A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure...A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure consists of a slave syst em and a master controller. In the slave system, a recurrent neural network (RNN ) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant, which is used to linearize the slave s ystem. The master controller is a Smith predictor for the linearized slave syste m, which provides prediction and maintains the desirable tracking performance. S tability propriety is guaranteed based on the Lyapunov method. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of th e proposed control strategy.展开更多
文摘A neural network Smith predictive control strategy is proposed to deal with inpu t and feedback time delays in telerobot systems. The delay time is assumed to b e invariant and unknown. The proposed control structure consists of a slave syst em and a master controller. In the slave system, a recurrent neural network (RNN ) with on-line weight tuning algorithm is employed to approximate the dynamics of the time-delay-free nonlinear plant, which is used to linearize the slave s ystem. The master controller is a Smith predictor for the linearized slave syste m, which provides prediction and maintains the desirable tracking performance. S tability propriety is guaranteed based on the Lyapunov method. A simulation of a two-link robotic manipulator is provided to illustrate the effectiveness of th e proposed control strategy.
