Optimized dead-zone control based on a sliding-mode mechanism for a class of unknown nonlinear dynamic systems

The article aims to propose an optimized tracking control for the high-order nonlinear dynamic system with the unknown dead zone of the controller. The dead zone refers to a control with zero behavior in some ranges, hence the system performance will be inevitably affected. Since the dead-zone phenomenon is frequently encountered in control systems, it is very necessary to consider the effect in optimized nonlinear control. Because the high-order system contains multiple system states, the optimized dead-zone control is designed by combining both reinforcement learning (RL) and sliding-mode control. Furthermore, an adaptive compensation of the remainder of the dead-zone function is added into the dead-zone input, then the optimized dead-zone control is yielded from the RL under identifier–actor–critic architecture, where the identifier can remove the requirement of known dynamic function. Finally, the effectiveness of this optimized control is proved by Lyapunov stability analysis and a simulation example.