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Adaptive Sliding Mode Control Using Radial Basis Function Network for Container Cranes
Ngo Phong Nguyen,Quang Hieu Ngo,Chi Ngon Nguyen 제어로봇시스템학회 2017 제어로봇시스템학회 국제학술대회 논문집 Vol.2017 No.10
An adaptive sliding mode control scheme using radial basis function network (RBFN) for container cranes is investigated in this study. Here, a sliding surface is designed in such a way that sway motion of the payload is incorporated into the trolley dynamics. In addition, to relax the requirement of mathematical model in the design of a traditional sliding mode control (SMC) system, a neural network compensator, obtained by a radial basis function network and an adaption law, which approximates the nonlinear functions in the traditional SMC control law. This control scheme guarantees the asymptotic stability of the closed-loop system based on Lyapunov theory. To illustrate the efficiency of proposed control strategy, simulation results are provided.