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Iterative learning control for MIMO nonlinear systems with arbitrary relative degree and no states measurement



This article presents a state observer based iterative learning control to solve the trajectory tracking problem of a class of time-varying Multi-Input-Multi-Output nonlinear systems with arbitrary relative degree. For this purpose, an asymptotically stable observer is derived for the system under consideration. There after, this observer is integrated with the iterative learning controller by replacing the state in the control law with its estimation yielded by the state observer. Hence, the stability of the whole control (nonlinear system plus controller plus observer) is guaranteed. Simulation result on nonlinear system shows that the trajectory tracking error decreases through the iterations. © 2013 Wiley Periodicals, Inc. Complexity 19: 37–45, 2013