2009
DOI: 10.1016/j.eswa.2008.05.031
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Design and simulation of self-tuning PID-type fuzzy adaptive control for an expert HVAC system

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Cited by 193 publications
(86 citation statements)
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“…There are varied prominent studies in self-tuning PID field. Supervisory control or self-tuning can be executed via different methods, for instance optimization based [21][22][23], fuzzy-logic mechanism [24,25], neural networks [26,27]. In this paper, for the first time in the literature and beside of mentioned self-tuning PID strategies, the self-tuning PI controller via FCM method is proposed.…”
Section: A Brief Overview Of Fuzzy Cognitive Mapsmentioning
confidence: 99%
“…There are varied prominent studies in self-tuning PID field. Supervisory control or self-tuning can be executed via different methods, for instance optimization based [21][22][23], fuzzy-logic mechanism [24,25], neural networks [26,27]. In this paper, for the first time in the literature and beside of mentioned self-tuning PID strategies, the self-tuning PI controller via FCM method is proposed.…”
Section: A Brief Overview Of Fuzzy Cognitive Mapsmentioning
confidence: 99%
“…In this case, of a regulator type controller, the approach in the construction of the rules base is different. We specify that there is a booming literature of the field, but especially we highlight the papers [30]- [32]. A conventional FLC of Proportional Derivative (PD)-type will be first described.…”
Section: Artificial Intelligence Based Control Of Hvac Systemmentioning
confidence: 99%
“…RB shown in Fig. 10 is used in [32]. The defuzzyfier concerns just the transforming of these if …, then rules into a mathematical formula giving the output control variable u f .…”
Section: Artificial Intelligence Based Control Of Hvac Systemmentioning
confidence: 99%
“…The summary showed that fuzzy supervisory controllers are capable of extending the capacity of the conventional PID control paradigm to coupe with challenging applications. (28,52,53,(55)(56)(57)(58)(59)(60)(61)(62)(63)(64)(65) This paper presents the design of a fuzzy supervisory controller for managing the indoor comfort of an airport terminal and examines its benefits. A detailed simulation model is used to determine the effects in terms of energy and carbon emission reduction as well as passenger comfort in a UK airport terminal.…”
Section: Introductionmentioning
confidence: 99%