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TSK MODEL-BASED FUZZY LOGIC CONTROL OF CARBON DIOXIDE CONCENTRATION IN ROOMS

MECHATRONIC SYSTEMS AND CONTROL 2018年第1期46卷 32-38页

作者： Yordanova, Snejana Tech Univ Sofia Fac Automat Intelligent Control Syst Sofia Bulgaria

The proper carbon dioxide concentration in premises is one of the factors for the indoor climate comfort. Its control via ventilation depends on the quality of the fresh air used and is accompanied by high energy consumption. The plant is nonlinear with no reliable and simple plant model which makes the design of a linear controller difficult. The model-free fuzzy logic controllers (FLCs) successfully tackle such problems. In the present paper, an FLC based on the principle of parallel distributed compensation is designed to enhance the controller's tuning, to further improve the control system performance and energy efficiency and to enable its stability analysis. It uses a Takagi-Sugeno-Kang plant model derived from plant input-output experimental data with the help of genetic algorithms optimization.

关键词： Carbon dioxide concentration genetic algorithms MATLAB (TM) real-time control parallel distributed compensation stability analysis Takagi-Sugeno-Kang modelling

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Improvements on PDC Controller Design for Takagi-Sugeno Fuzzy Systems with State Time-Varying Delays

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IFAC-PapersOnLine 2016年第5期49卷 200-205页

作者： Bourahala, Fayçal Guelton, Kevin Khaber, Farid Manamanni, Noureddine QUERE Laboratory Electrotechnic Department Ferhat Abbas University Setif19000 Algeria CReSTIC EA3804 University of Reims Champagne-Ardenne 51687 Reims Cedex 2 BP1039 France

This paper deals with the controller design for a class of T-S fuzzy model with state time-varying delays. By choosing a convenient augmented Lyapunov-Krasovskii functional and employing a parallel distributed compensation (PDC) control law including both memoryless and delayed state feedback, new delay dependent sufficient conditions for the stabilization of TS fuzzy model with time-varying delay are derived in terms of linear matrix inequalities (LMIs). By taking into account the bounds of the time varying delays and its maximal rate of variation, the proposed LMI-based conditions guarantee the closed-loop asymptotic stability of the considered class of delayed T-S fuzzy systems. Finally, a numerical example is given to illustrate the effectiveness of the proposed controller design methodology and the conservatism improvement regarding to previous results. © 2016

关键词： Time varying control systems Asymptotic stability Controllers Design Feedback control Fuzzy systems Linear matrix inequalities Lyapunov functions State feedback Time delay Delay dependent conditions Delayed state feedback Linear Matrix Inequalities (LMIs) Lyapunov Krasovskii functionals parallel distributed compensation Takagi Sugeno fuzzy models Takagi Sugeno fuzzy systems Time varying delays

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An efficient projection method to stability issues of fuzzy systems

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INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 2005年第2期24卷 75-82页

作者： Huang, Chih-Peng Juang, Yau-Tarng Natl Cent Univ Dept Elect Engn Chungli Taiwan

This paper deals with the stability issues for a class of nonlinear systems described in the Takagi-Sugeno's (T-S) fuzzy model. Based on the alternating projection method, first we propose an efficient projection algorithm for stability analysis. By involving the controller, the design method for the resulting closed-loop system is further investigated. Some numerical examples are given to demonstrate the validity of the proposed methods. The design strategy is verified by the problem of balancing and swing-up of an inverted pendulum on a car.

关键词： nonlinear system fuzzy control T-S fuzzy model stability parallel distributed compensation

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Counterpart of Advanced TS discrete controller without matrix inversion

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IFAC-PapersOnLine 2016年第5期49卷 182-187页

作者： Laurain, Thomas Lauber, Jimmy Palhares, Reinaldo LAMIH UMR/CNRS 8201 University of Valenciennes France Department of Electronics Engineering Federal University of Minas Gerais Belo Horizonte Brazil

This paper aims to present a systematic methodology for designing a Counterpart of an Advanced Takagi-Sugeno (CATS) discrete controller. Advance controllers for nonlinear systems under Takagi-Sugeno representation have been designed for years using efficient control laws such as the non-PDC (parallel distributed compensation) controller. In terms of stabilization, that kind of controllers is a powerful tool which allows outperforming the classical PDC results using non quadratic Lyapunov function. However, in spite of these advantages, this control strategy presents a major inconvenient from real time implementation point of view: the use of a nonlinear matrix inversion at each sample time. In order to solve this problem, our paper presents a CATS controller design methodology to obtain an equivalent to the non-PDC controller without matrix inversion. Through a given procedure associated with a stability analysis, not only the efficiency is proved but also its validity. Finally, some simulation results will emphasize the originality and the usefulness of the proposed CATS controller. © 2016

关键词： Controllers Control theory Digital control systems Discrete time control systems Feedback control Lyapunov functions Real time control Advanced control Discrete time systems Non quadratic lyapunov functions non PDC parallel distributed compensation Real time implementations Systematic methodology Takagi sugeno

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Quadratic design of D-stabilizing Non-PDC controllers for Quasi-LPV/T-S models

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IFAC-PapersOnLine 2015年第26期48卷 164-169页

作者： Cherifi, Abdelmadjid Guelton, Kevin Arcese, Laurent CReSTIC jEM3804 Université de Reims Champagne-Ardenne Moulin de la housse BP1039 Reims Cedex 251687 France

This paper deals with the D-stabilization of quasi-LPV/Takagi-Sugeno (T- S) models. Based on a Quadratic Lyapunov Function (QLF) candidate, basic conditions are presented for the design of D-stabilizing parallel distributed compensation (PDC) control, i.e with LMI region constraints. Then, relaxed quadratic LMI conditions are proposed in order to design a D-stabilizing non-PDC controller. The proposed results are illustrated in simulation through an academic example, then through the benchmark of the stabilization of a flexible robot with single joint. © 2015 IPAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Controllers Feedback control Linear matrix inequalities Lyapunov functions Modal analysis Stabilization Basic conditions D stability D stabilization LPV models non PDC parallel distributed compensation Quadratic lyapunov function Takagi Sugeno models

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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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Passive Fuzzy Controller Design via Observer Feedback for Stochastic Takagi-Sugeno Fuzzy Models with Multiplicative Noises

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2011年第3期9卷 550-557页

作者： Chang, Wen-Jer Liu, Liang-Zhi Ku, Cheung-Chieh Natl Taiwan Ocean Univ Dept Marine Engn Keelung 202 Taiwan Natl Taiwan Ocean Univ Dept Elect Engn Keelung 20224 Taiwan

This paper investigates the fuzzy control problem of a class of nonlinear continuous-time stochastic systems with achieving the passivity performance. A model-based observer feedback fuzzy control utilizing the concept of so-called parallel distributed compensation (PDC) is employed to stabilize the class of nonlinear stochastic systems that are represented by the Takagi-Sugeno (T-S) fuzzy models. Based on the Lyapunov criteria, the Linear Matrix Inequality (LMI) technique is used to synthesize the observer feedback fuzzy controller design such that the closed-loop system satisfies stability and passivity constraints, simultaneously. Finally, a numerical example is given to demonstrate the applicability and effectiveness of the proposed design method.

关键词： Observer feedback fuzzy control parallel distributed compensation passivity property Takagi-Sugeno fuzzy model

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Fuzzy logic approach to coupled level control

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SYSTEMS SCIENCE & CONTROL ENGINEERING 2016年第1期4卷 215-222页

作者： Yordanova, Snejana Tech Univ Sofia Fac Automat Sofia Bulgaria

Liquid level in coupled tanks is difficult to control by classical techniques because the plant is nonlinear, multivariable, often with no self-regulation and no model. Fuzzy logic (FL) enables a successful stable and robust control by simple means and a model-free design. This paper suggests a procedure for the design of two-variable FL controllers (FLCs) for the levels in a laboratory coupled-tank system. First a model-free two-variable Mamdani FLC is empirically developed and applied for real-time levels control. The plant input and output experimental data are then used for derivation via genetic algorithms optimization of a Takagi-Sugeno-Kang (TSK) plant model needed for FLC improvement. The TSK model is validated on a different set of experimental data and used in designing of two-variable linear proportional-plus-integral (PI) controller and parallel distributed compensation with local linear PI controllers. The performance of the systems with the designed controllers is compared in real-time levels control.

关键词： Coupled tanks parallel distributed compensation real-time level control two-variable fuzzy logic controller TSK plant modelling

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On the Fuzzy Model Predictive Control of Interconnected Nonlinear Systems

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2017年第7期42卷 2759-2776页

作者： Dalhoumi, Latifa Chtourou, Mohamed Djemel, Mohamed Univ Sfax Natl Sch Engn Sfax Control & Energy Management Lab PB 1173 Sfax 3083 Tunisia

The present paper deals with a new fuzzy strategy of model-based predictive control for nonlinear systems that are assumed to be interconnected (INS). Each subsystem, supposed nonlinear (NSS), is represented by a Takagi-Sugeno fuzzy model where fuzzy rule conclusions are linear state space models. The proposed control strategy consists of the association of a set of subcriterion. The defined criteria have to be optimized for all NSSs that formulate the considered INS. In fact, using parallel distributed compensation principal, a fuzzy predictive controller is developed where fuzzy rule conclusions are local control laws, where each one is the result of the optimization of the corresponding subcriteria. The global control law applied for each NSS is the fusion of local control ones. The feasibility and the performance of the proposed strategy is shown through two examples.

关键词： Interconnected nonlinear systems Nonlinear subsystems Model predictive control Fuzzy model predictive control Takagi-Sugeno fuzzy models parallel distributed compensation

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Ultimate Boundedness Control for Uncertain Nonlinear Impulsive Switched Systems: A Fuzzy Approach Based on a Complete Takagi-Sugeno Structure

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JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS 2020年第2期31卷 271-282页

作者： Ghalehnoie, Mohsen Shahrood Univ Technol Dept Elect Engn Shahrood *** Iran

This paper deals with the ultimate boundedness control of nonlinear impulsive switched systems, which ensures that the state trajectories ultimately converge to a sufficient small region containing the origin. Given a general model, we first propose novel stability criteria that do not need to be satisfied on the entire space and include a condition to guarantee the remaining of trajectories within the ultimate bound, even though the impulse size is not zero at the origin or is not vanishing near the origin. Applying these criteria to a closed-loop system leads to a set of matrix inequalities that may be infeasible when the subsystems are highly nonlinear. Therefore, we redevelop them for an impulsive switched system represented by Takagi-Sugeno (T-S) fuzzy structure with nonlinear consequent parts. Since this structure has fewer rules than the traditional T-S models with linear consequent parts, the number of established stabilization matrix inequalities is sharply reduced. We then derive an optimization problem with linear and bilinear constraints to achieve a fuzzy controller that guarantees convergence to the smallest ultimate bound as well as practical control issues. Finally, a numerical example and a practical-motivated example are given to demonstrate the applicability of the proposed approach.

关键词： Impulsive switched systems Local sector nonlinearity Nonlinear control parallel distributed compensation Takagi-Sugeno fuzzy model

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