2008
DOI: 10.1016/j.automatica.2007.12.004
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Adaptive ILC for a class of discrete-time systems with iteration-varying trajectory and random initial condition

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Cited by 274 publications
(177 citation statements)
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“…The novelty of DAILC lies in that it removes the requirements of identical initial condition and iteration-invariant references in traditional ILC [10]. Thus, for (1), the initial condition x.i; 0/ and the desired trajectory r.i; t/ could be varying in the iteration domain, as long as they are bounded.…”
Section: Remarkmentioning
confidence: 99%
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“…The novelty of DAILC lies in that it removes the requirements of identical initial condition and iteration-invariant references in traditional ILC [10]. Thus, for (1), the initial condition x.i; 0/ and the desired trajectory r.i; t/ could be varying in the iteration domain, as long as they are bounded.…”
Section: Remarkmentioning
confidence: 99%
“…The discrete adaptive ILC was first introduced in [10], which utilized the least square algorithm for the parameter estimation along the iteration axis. Consider a first-order discrete-time nonlinear system with only parametric uncertainties as follows:…”
Section: Preliminary Of Adaptive Iterative Learning Controlmentioning
confidence: 99%
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“…Another ILC design was proposed to overcome the uncertainties and disturbances for discrete time nonlinear dynamic system [33] . And an adaptive ILC scheme was presented to deal with timevarying parametric uncertainties for discrete-time system and can achieve point-wise convergence over a finite interval under random initial states and iteration-varying reference trajectory [34] . Yu et al [35] presented ILC for discrete-time systems with unknown control directions under the framework of adaptive ILC.…”
Section: Introductionmentioning
confidence: 99%