Adaptive prescribed performance asymptotic tracking control for nonlinear systems with time-varying parameters

This study considers the problem of prescribed performance adaptive asymptotic tracking control for a class of nonlinear systems with time-varying parameters. A novel adaptive tracking control scheme is constructed by using the congelation of variables method and the backstepping method, in which the adaptive laws are designed to approximate the averages of the time-varying parameters. The normalized function transformation is introduced to achieve the prescribed performance control; meanwhile, the issue of the explosion of complexity is avoided by using the command filtered technique. In addition, the proposed approach guarantees that all signals of the closed-loop system are bounded and the tracking error can asymptotically converge to zero, while staying within prescribed boundaries. Finally, the effectiveness of the control strategy is shown by two simulation examples.