Finite‐time Command Filtered Control Combined with Pi‐sigma Fuzzy Neural Network for Hydraulic Control System

This paper considers the problem of the finite‐time command filtered control for hydraulic motor system with external load disturbance using a new hydraulic transformer. Based on the backstepping design method and pi‐sigma fuzzy neural network, a controller is designed. Firstly, the mathematical model of the hydraulic motor system is established, and the command filtered method is employed to solve the problem of the “explosion of complexity” caused by repeated differentiation of the virtual control signals in the backstepping design process, and the error compensation mechanisms are designed to reduce the errors produced by command filters. Then, the finite‐time control approach is adopted to guarantee the tracking errors converge in finite time. In addition, the pi‐sigma fuzzy neural network is used to approximate the nonlinear functions. The designed controller not only solves the strong nonlinear coupling but also enables the system to work efficiently with stronger robustness and faster error convergence. Finally, the effectiveness of the proposed controller is shown by comparisons with the traditional PID and pi‐sigma fuzzy neural networks methods.