ship is simulated and the results also show that TSFCNC performs better than TSFCLC. (c) 2006 Elsevier B. V. All rights reserved.

关键词： T-S fuzzy model T-S fuzzy model with nonlinear consequence parallel distributed compensation inverted pendulum fuzzy control feedback control

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Complexity relaxation of the tensor product model transformation for higher dimensional problems

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ASIAN JOURNAL OF CONTROL 2007年第2期9卷 195-200页

作者： Baranyi, Peter Petres, Zoltan Korondi, Peter Yam, Yeung Hashimoto, Hideki Hungarian Acad Sci Comp & Automat Res Inst H-1117 Budapest Hungary Budapest Univ Technol & Econ Dept Telecommun & Media Informat H-1117 Budapest Hungary Budapest Univ Technol & Econ Integrated Intelligent Syst Japanese Hungarian La H-1117 Budapest Hungary Chinese Univ Hong Kong Dept Automat & Comp Aided Engn Shatin Hong Kong Peoples R China Univ Tokyo Inst Ind Sci Tokyo 1538505 Japan

The Tensor Product (TP) model transformation method was proposed recently as an automated gateway between a class of non-linear models and linear matrix inequality based control design. The core of the TP model transformation is the higher order singular value decomposition of a large sized tensor, which requires high computational power that is usually outside of a regular computer capacity in cases of higher dimensionality. This disadvantage restricts the utilization of the TP model transformation to models having smaller dimensionality. The aim of this paper is to propose a computationally relaxed version of the TP model transformation. The paper also presents a 6 dimensional example to show the effectiveness of the modified transformation.

关键词： non-linear control design TP model transformation parallel distributed compensation linear matrix inequality

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A study on PDC of nonlinear systems by T-S fuzzy model with comparing pole placement method and linear quadratic regulator

A study on PDC of nonlinear systems by T-S fuzzy model with ...

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9th WSEAS International Conference on Automatic Control, Modeling and Simulation

作者： Yucelen, Tansel So Illinois Univ Dept Elect & Comp Engn Carbondale IL 62901 USA

ISBN: (纸本)9789608457720

This paper discuss parallel distributed compensation (PDC) of nonlinear systems by Takagi-Sugeno (T-S) fuzzy model, and presents the design of T-S PDC controller in every detail. The purposed approach is designed both using pole placement method (PPM) and linear quadratic regulator (LQR) optimal control method, and also improved in a way to obtain a better system response by using additional membership functions (W) for error with different desired pole locations for each MF for PPM and different design parameters for each MF for LQR. The applicability of this new method is also demonstrated on a detailed simulation.

关键词： parallel distributed compensation takagi-sugeno fuzzy model nonlinear control

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Further studies on LMI-based relaxed stabilization conditions for nonlinear systems in Takagi-Sugeno's form

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AUTOMATICA 2006年第3期42卷 503-508页

作者： Ding, BC Sun, HX Yang, P Hebei Univ Technol Sch Elect & Automat Tianjin 300130 Peoples R China

This paper further studies stabilization of nonlinear systems represented by a Takagi-Sugeno (T-S) discrete fuzzy model. By extending a nonquadratic Lyapunov function and applying a nonparallel distributed compensation (non-PDC) law, a new stabilization conclusion is presented that is a generalization of some previous results in the literature. The new conclusion under a special situation is also suitable for a PDC law, which presents to be more relaxed than some existing results. An example is provided to demonstrate the effectiveness of the new conclusions. (C) 2005 Elsevier Ltd. All rights reserved.

关键词： T-S fuzzy systems parameter-dependent Lyapunov function parallel distributed compensation nonquadratic Lyapunov function

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Stability analysis and design of Takagi-Sugeno fuzzy systems

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INFORMATION SCIENCES 2006年第19期176卷 2817-2845页

作者： Ting, Chen-Sheng Natl Huwei Univ Sci & Technol Dept Elect Engn Huwei 632 Yunlin Taiwan

This work presents stable composite control criteria for multivariable Takagi-Sugeno (T-S) fuzzy systems. On the basis of the linear matrix inequality (LMI) control strategy and parametric optimization, the composite fuzzy control algorithms are derived. Unlike earlier studies of fuzzy-control systems on an LMI framework, this investigation develops a supervisory control approach, such that a fuzzy controller can be synthesized more efficiently. Moreover, a robust control scheme is applied to the T-S fuzzy model with parametric uncertainties. The sufficient conditions are deduced in the form of reduced LMIs and adaptive tuning rules. Finally, numeric simulations are given to validate the proposed approach. (C) 2005 Elsevier Inc. All rights reserved.

关键词： T-S fuzzy system parallel distributed compensation reduced stability conditions

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