This paper proposes an improved wavelet cerebellar model articulation control system (IWCMACS) to control precision positioning of the linear piezoelectric motor (LPM). The proposed system combines the improved wavelet cerebellar articulation model controller (IWCMAC) with the estimated bound compensator controller to obtain high-precision positioning for applications requring accuracy within micrometer or nanometer range. In this research, the momentum and propotional factors are added into learning algorithm to escape from local minima points and speed up convergence of the system. The Lyapunov-Like Lema theory is used to estimate error bound to guarantee the stable of the system. The experimental results for the piezo-priven stage conclude the effectiveness and applicability of the proposed control system for model-free nonlinear.
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