Robust control research on adaptive wavelet neural network identification for tank all-electric gun control system

Complex plants seldom fulfill the conditions required for the direct feedback linearization(DFL) control. Aiming at the mathematic model not known exactly, wavelet neural network(WNN) identifier combined with H
_∞
controller is proposed. WNN is used to approximate the unknown function, novel control and update laws for the weights in the WNN are derived to guarantee that the tracking error is uniformly ultimately bounded (UUB) in the sense of Lyapunov. In addition, a variable structure control and H
_∞
robust compensator is designed to improve the tracking performance. This control method is used to the AC all-electrical tank gun control system, computer simulations show that the tracking accuracy is much better and the control system has strong adaptability and robustness.