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Research on servo tracking performance of flight simulator

Because the flight simulator works in different environment for simulating various flight attitudes, the different control algorithm is used for improving the dynamic and static performance. The neural network has good self-learning and self-adaptive, and PID has good robustness, so the adaptive controller based on neural network and PID is used to overcome the coupling inertia and imbalance torque when simulator worked in high speed or large range. And the friction compensation based model reference adaptive control is adopted in low speed status. It has good stability and precision because of using the Stribeck model and Lyapunov stability theory. In order to prove the effectiveness of this controller, experiments have been done.