Neuroadaptive control for pneumatic cylinder servo systems with input saturation and time-varying constraints

In this paper, an anti-windup barrier neuroadaptive control approach is proposed to solve the trajectory tracking problem for pneumatic cylinder servo systems with time-varying constraints and input saturation. Time-varying barrier Lyapunov functions are constructed for controller design to restrict the displacement error and velocity error within their respective preset time-varying boundaries, thereby ensuring the specified tracking performance during control process. An improved anti-wind strategy is developed to achieve saturation compensation. Two finite-time differentiators are constructed to estimate the derivatives of virtual control signals for lowering the design difficulty. Adaptive ELM neural network is established for disturbance rejection and uncertainty approximation. The comparative simulation results verify the effectiveness of the proposed anti-windup neuroadaptive control scheme.