[Proceedings 1993] Second IEEE International Conference on Fuzzy Systems
DOI: 10.1109/fuzzy.1993.327572
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Design of quasi-optimal fuzzy controller by fuzzy dynamic programming

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Cited by 11 publications
(3 citation statements)
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“…Fuzzy constraints are imposed on the future sequence of control variables and fuzzy goals are imposed on the predicted states . Imposing fuzzy constraints on the control signal is a compromise between the no constraints case which may not be realistic and the tight, hard constraints which could yield a bang bang control [7]. In the particular case where the constraints are limits on the control signal (9) the fuzzy constraints can be regarded as a softening or fuzzification of these hard limitations.…”
Section: Model-based Fuzzy Predictive Controlmentioning
confidence: 99%
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“…Fuzzy constraints are imposed on the future sequence of control variables and fuzzy goals are imposed on the predicted states . Imposing fuzzy constraints on the control signal is a compromise between the no constraints case which may not be realistic and the tight, hard constraints which could yield a bang bang control [7]. In the particular case where the constraints are limits on the control signal (9) the fuzzy constraints can be regarded as a softening or fuzzification of these hard limitations.…”
Section: Model-based Fuzzy Predictive Controlmentioning
confidence: 99%
“…In these methods, close to the so-called fuzzy optimal control [7], [8], the model of the system may be fuzzy or non fuzzy although the latter case is more often studied, but the control objectives and constraints are fuzzy, leading to the terminology of fuzzy goals and fuzzy constraints. The predictive control problem is formulated as finding the confluence of fuzzy constraints and fuzzy goals over a future finite horizon, leading to model based fuzzy predictive controller [11], [23], [25].…”
Section: Introductionmentioning
confidence: 99%
“…Tl4e dynamic programming method has the advantage that is conceptually simple and does not need an analytic description of the dynamic system, so that a linguistic (or fuzzy)-description can be used instead. This re~nark was effectively known for already some time (see [13,14]) but only lately has been detailed in a series of applications [8], due only to increasing available computin-g power. But this approach Permission to copy without fee all or part of this material is granted provided ",hat the copies arc not made or distribeled for direct comme~ial advantage, the ACM copyright notice and the title of the publication and its date appear, and notice is given that copying is by pel'm~sion of the Association for Computing Machinery.…”
Section: Introductionmentioning
confidence: 98%