Output redefinition based learning control for linear non-minimum phase systems

This paper presents learning control for linear non-minimum phase systems. The desired trajectories are either of finite duration or periodic in time, and the systems undertaken are assumed to perform the tracking tasks repetitively or periodically. Output redefinition is carried out and the zero-dynamics with respect to the redefined output exhibit stable behavior. Both methodologies of iterative learning and repetitive learning are adopted for the controller designs. The stability and asymptotic convergence of the learning systems are established. The effectiveness of the proposed learning control method is demonstrated through numerical simulation results.