Adaptive Wavelet CMAC Tracking Control for Induction Servomotor Drive System
This research proposes an enhanced control system for induction servomotor to obtain the high-precision position tracking based on wavelet cerebellar model articulation controller. The proposed controller combines the wavelet cerebellar articulation model (WCMAC) with compensator controller to have high performance for the system. The superior properties of the WCMAC are its fast learning of the CMAC and wavelet decomposition capability. Therefore, it is used to mimic a model-based controller with exactly unknown parameters. The compensator controller with an estimated boundary error attenuates the effects of disturbances due to time-varying parameters and load acting on the shaft of motor. The online learning rules of WCMAC derived from gradient-descent method and Lyapunov function is used to estimate bound error to ensure the stability of the system. The experimental results for induction servomotor are provided to conclude the effectiveness of the proposed control system even the dynamic model of the induction servomotor is completely unknown.
KeywordsWavelet Cerebellar model articulation controller (CMAC) Uncertain non-linear systems Servomotor Neural network (NN) Wavelet neural network (WNN)
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