Adaptive nonlinear dynamic inversion control for airborne dispenser uncertain system

This An approach to design dynamic inversion controller with adaptive compensator for airborne dispenser has been presented in this paper. The basic control law is designed using the dynamic inversion method, and the online learning neural networks are used to compensate the system errors and external disturbance. The online weights and thresholds tuning rules are deduced according to the tracking error performance functions by Lyapunov method. And it can guarantee the system to keep stable. With the changes of the flying states, the controller can adapt to the fast varying states of the system, and has preferable performance. Simulation results show that limitation of needing accurate mathematical model in dynamic inversion can be released. And the robustness of the whole system is greatly improved.