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Wen-Jie Si,Xun-De Dong,Fei-Fei Yang 제어·로봇·시스템학회 2017 International Journal of Control, Automation, and Vol.15 No.5
This paper investigates adaptive tracking control for a more general class of stochastic nonlinear timedelaysystems with unknown input dead-zone. For the considered system, the drift and diffusion terms containtime-delay state variables. In control design, Lyapunov-Krasovskii functionals are employed to handle unknowntime-delay terms. Then, unknown nonlinear functions are approximated by RBF neural networks, and the dynamicsurface control (DSC) technique is utilized to avoid the problem of explosion of complexity. At last, based onthe Lyapunov stability theory, a robust adaptive controller is designed to guarantee that all closed-loop signals arebounded in probability and the tracking error converges to a small neighborhood of the origin. The simulationexample is presented to further show the effectiveness of the proposed approach.