2016
DOI: 10.1109/tfuzz.2015.2463674
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Cooperative Fuzzy Model-Predictive Control

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Cited by 29 publications
(15 citation statements)
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“…containing k − 1 ones, the rest zeros. Indeed, the resulting prediction model with q [k] in (28) to be (1,1,1,1,...,1,0,0,...) containing "k" ones would yield [31, eq. (11)] as a particular case.…”
Section: Discussion and Comparative Analysismentioning
confidence: 99%
See 1 more Smart Citation
“…containing k − 1 ones, the rest zeros. Indeed, the resulting prediction model with q [k] in (28) to be (1,1,1,1,...,1,0,0,...) containing "k" ones would yield [31, eq. (11)] as a particular case.…”
Section: Discussion and Comparative Analysismentioning
confidence: 99%
“…Recent works such as [25] discusses networked interval type-2 systems, but their results are still based on the 1-step equation discussed above so they are not solving a "proper" multi-step problem as most MPC literature understands. There are other related works on LMI-based suboptimal MPC for Wiener and Hammerstein models [26] or for input-output LPV systems (uncertain impulse-response coefficients) [27] anyway, these non-TS representations are intentionally out of the scope of the present manuscript, as well as other multi-agent/cooperative/stochastic versions of MPC [28,29].…”
Section: Introductionmentioning
confidence: 99%
“…An extension to a special form of nonlinear cooperative MPC is established in [47]. The theoretical developed approach of [47] is also used in the field of building automation, see [9].…”
Section: How Can Conflicting Control Goals Be Resolved?mentioning
confidence: 99%
“…An extension to a special form of nonlinear cooperative MPC is established in [47]. The theoretical developed approach of [47] is also used in the field of building automation, see [9]. An alternative approach to deal with conflicting optimization goals is presented in [48], where a hierarchical MPC structure splits the overall optimization problem in two less complex optimization problems (maximization of user comfort an minimization of energy demand).…”
Section: How Can Conflicting Control Goals Be Resolved?mentioning
confidence: 99%
“…Then the overall MPC law is obtained by the fuzzy blending of these controllers. However, in [11][12][13], delayed T-S systems are not studied. In [14], a robust MPC is investigated for a class of continuous-time uncertain delayed linear systems with non-linear cost function.…”
Section: Introductionmentioning
confidence: 99%