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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,...
In this work, we propose a new method approach of designing a repetitive learning controller for a class of unmatched nonlinear systems with both completely unknown virtual control coefficients and unknown time-varying parameters. By incorporating a Nussbaum-type function and backstepping technique, the learning control mechanism is constructed with both differential and difference updating learning...
In this paper, we propose a repetitive learning control (RLC), which deals with nonlinear dynamical systems with non-parametric uncertainties. We address three fundamental issues associated with the new learning control methods: the existence of the solution, learning convergence property and robustification, which are indispensable for the learning control methods to evolve to a new paradigm. Applying...
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