Adaptive Control of Flexible Manipulators Based on Neural Network and Backstepping
Flexible manipulators system is a kind of high-order nonlinear system with strong coupling.The dynamic model usual-ly contains structural uncertainties.Aiming at the complex problem of trajectory tracking control caused by structural uncertain-ty,an adaptive backstepping control based on RBF neural network is proposed.Firstly,the known information part and unknown information part of the system are separated;Then,the trajectory tracking controller of the system is designed by backstepping;Next,the RBF neural network is used to approximate the unknown information and virtual control derivative in the system mod-el,an adaptive control law based on RBF neural network is designed and the stability of the system is proved by Lyapunov theory.Finally,the results show that the trajectory tracking performance of this method is better,and the tracking accuracy is improved by more than 80%,which proves the effectiveness of the control method by numerical simulation and comparison with the tradi-tional PDcontrol.
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