This paper studies the robust fuzzy control for nonlinear chaotic system in the presence of parametric uncertainties. An uncertain Takagi-Sugeno （T-S） fuzzy model is employed for fuzzy modelling of an unknown chaoti...This paper studies the robust fuzzy control for nonlinear chaotic system in the presence of parametric uncertainties. An uncertain Takagi-Sugeno （T-S） fuzzy model is employed for fuzzy modelling of an unknown chaotic system. A sufficient condition formulated in terms of linear matrix inequality （LMI） for the existence of fuzzy controller is obtained. Then the output feedback fuzzy-model-based regulator derived from the LMI solutions can guarantee the stability of the closed-loop overall fuzzy system. The T-S fuzzy model of the chaotic Chen system is developed as an example for illustration. The effectiveness of the proposed controller design methodology is finally demonstrated through computer simulations on the uncertain Chen chaotic system.展开更多
A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl...A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl system, and then a T-S fuzzy model is adopted to approximate the nonlinear system. Since the strong nonlinearities and the external disturbance of the trawling system, a mixed H2/H∞ fuzzy output tracking control strategy via T-S fuzzy system is proposed to regulate the trawl depth to follow a desired trajectory. The trawl depth can be regulated by adjusting the winch velocity automatically and the tracking error can be minimized according to the robust optimal criterion. In order to validate the proposed control method, a computer simulation is conducted. The simulation results indicate that the proposed fuzzy robust optimal controller make the trawl net rapidly follow the desired trajectory under the model uncertainties and the extemal disturbance caused by wave and current.展开更多
A time-delay-dependent wide-area damping controller synthesis approach,based on Jensen’s integral inequality and evolution algorithm,is developed to suppress the adverse effect of time delay on the supplemental contr...A time-delay-dependent wide-area damping controller synthesis approach,based on Jensen’s integral inequality and evolution algorithm,is developed to suppress the adverse effect of time delay on the supplemental control of high-voltage direct current(DC)transmission systems.Initially,the state-space model of hybrid AC/DC systems with time delay is derived and the delay-dependent criteria for the stability of the closed-loop system are provided based on Jensen’s integral inequality.Subsequently,initial solutions are randomly generated to overcome the difficulty of solving the nonlinear matrix inequality.Finally,the time-delay stability upper bound of the controller is optimized using the differential evolution algorithm.In comparison to popular time-delay stable controller design methods,such as the free-weighting-matrix approach,the proposed method based on output feedback realization requires fewer decision variables and is more suitable for large-scale hybrid AC/DC systems.Three examples are introduced to verify the effectiveness of the proposed method.展开更多
A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuz...A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuzzy models. The SNNM is composed of a discrete-time linear dynamic system and a bounded static nonlinear operator. Based on the global asymptotic stability analysis of the SNNMs, linear and nonlinear dynamic output feedback controllers are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities （LMIs） which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based （or fuzzy） discrete-time intelligent systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Three application examples show that the SNNMs not only make controller synthesis of neural-network-based （or fuzzy） discrete-time intelligent systems much easier, but also provide a new approach to the synthesis of the controllers for the other type of nonlinear systems.展开更多
基金Project supported by the National Natural Science Foundation of China （Grant No 60375001）, the Hunan Province Natural Science Foundation, China （Grant No 03JJY3107） and the Scientific Research Funds of Hunan Provincial Education Department, China （Grant No 05B016）.
文摘This paper studies the robust fuzzy control for nonlinear chaotic system in the presence of parametric uncertainties. An uncertain Takagi-Sugeno （T-S） fuzzy model is employed for fuzzy modelling of an unknown chaotic system. A sufficient condition formulated in terms of linear matrix inequality （LMI） for the existence of fuzzy controller is obtained. Then the output feedback fuzzy-model-based regulator derived from the LMI solutions can guarantee the stability of the closed-loop overall fuzzy system. The T-S fuzzy model of the chaotic Chen system is developed as an example for illustration. The effectiveness of the proposed controller design methodology is finally demonstrated through computer simulations on the uncertain Chen chaotic system.
基金supported by the National High-Technology Research and Development Program of China (863 Program,Grant No. 2008AA042703)
文摘A robust optimal output tracking control method for a midwater trawl system is investigated based on T-S fuzzy nonlinear model. A simplified nonlinear mathematical model is first employed to represent a midwater trawl system, and then a T-S fuzzy model is adopted to approximate the nonlinear system. Since the strong nonlinearities and the external disturbance of the trawling system, a mixed H2/H∞ fuzzy output tracking control strategy via T-S fuzzy system is proposed to regulate the trawl depth to follow a desired trajectory. The trawl depth can be regulated by adjusting the winch velocity automatically and the tracking error can be minimized according to the robust optimal criterion. In order to validate the proposed control method, a computer simulation is conducted. The simulation results indicate that the proposed fuzzy robust optimal controller make the trawl net rapidly follow the desired trajectory under the model uncertainties and the extemal disturbance caused by wave and current.
基金supported by the National Key Research and Development Program of China(2016YFB0901001).
文摘A time-delay-dependent wide-area damping controller synthesis approach,based on Jensen’s integral inequality and evolution algorithm,is developed to suppress the adverse effect of time delay on the supplemental control of high-voltage direct current(DC)transmission systems.Initially,the state-space model of hybrid AC/DC systems with time delay is derived and the delay-dependent criteria for the stability of the closed-loop system are provided based on Jensen’s integral inequality.Subsequently,initial solutions are randomly generated to overcome the difficulty of solving the nonlinear matrix inequality.Finally,the time-delay stability upper bound of the controller is optimized using the differential evolution algorithm.In comparison to popular time-delay stable controller design methods,such as the free-weighting-matrix approach,the proposed method based on output feedback realization requires fewer decision variables and is more suitable for large-scale hybrid AC/DC systems.Three examples are introduced to verify the effectiveness of the proposed method.
基金the National Natural Science Foundation of China (Grant No. 60504024)the Zhejiang Provincial Natural Science Foundation of China (Grant No. Y106010)the Specialized Research Fund for the Doctoral Program of Higher Education (SRFDP), China (Grant No. 20060335022)
文摘A novel model, termed the standard neural network model （SNNM）, is advanced to describe some delayed （or non-delayed） discrete-time intelligent systems composed of neural networks and Takagi and Sugeno （T-S） fuzzy models. The SNNM is composed of a discrete-time linear dynamic system and a bounded static nonlinear operator. Based on the global asymptotic stability analysis of the SNNMs, linear and nonlinear dynamic output feedback controllers are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities （LMIs） which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based （or fuzzy） discrete-time intelligent systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Three application examples show that the SNNMs not only make controller synthesis of neural-network-based （or fuzzy） discrete-time intelligent systems much easier, but also provide a new approach to the synthesis of the controllers for the other type of nonlinear systems.
基金supported by the National Natural Science Foundation of China under Grant Nos.61134001,51477146the Applied Basic Research Program of Science and Technology Department of Sichuan Province,China under Grant No.2016JY0085
