document: Robust wavelet neuro control for linear brushless motors Design , simulation and experimental implementation of a wavelet basis function network learning controller for linear brushless dc motors -LRB- LBDCM -RRB- are considered . Stability robustness with position tracking is the primary concern . The proposed controller deals mainly with external disturbances , e.g. nonlinear friction force and payload variation in motion control of linear motors . It consists of two parts , one is a state feedback component , and the other one is a learning feedback component . The state feedback controller is designed on the basis of a simple linear model , and the learning feedback component is a wavelet neural controller . The attenuation effect of wavelet neural networks on friction force is first verified by the numerical method . The learning effect of wavelet neural networks on friction force is also shown in the numerical results . Then , a wavelet neural network is applied on a real LBDCM to on-line suppress the friction force , which may be variable due to the different lubrication . The effectiveness of the proposed control schemes is demonstrated by simulated and experimental results
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