Adaptive repetitive learning control for a class of honlinearly parameterized uncertain systems

Combining the pointwise integral mechanism with the feedback linearization approach,we propose a novel adaptive repetitive learning control for higher-order nonlinearly parameterized uncertain systems with time-varying and time-invariant parameters.This control can be applied to an uncertain system with time-varying parameters which are varying rapidly and periodically in an unknown compact set.A differential-difference mixed-type adaptive law and an adaptive repetitive learning control law are configured to ensure the asymptotic convergence of the extended tracking error in the sense of square error-norm.Also,a sufficient condition of the convergence of the method is given by constructing a Lyapunov functional.A simulation example illustrates the feasibility of the proposed method.