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Fuzzy logic approach to coupled level control

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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Quadratic Design of Robust Controllers for Uncertain T-S Models with D-Stability Contraints

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IFAC-PapersOnLine 2016年第5期49卷 19-24页

作者： Cherifi, Abdelmadjid Guelton, Kevin Arcese, Laurent CReSTIC EA3804 - Université de Reims Champagne-Ardenne Moulin de la housse BP1039 51687 Reims cedex 2 France

This paper deals with the robust D-stabilization of uncertain Takagi-Sugeno (T-S) fuzzy systems. New Linear Matrix Linearity (LMI) conditions are proposed for the design of non parallel-distributed-compensation (non-PDC) controllers with D-stability constraints, i.e forcing the poles of each linear polytopes of the closed-loop T-S plant with model uncertainties to belong in a prescribed LMI region. The LMI conditions are obtained through the use of a quadratic Lyapunov function candidate and relaxed by the introduction of free weighting matrices. To illustrate the effectiveness of the proposed approach, the D-stabilization of an academic example of a fourth-order uncertain T-S model is provided in simulation. © 2016

关键词： Linear matrix inequalities Chaotic systems Controllers Feedback control Lyapunov functions Robust control Stabilization Uncertainty analysis D stability Design of robust controllers Free weighting matrices non PDC parallel distributed compensation Quadratic lyapunov function T S fuzzy models Takagi Sugeno fuzzy systems

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Tracking controller design of a sideslip angle and yaw rate for electrical vehicle bicycle model

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IFAC-PapersOnLine 2016年第5期49卷 169-174页

作者： Frendi, S. Mellah, R. Seddiki, L. Akdag, H. L2CSP University Mouloud Mammeri of Tizi-Ouzou Algeria LIASD Paris 8 University 2 Rue de la Liberté - 93526 Saint-Denis Cedex 02 France

To improve road safety, this paper proposes a fuzzy control strategy of the rear steering angle and yaw moment of an Electric Vehicle (EV). A H∞control structure based on the Takagi-Sugeno (TS) multi-models is proposed to track the desired trajectories and to attenuate external disturbances. First, a bicycle model is introduced with a reference model that are used to construct the augmented system. Next, fuzzy TS multi-models are used to represent the Linear Parameters Varying (LPV) system. Then, based on these models a parallel distributed compensation (PDC) control law is designed. Finally, the stability analysis is treated as a convex optimization problem formulated in Linear Matrix Inequality (LMI) formalism. Finally, the simulation results of the proposed control strategy illustrate the efficiency of the proposed approach. © 2016

关键词： Electric machine control Control theory Controllers Convex optimization Electric vehicles Feedback control Fuzzy control Linear matrix inequalities Motor transportation Convex optimization problems External disturbances Fuzzy control strategy LMI formalism LPV systems Multi model parallel distributed compensation Tracking trajectory

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A Disturbance Rejection Fuzzy Robust parallel distributed Compensator Design for Underactuated Robot System 14

A Disturbance Rejection Fuzzy Robust Parallel Distributed Co...

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14th International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Rajabpour, Leila Barzegar, Alireza Su, Rong Nanayang Technol Univ Sch Elect & Elect Engn Singapore Singapore

ISBN: (纸本)9781509035496

In this paper we present a robust controller based on Takagi-Sugeno (T-S) fuzzy model. First, we obtain the nonlinear state equation of the underactuated robot systems by linearization, then, the parallel distributed compensation scheme (PDC) is applied to design the controller. Simulation results show the robustness of the pendubot control system against the disturbance.

关键词： T-S fuzzy model linear matrix inequality (LMI) underactuated robot parallel distributed compensation robust controller

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Stabilization of single machine infinite bus by optimal fuzzy control 17

Stabilization of single machine infinite bus by optimal fuzz...

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17th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA)

作者： Rim, Ben Salah Omar, Kahouli Hsan, Hadj Abdallah Natl Engn Sch Sfax Control & Energy Management Lab Dept Elect Engn Sfax Tunisia

ISBN: (纸本)9781509034079

this paper presents the methodology for design Takagi-Sugeno controller to mono-machine power system in order to study transient stability under severe perturbation. The nonlinear system is modeled and transformed on linear fuzzy model. Then, the design of Takagi-Sugeno regulator is derived from optimal control. The feedback gains are determined by linear quadratic instruction. This Technique is applied on test system. Important issues of transient stability and design are remarked.

关键词： Transient stability Takagi-Sugeno controller parallel distributed compensation linear matrix inequalities optimal control power system

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ESTIMATED STATE FEEDBACK FUZZY CONTROL FOR PASSIVE DISCRETE TIME-DELAY MULTIPLICATIVE NOISED PENDULUM SYSTEMS

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JOURNAL OF MARINE SCIENCE AND TECHNOLOGY-TAIWAN 2015年第1期23卷 98-108页

作者： Chang, Wen-Jer Lin, Chun-Hung Ku, Cheung-Chieh Natl Taiwan Ocean Univ Dept Marine Engn Keelung Taiwan

This paper develops a fuzzy controller design method via estimated state feedback scheme for discrete-time nonlinear stochastic time-delay systems which are presented by Takagi Sugeno fuzzy model with multiplicative noises. The proposed design method is accomplished by the concept of parallel distributed compensation. Using the Lyapunov-Krasovskii function and passivity theory, the stability conditions are derived to guarantee the stability and attenuation performance. An algorithm is proposed in this paper to solve the derived stability conditions that belong to non-strict linear matrix inequality problems. Moreover, the discrete Jensen inequality and free-weighting matrix technique are employed to decrease the conservatism of the proposed design method Finally, the control of a nonlinear time-delay pendulum system is provided to illustrate the effectiveness and usefulness of the proposed fuzzy control method.

关键词： T-S fuzzy model multiplicative noise parallel distributed compensation passivity theory discrete Jensen inequality

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More Relaxed Non-quadratic Stabilization Conditions for TS Fuzzy Control Systems using LMI and GEVP

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INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS 2015年第4期13卷 995-1002页

作者： Vafamand, Navid Sadeghi, Mokhtar Sha Shiraz Univ Technol Elect & Elect Engn Fac Dept Control Engn Shiraz Fars Province Iran

In this paper, a new systematic approach is presented to further decrease the conservativeness in stability analysis condition and controller design. Non-quadratic Lyapunov function is utilized to derive stability conditions in terms of linear matrix inequalities. Also, the control problem is formulated in a generalized eigenvalue problem. Considering the concept of decay rate and control input constraint, a new systematic procedure is proposed to calculate a maximum bound for the upper bounds of the time derivatives of the membership functions. Moreover, some slack matrices are introduced that help to reduce conservativeness. The number of inequalities is few compared to the existing results in literature, which helps the feasibility in the case of large number of fuzzy rules. Simulation examples and comparison results demonstrate the merits of this method.

关键词： Linear matrix inequality parallel distributed compensation relaxed conservativeness stability conditions Takagi-Sugeno fuzzy model

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Mixed sliding mode fuzzy control for discrete-time non-linear stochastic systems subject to variance and passivity constraints

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IET CONTROL THEORY AND APPLICATIONS 2015年第16期9卷 2369-2376页

作者： Chang, Wen-Jer Chen, Po-Hsun Ku, Cheung-Chieh Natl Taiwan Ocean Univ Dept Marine Engn Keelung 202 Taiwan

In this study, a novel multi-objective sliding mode fuzzy control technique is presented for a class of discrete-time non-linear stochastic systems that are represented by Takagi-Sugeno (T-S) fuzzy models. Subject to variance and passivity constraints, parallel distributed compensation based sliding mode fuzzy control approach is investigated for the discrete-time T-S fuzzy models. Combining Lyapunov theory, passivity theory and covariance theory, sufficient conditions are derived to satisfy stability, passivity and variance constraints. The iterative linear matrix inequality algorithm is employed in this study to solve these sufficient conditions. The contribution of this study is to develop a novel sliding mode fuzzy control method such that the closed-loop discrete-time non-linear stochastic system achieves passivity constraint and individual state variance constraints, simultaneously. At last, the simulations of controlling a discrete-time non-linear ship steering system are given in a numerical example to demonstrate the effectiveness and usefulness of proposed sliding mode fuzzy control methodology.

关键词： stochastic systems nonlinear control systems discrete time systems fuzzy control variable structure systems Lyapunov methods covariance analysis stability iterative methods linear matrix inequalities closed loop systems mixed sliding mode fuzzy control passivity constraints multiobjective control technique discrete-time nonlinear stochastic systems Takagi-Sugeno models T-S models parallel distributed compensation Lyapunov theory stability covariance theory iterative linear matrix inequality algorithm LMI closed-loop system state variance constraints ship steering system

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Fuzzy dynamic output-feedback control of non-linear networked discrete-time system with missing measurements

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IET CONTROL THEORY AND APPLICATIONS 2015年第3期9卷 327-335页

作者： Li, Hongyi Wu, Chengwei Feng, Zhiguang Bohai Univ Coll Engn Jinzhou 121013 Liaoning Peoples R China Bohai Univ Coll Informat Sci & Technol Jinzhou 121013 Liaoning Peoples R China

This article studies the problem of H dynamic output-feedback control of non-linear networked discrete-time systems with data packet dropouts. Specifically, the data missing happens randomly from the sensor to the controller and the controller to the actuator. A sequence of independent variables obeying the Bernoulli random binary distribution is introduced to account for the measurement missing. The Takagi-Sugeno fuzzy model is used to describe the non-linear plant. In addition, the strategy of parallel distributed compensation is adopted to design the fuzzy dynamic output-feedback controller. Here, attention is focused on obtaining the sufficient conditions to guarantee the closed-loop system to be stochastically stable as well as the prescribed H performance. An approach based on fuzzy Lyapunov function is developed to solve it. To tackle the non-convex problem, the cone-complementarity linearisation procedure is adopted. Finally, a numerical example is employed to show the usefulness of the proposed result.

关键词： fuzzy control feedback control system synthesis nonlinear control systems networked control systems distributed parameter systems discrete time systems H control compensation closed loop systems asymptotic stability Lyapunov methods concave programming linearisation techniques fuzzy dynamic output-feedback controller design nonlinear networked discrete-time system data missing measurements H dynamic output-feedback control problem data packet dropouts independent variables Bernoulli random binary distributed Takagi-Sugeno fuzzy model nonlinear plant parallel distributed compensation closed-loop system asymptotic stability fuzzy Lyapunov function nonconvex problem cone-complementarity linearisation procedure

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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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