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In this paper, we propose a new iterative learning control (ILC) scheme, which is devoted to dealing with unknown parameters that are both time varying and iteration varying. In particular, we consider iteration-varying parameters that are generated by a second-order internal model. By incorporating the internal model into the parametric learning law, the ILC scheme can handle more generic nonlinear...
This paper considers the problem of output regulation for nonlinear, possibly non-minimum phase, systems, in the presence of parameter-uncertain exosystems. The proposed result relies upon a framework recently proposed by the authors to deal with the presence of unstable zero dynamics in nonlinear output regulation. An interesting aspect of the theory presented in the paper is given by the fact that...
In this paper we study the global robust output regulation problem for a class of nonlinear systems by output feedback control. The class of systems possesses nonlinear zero-dynamics and, is thus considerably larger than systems studied in the existing literature. As an illustration of our approach, we have applied our approach to the global robust asymptotic tracking problem of the hyperchaotic Lorenz...
Combining the backstepping approach with the pointwise integral mechanism, a novel adaptive repetitive learning control for high-order nonlinear systems with time-varying and time-invariant parameters is proposed. It can be applied to the time-varying parametric uncertainty systems with unknown compact set, non-vanishing, rapid time-varying, periodic and where the prior knowledge is the periodicity...
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