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Journal of systems science & Complexity 2022年第3期35卷 860-887页

作者： LIU Yuanyuan ZHANG Yutong MA Yuechao school of science Yanshan UniversityQinhuangdao 066004China

the paper analyzes finite-time H_(∞)sampled-data reliability control for nonlinear continuous time Markovian jump systems with randomly occurring uncertainty on account of t-s fuzzy model.In particular,the transition rates of the Markovian jump systems have both the upper bound and lower bound.Meanwhile,a new Lyapunov-Krasovskii functional(LKF)is considered,which fully captures the available characteristics of real sampling period,and a sampled-data controller with nonlinear actuator failures is designed.Based on the integral inequality technique,some less conservative conditions are proposed such that the stochastic fuzzy system is reliable in the sense,which satisfies finite-time bounded and certain H_(∞)performance levelγ.Additionally,some numerical examples can illustrate the effectiveness of the results.

关键词： Actuator fault control finite-time H_(∞)bounded Markovian jump system sampled-data control t-s fuzzy model

Generating Li-Yorke chaos in a stable continuous-time t-s fuzzy model via time-delay feedback control

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Chinese Physics B 2010年第7期19卷 141-149页

作者：孙秋野张化光赵琰 College of Information science and Engineering Northeastern University Key Laboratory of Integrated Automation of Process Industry Ministry of EducationNortheastern University Department of Automatic Control Engineering Shenyang Institute of Engineering

this paper investigates the chaotification problem of a stable continuous-time t s fuzzy system. A simple nonlinear state time-delay feedback controller is designed by parallel distributed compensation technique. then, the asymptotically approximate relationship between the controlled continuous-time t-s fuzzy system with time-delay and a discrete-time t-s fuzzy system is established. Based on the discrete-time t-s fuzzy system, it proves that the chaos in the discrete- time t-s fuzzy system satisfies the Li-Yorke definition by choosing appropriate controller parameters via the revised Marotto theorem. Finally, the effectiveness of the proposed chaotic anticontrol method is verified by a practical example.

关键词： chaotification t-s fuzzy model time-delay feedback Li Yorke chaos 1

Constrained predictive control based on t-s fuzzy model for nonlinear systems

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Journal of systems Engineering and Electronics 2007年第1期18卷 95-100页

作者： su Baili Chen Zengqiang Yuan Zhuzhi Dept. of Automation Nankai Univ. Tianjin 300071 P. R. China Qufu Normal Univ. Qufu 273165 P. R. China

A constrained generalized predictive control （GPC） algorithm based on the t-s fuzzy model is presented for the nonlinear system. First, a takagi-sugeno （t-s） fuzzy model based on the fuzzy cluster algorithm and the orthogonalleast square method is constructed to approach the nonlinear system. since its consequence is linear, it can divide the nonlinear system into a number of linear or nearly linear subsystems. For this t-s fuzzy model, a GPC algorithm with input constraints is presented. this strategy takes into account all the constraints of the control signal and its increment, and does not require the calculation of the Diophantine equations. so it needs only a small computer memory and the computational speed is high. the simulation results show a good performance for the nonlinear systems.

关键词： Generalized predictive control （GPC） Nonlinear system t-s fuzzy model Input constraint fuzzy cluster

Predictive Control Algorithm for Urban Rail train Brake Control system Based on t-s fuzzy model

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Computers, Materials & Continua 2020年第9期64卷 1859-1867页

作者： Xiaokan Wang Qiong Wang shuang Liang school of Electronic and Information Engineering Beijing Jiaotong UniversityBeijing100044China Henan Mechanical and Electrical Vocational College Xinzheng451191China University of Florence Via Sandro PertiniFirenze50041Italy

Urban rail transit has the advantages of large traffic capacity,high punctuality and zero congestion,and it plays an increasingly important role in modern urban life.Braking system is an important system of urban rail train,which directly affects the performance and safety of train operation and impacts passenger comfort.the braking performance of urban rail trains is directly related to the improvement of train speed and transportation capacity.Also,urban rail transit has the characteristics of high speed,short station distance,frequent starting,and frequent braking.this makes the braking control system constitute a time-varying,time-delaying and nonlinear control system,especially the braking force changes directly disturb the parking accuracy and comfort.to solve these issues,a predictive control algorithm based on t-s fuzzy model was proposed and applied to the train braking control system.Compared with the traditional PID control algorithm and self-adaptive fuzzy PID control algorithm,the braking capacity of urban rail train was improved by 8%.the algorithm can achieve fast and accurate synchronous braking,thereby overcoming the dynamic influence of the uncertainty,hysteresis and time-varying factors of the controlled object.Finally,the desired control objectives can be achieved,the system will have superior robustness,stability and comfort.

关键词： Predictive control t-s fuzzy model urban rail train algorithm

statistic PID tracking Control for Non-Gaussian stochastic systems Based on t-s fuzzy model

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International Journal of Automation and computing 2009年第1期6卷 81-87页

作者： Yang Yi Hong shen Lei Gu school of Automation Southeast University Nanjing 210096 PRC school of Economics and Management Southeast University Nanjing 210096 PRC school of Instrumentation and Opto-Eiectronics Engineering Beihang University Beijing 100083 PRC

A new robust proportional-integral-derivative （PID） tracking control framework is considered for stochastic systems with non-Gaussian variable based on B-spline neural network approximation and t-s fuzzy model identification. the tracked object is the statistical information of a given target probability density function （PDF）, rather than a deterministic signal. Following B-spline approximation to the integrated performance function, the concerned problem is transferred into the tracking of given weights. Different from the previous related works, the time delay t-s fuzzy models with the exogenous disturbances are applied to identify the nonlinear weighting dynamics. Meanwhile, the generalized PID controller structure and the improved convex linear matrix inequalities （LMI） algorithms are proposed to fulfil the tracking problem. Furthermore, in order to enhance the robust performance, the peak-to-peak measure index is applied to optimize the tracking performance. simulations are given to demonstrate the efficiency of the proposed approach.

关键词： Non-Gaussian systems probability density function statistic tracking control t-s fuzzy model proportional-integralderivative control.

t-s fuzzy model-Based Depth Control of Underwater Vehicles

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Journal of shanghai Jiaotong university(science) 2020年第3期25卷 315-324页

作者：钱缘冯正平毕安元刘伟奇 school of Naval Architecture Ocean and Civil EngineeringShanghai Jiao Tong UniversityShanghai 200240China Collaborative Innovation Center for Advanced ship and Deep-sea Exploration Shanghai Jiao Tong UniversityShanghai 200240China

A t-s fuzzy model with two rules is established to exactly describe the nonlinear uncertain heave dynamics of underwater vehicles with bounded heave speed.A single linear-matrix-inequality-based (LMI-based) state feedback controller is then synthesized to guarantee the global stability of the depth control system.simulation results verify the effectiveness of the proposed approach in comparison with linear-quadratic regulator (LQR) method.Nonlinear disturbance observer is appended to the system when the underwater vehicles are affected by the gravity-buoyancy imbalance.the two-stage control method is effective to stabilize an uncertain system with both parameter uncertainties and external disturbances.

关键词： underwater vehicles uncertainty depth control t-s fuzzy model

Controller design of uncertain nonlinear systems based on t-s fuzzy model

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控制理论与应用（英文版） 2009年第2期7卷 139-143页

作者： songtao ZHANG shizhen BAI school of Management Harbin University of Commerce Harbin Heilongjiang 150076 China

A robust control for uncertain nonlinear systems based on t-s fuzzy model is discussed in this paper. First, a t-s fuzzy system is adopted to model the uncertain nonlinear systems. then, for the system with input variables adopting standard fuzzy partitions, the efficient maximal overlapped-rules group （EMORG） is presented, and a new sufficient condition to check the stability of t-s fuzzy system with uncertainty is derived, which is expressed in terms of Linear Matrix Inequalities. the derived stability condition, which only requires a local common positive definite matrix in each EMORG, can reduce the conservatism and difficulty in existing stability conditions. Finally, a simulation example shows the proposed approach is effective.

关键词： Controller design Uncertain nonlinear systems t-s fuzzy model

Predictive functional control based on fuzzy t-s model for HVAC systems temperature control

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控制理论与应用（英文版） 2007年第1期5卷 94-98页

作者： Hongli LU Lei JIA shulan KONG Zhaosheng ZHANG school of Control science and Engineering Shandong University Jinan Shandong 250061 China school of Mathematics science Qufu Normal University Qufu Shandong 273165 China

In heating, ventilating and air-conditioning （HVAC） systems, there exist severe nonlinearity, time-varying nature, disturbances and uncertainties. A new predictive functional control based on takagi-sugeno （t-s） fuzzy model was proposed to control HVAC systems. the t-s fuzzy model of stabilized controlled process was obtained using the least squares method, then on the basis of global linear predictive model from t-s fuzzy model, the process was controlled by the predictive functional controller. Especially the feedback regulation part was developed to compensate uncertainties of fuzzy predictive model. Finally simulation test results in HVAC systems control applications showed that the proposed fuzzy model predictive functional control improves tracking effect and robustness. Compared with the conventional PID controller, this control strategy has the advantages of less overshoot and shorter setting time, etc.

关键词： t-s fuzzy model Predictive functional control Least squares method HVAC systems

Impulsive Control for t-s fuzzy model Based Chaotic systems Consisting of Van der Pol Oscillators Coupled to Linear Oscillators

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Journal of Electronic science and technology of China 2007年第4期5卷 348-351页

作者： Qi-shui Zhong Jing-Fu Bao Zhu-sheng Kang school of Electronic Engineering University of Electronic Science and Technology of China （UESTC） Chengdu 610054 China

this paper proposes an impulsive control scheme for chaotic systems consisting of Van der Pol oscillators coupled to linear oscillators （VDPL） based on their takagi-sugeno （t-s） fuzzy models. A t-s fuzzy model is utilized to represent the chaotic VDPL system. By using comparison method, a general asymptotical stability criterion by means of linear matrix inequality （LMI） is derived for the t-s fuzzy model of VDPL system with impulsive effects. the simulation results demonstrate the effectiveness of the proposed scheme.

关键词： Impulsive control t-s fuzzy model chaos Van der Pol oscillator.

Nonlinear model Predictive Control based on t-s fuzzy model for a PWR Nuclear Power Plant

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Nonlinear Model Predictive Control based on T-S Fuzzy model ...