2020
DOI: 10.1155/2020/6195162
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State-Estimator-Based Asynchronous Repetitive Control of Discrete-Time Markovian Switching Systems

Abstract: is paper investigates the problem of asynchronous repetitive control for a class of discrete-time Markovian switching systems. e control goal is to track a given periodic reference without steady-state error. To achieve this goal, an asynchronous repetitive controller that renders the overall closed-loop switched system mean square stable is proposed. To reflect realistic scenarios, the proposed approach does not assume that the system modes are available synchronously to the controller but instead designs a d… Show more

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Cited by 3 publications
(2 citation statements)
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“…Repetitive control [32] is derived from the internal model principle (IMP). e merit of IMP is that, in a stable closedloop control system, the internal control includes thẽ Complexity generator of external controlled signals, so as to realize the adjustment without steady-state error and suppress the periodic interference.…”
Section: Repetitive Control Design Of Single-phase Grid-connected Invertermentioning
confidence: 99%
“…Repetitive control [32] is derived from the internal model principle (IMP). e merit of IMP is that, in a stable closedloop control system, the internal control includes thẽ Complexity generator of external controlled signals, so as to realize the adjustment without steady-state error and suppress the periodic interference.…”
Section: Repetitive Control Design Of Single-phase Grid-connected Invertermentioning
confidence: 99%
“…Markov chain is a class of important stochastic processes with nonaftereffect property [17][18][19][20]. As it is proved that the optimization processes of some classical intelligent algorithms also have this property [21], Markov chain has been widely applied in convergence analysis of many intelligent algorithms [22][23][24][25][26][27][28], e.g., chicken swarm optimization, ant colony algorithm, and genetic algorithm (GA).…”
Section: Introductionmentioning
confidence: 99%