An adaptive robust control for linear motors based on composite adaptation
基于复合自适应律的直线电机自适应鲁棒控制

The adaptive robust control(ARC) not only reduces the influence of parametric uncertainties and disturbance to the system, but also provides a good performance in output tracking. However, the parameter estimates of traditional ARC do not give good approximations to the true values of the corresponding parameters. To achieve a high performance control and accurate parameter estimation, we propose a novel composite-adaptation-based adaptive robust control method(CAARC). This method combines the information of output tracking error with the parameter estimate error in constructing the adaptation law, which gives a better result in parameter estimation than that from the traditional ARC. The close-loop stability and the convergence of parameter estimates are also proved. It has been shown by analysis that CAARC has a better tracking performance than the traditional ARC. Finally, the effectiveness of the proposed method is demonstrated by simulation.