Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feed...Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feedback item was designed based on robust H∞ control theory. The robust state feedback control was utilized to substitute for the equivalent control of the traditional sliding mode control. Thus the robustness of systems sliding mode motion was improved even the initial states were unknown. Furthermore, when the upper bound of disturbance was unknown, the switching control logic was difficult to design, and the drawbacks of chattering in sliding mode control should also be considered simultaneously. To solve the above-mentioned problems, the fuzzy nonlinear method was applied to approximate the switching control term. Based on the Lyapunov stability theory, the parameter adaptive law which could guarantee the system stability was devised. The proposed control strategy could reduce the system chattering effectively. And the control input would not switch sharply, which improved the practicality of the sliding mode controller. Finally, simulation was conducted on system with parameter perturbations and unknown external disturbances. The result shows that the proposed method could enhance the approaching motion performance effectively. The chattering phenomenon is weakened, and the system possesses stronger robustness against parameter perturbations and external disturbances.展开更多
The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial...The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial neurons have the adaptive, parallel processing, selflearning learning, and mare fault-tolerant characteristics. When the artificial neurons are used to control the process, the syste^n will enabled to en-sure that the accused has strong anti-interference capability and ro. bustness.展开更多
基金Project(51476187)supported by the National Natural Science Foundation of China
文摘Aiming at a class of systems under parameter perturbations and unknown external disturbances, a method of fuzzy robust sliding mode control was proposed. Firstly, an integral sliding mode surface containing state feedback item was designed based on robust H∞ control theory. The robust state feedback control was utilized to substitute for the equivalent control of the traditional sliding mode control. Thus the robustness of systems sliding mode motion was improved even the initial states were unknown. Furthermore, when the upper bound of disturbance was unknown, the switching control logic was difficult to design, and the drawbacks of chattering in sliding mode control should also be considered simultaneously. To solve the above-mentioned problems, the fuzzy nonlinear method was applied to approximate the switching control term. Based on the Lyapunov stability theory, the parameter adaptive law which could guarantee the system stability was devised. The proposed control strategy could reduce the system chattering effectively. And the control input would not switch sharply, which improved the practicality of the sliding mode controller. Finally, simulation was conducted on system with parameter perturbations and unknown external disturbances. The result shows that the proposed method could enhance the approaching motion performance effectively. The chattering phenomenon is weakened, and the system possesses stronger robustness against parameter perturbations and external disturbances.
文摘The purpose of this paper is to design a neuron adaptive PID controller based on the theory of intelligent control of the extens- ive research on the characteristics of neuronss, neurons and PID controller. Artificial neurons have the adaptive, parallel processing, selflearning learning, and mare fault-tolerant characteristics. When the artificial neurons are used to control the process, the syste^n will enabled to en-sure that the accused has strong anti-interference capability and ro. bustness.
