Disturbance Rejection-Based Motion Control of Linear Motors Via Integral Sliding Mode Observer
Zhitai Liu, Zhongjin Zhang, Weiyang Lin, Xinghu Yu, Concettina Buccella, Carlo Cecati
Abstract
To enhance tracking performance and accuracy of linear motor (LM) systems, it is essential to consider the main system uncertainties, such as parameter variations, unmodeled dynamics, and external disturbances, in the control algorithm design. This article proposes a novel motion control scheme based on the utilization of an integral sliding mode observer (SMO). Initially, an indirect adaptive strategy that depends on system states rather than tracking error is designed for parameter estimation, which facilitates the convergence of parameters to their true values. Subsequently, an integral SMO is proposed to estimate the remaining uncertainties, eliminating the requirement of disturbance derivability typical of many existing observers. The finite-time stability of the observer is proven via Lyapunov theory. By combining the two aspects, a composite adaptive controller is designed for LMs. Comparative experiments demonstrate the effectiveness of the proposed controller.