Adaptive repetitive learning control for a class of nonlinearly parameterized uncertain systems
一类非线性参数化系统自适应重复学习控制

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.