An adaptive robust control for linear motors based on composite adaptation

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.