2012
DOI: 10.1049/iet-cta.2010.0580
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Robust control of observer-based sampled-data systems: digital redesign approach

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Cited by 9 publications
(6 citation statements)
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“…Theorem 2: Consider the observer-based sampled-data fuzzy controller (6) for the fuzzy system (2) associated with the cost function (8). If the following optimisation problem has a solution: min ψ subject to LMIs (10)- (12) and (21) (32) whereP fij = diag{P 1 fij , P 2 fij } andP 2 fij = diag{I , P 2 fij } for f ∈ I 2 , then the observer-based sampled-data fuzzy controller is an optimal controller for the IDR of the fuzzy system (2), and J * = ψ is the minimised upper bound of the state-matching error cost function (8).…”
Section: Corollarymentioning
confidence: 99%
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“…Theorem 2: Consider the observer-based sampled-data fuzzy controller (6) for the fuzzy system (2) associated with the cost function (8). If the following optimisation problem has a solution: min ψ subject to LMIs (10)- (12) and (21) (32) whereP fij = diag{P 1 fij , P 2 fij } andP 2 fij = diag{I , P 2 fij } for f ∈ I 2 , then the observer-based sampled-data fuzzy controller is an optimal controller for the IDR of the fuzzy system (2), and J * = ψ is the minimised upper bound of the state-matching error cost function (8).…”
Section: Corollarymentioning
confidence: 99%
“…Especially, the digital redesign (DR), which is one of the sampled-data control techniques, guarantees the approximate performance to a well-designed analog controller, because the DR is possible to convert an analog controller into an equivalent digital one in the state-matching sense. Thus, many DR techniques have been proposed [16][17][18][19][20][21], and especially, the DR is extended into the intelligent DR (IDR) for non-linear systems [22][23][24][25][26]. In the DR and IDR techniques for observer-based sampled-data control, remarkable researches have been performed [18,21,24,26], but there are still some problems to be solved.…”
Section: Introductionmentioning
confidence: 99%
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“…Later, in [21], the technique of sampled‐data feedback domination was developed to global sampled‐data output‐feedback stabilisation of a class of upper‐triangular non‐linear systems. In [22, 23], for several kinds of different systems, the problem of sampled‐data control was also discussed. However, these results [4, 2123] do not consider the effect of input delay.…”
Section: Introductionmentioning
confidence: 99%
“…In [22, 23], for several kinds of different systems, the problem of sampled‐data control was also discussed. However, these results [4, 2123] do not consider the effect of input delay. When there exist both sampled‐data and input delay, in [24], the stabilisation problem of non‐linear systems was investigated.…”
Section: Introductionmentioning
confidence: 99%