On initial conditions in iterative learning control

Initial conditions, or initial resetting conditions, play a fundamental role in all kinds of iterative learning control methods. In this work we study five different initial conditions, disclose the inherent relationship between each initial condition and corresponding learning convergence (or boundedness) property. The iterative learning control method under consideration is based on Lyapunov theory, which is suitable for plants with time varying parametric uncertainties and local Lipschitz nonlinearities

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