An adaptive control mechanism for improving the loading precision of aircraft hydraulic servo load simulator

During the ground test of aircraft hydraulic steering gears, the high precision simulation of the load experienced by steering engine in aircraft flying process is of critical importance. To tackle with the control system non-linearity, parameter timevarying properties as well as the excessive force caused by the position perturbation, a parallel CMAC and PID based control algorithm is proposed. Specifically, a nonlinear mathematical model for the system is established first, and then, the PID controller is utilized to realize feedback control, and meanwhile, provide the mentor signals to the CMAC neural network. While the CMAC neural network itself is a feed-forward control system that can be utilized to reduce the interference caused by the excess forces and time-varying parameters, which thus realize a nonlinear approximation process. Simulations are conducted to verify the effectiveness of the proposed algorithm, and results show that the proposed algorithm is able to suppress the excess forces to be around 22.5% that of the conventional method. Compared to the existing methods, such a proposed algorithm is of higher tracking precision and anti-interference capability and more robust, and thus could improve the system performances and provide references to the practical application of the system.