The Neural Sliding-Mode Control with Actor-Critic for Nonlinear System

In this paper, we proposed the RBF sliding-mode control (RBFSMC) with actor-critic compensation methods tracking control system is proposed for nonlinear systems. The proposed adaptive control scheme is developed for nonlinear systems with unknown bounded uncertainties. The adaptation laws are derived using a gradient descent, so that both system tracking stability and error convergence can be guaranteed in the closed-loop system. It was used to demonstrate the effectiveness and performance of proposed unite control technique.