Abstract
A class of single-input single-output nonlinear systems which are partially linearizable by state feedback is considered: feedback linearizable systems are included in such a class; no parametrization is required for the uncertainties which are required to satisfy the matching condition. Periodic reference signals with known period T are to be tracked by the output. Provided that known bounding functions on the uncertainties are available, a state feedback iterative learning control is designed which achieves asymptotic output tracking and guarantees bounded closed loop signals from any intial condition. The novel control tecnhique is illustrated for a single-link robot arm.
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