Control of time varying nonlinear system of supporting robot based on neural network

This paper takes mining hydraulic supporting robot as the research object. On the basis of analyzing the dynamic model of the supporting robot and transfer functions of the hydraulic system, system construction and simulation are realized in Simulink. Due to the existence of time-varying parameters in the system, common negative feedback controls are not effective and stable. Therefore, a neural network adaptive PID controller is proposed in this paper, and results are analyzed and compared with traditional PID control. Results show that the neural network adaptive PID controller has fast response speed and very small overshoot. The remarkable feature is that the system shows an excellent adaptive ability to quickly return to the control position after interference impacts, which fully demonstrates the effectiveness of the neural network adaptive PID controller for hydraulic supporting robot time-varying system.