Abstract
A novel self-organizing adaptive wavelet cerebellar model articulation controller backstepping (SOWCB) control is proposed, aiming at some nonlinear and uncertain factors that caused difficulties in controlling the AC servo system. This controller consists of self-organizing wavelet cerebellar model articulation controller (CMAC) and robust compensator. It absorbs fast learning and precise approaching advantage of self-organizing wavelet CMAC to mimic a backstepping controller, and then robust compensator is added to inhibit influence of the uncertainties on system performance effectively and realize high accuracy position tracking for AC servo system. Moreover, the stability of the control system can be guaranteed by using Lyapunov method. The results of the simulation and the prototype test prove that the proposed approach can improve the steady state performance and control accuracy and possess a strong robustness to both parameter perturbation and load disturbance.
Highlights
With the advancement of technology, AC servo systems have become more and more widely utilized
Zhou and Zhu [1, 2] use nonlinear backstepping control method that can effectively realize the nonlinear decoupling of AC servo system and ensure the accuracy of the motor servo control at the same time; the algorithm requires accurate mathematical model of controlled object that is known; if the controlled object has uncertain amount of interference, the algorithm will not be able to achieve good control effect
The structure diagram of an AC servo system is presented in Figure 1, where the magnetic powder brake is the purpose of the change of load simulation system
Summary
With the advancement of technology, AC servo systems have become more and more widely utilized. Zhou and Zhu [1, 2] use nonlinear backstepping control method that can effectively realize the nonlinear decoupling of AC servo system and ensure the accuracy of the motor servo control at the same time; the algorithm requires accurate mathematical model of controlled object that is known; if the controlled object has uncertain amount of interference, the algorithm will not be able to achieve good control effect Su and He [3, 4] for uncertain nonlinear system using backstepping control and learning control method of combining designed several adaptive learning controllers; the literature [5,6,7] uses wavelet neural network approach in the use of complex nonlinear term backstepping process; the control structure has been simplified and improved learning ability. Experiments of AC servo system and the prototype test can prove the effectiveness of the proposed method
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
