부산대학교 도서관

In this paper, an adaptive sliding mode neural network(NN) control method is investigated for input delaytractor-trailer system with two degrees of freedom. An uncertain camera-object kinematic tracking error model of atractor car with n trailers with input delay is proposed. Radial basis function neural networks(RBFNNs) are appliedto approximate the unknown functions in the error model. A sliding mode surface with variable structure controlis designed by using backstepping method. Then, an adaptive NN sliding mode control method is thus obtained bycombining Lyapunov-Krasovskii functionals. The controller realizes the global asymptotic trajectories tracking ofthe kinematics system. The stability of the closed-loop system is strictly proved by the Lyapunov theory. Matlabsimulation results demonstrate the feasibility of the proposed method.
In this paper, an adaptive sliding mode neural network(NN) control method is investigated for input delaytractor-trailer system with two degrees of freedom. An uncertain camera-object kinematic tracking error model of atractor car with n trailers with input delay is proposed. Radial basis function neural networks(RBFNNs) are appliedto approximate the unknown functions in the error model. A sliding mode surface with variable structure controlis designed by using backstepping method. Then, an adaptive NN sliding mode control method is thus obtained bycombining Lyapunov-Krasovskii functionals. The controller realizes the global asymptotic trajectories tracking ofthe kinematics system. The stability of the closed-loop system is strictly proved by the Lyapunov theory. Matlabsimulation results demonstrate the feasibility of the proposed method.