Robust Learning Control for a Class of Uncertain Nonlinear Systems

This paper addresses the robust learning control problem for a class of nonlinear systems with structured periodic and unstructured aperiodic uncertainties. A recursive technique is proposed which extends the currently popular backstepping idea to the robust repetitive learning control systems. An learning evaluation function instead of a Lyapunov function is formulated as a guideline for derivation of the control strategy which guarantees the asymptotic stability of the tracking system. The proposed method is validated by simulation of tracking control of two systems with periodic uncertainties, one of which is the well-known van der Pol chaotic oscillator.