2022
DOI: 10.1109/tcyb.2021.3062672
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Asynchronous Control for Discrete-Time Hidden Markov Jump Power Systems

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Cited by 50 publications
(18 citation statements)
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“…It should be pointed out that the proposed Markov process (MP) can be used to describe the abrupt changes in system structure, which has been widely used in theoretical analysis and practical applications [33], [34], [35]. Soliman and Shafiq [36], used the discrete-time MP to model transient and permanent faults of power lines, and the results were generalized to discrete-time hidden Markov jump power systems [37]. Zhao et al [30], proposed a distributed secondary control for islanded MG, and adopted the MP to describe the switching between multiple time delays.…”
Section: B Literature Reviewmentioning
confidence: 99%
“…It should be pointed out that the proposed Markov process (MP) can be used to describe the abrupt changes in system structure, which has been widely used in theoretical analysis and practical applications [33], [34], [35]. Soliman and Shafiq [36], used the discrete-time MP to model transient and permanent faults of power lines, and the results were generalized to discrete-time hidden Markov jump power systems [37]. Zhao et al [30], proposed a distributed secondary control for islanded MG, and adopted the MP to describe the switching between multiple time delays.…”
Section: B Literature Reviewmentioning
confidence: 99%
“…A typical problem in data analysis to study timeserie properties and, possibly, trying to build a predictive model. Built model are typically of autoregression, Kalman filter [9], [10], [11], [12], [13], hidden Markov model [14], [15], [16], [17], [18], [19], [20], and others [21]. In this work we consider timeserie data of M past observations, only past observations l = 1 .…”
Section: Introductionmentioning
confidence: 99%
“…According to Lemma 1 and by using the Schur complement in equation ( 21) (10) the proof is completed.…”
mentioning
confidence: 95%
“…In this case, Markov chains are widely adopted to model the variations in PS states. In [10], the Markov chain was employed to describe the random mutations of the discrete-time PS. In [11], the uncertain Markov chain was applied for the decentralized control of the PS.…”
mentioning
confidence: 99%