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|Title:||Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers|
Wan Tan, Woei
Type-2 fuzzy logic controller
|Citation:||Wu, Dongrui, Wan Tan, Woei (2006-12). Genetic learning and performance evaluation of interval type-2 fuzzy logic controllers. Engineering Applications of Artificial Intelligence 19 (8) : 829-841. ScholarBank@NUS Repository. https://doi.org/10.1016/j.engappai.2005.12.011|
|Abstract:||Type-2 fuzzy sets, which are characterized by membership functions (MFs) that are themselves fuzzy, have been attracting interest. This paper focuses on advancing the understanding of interval type-2 fuzzy logic controllers (FLCs). First, a type-2 FLC is evolved using Genetic Algorithms (GAs). The type-2 FLC is then compared with another three GA evolved type-1 FLCs that have different design parameters. The objective is to examine the amount by which the extra degrees of freedom provided by antecedent type-2 fuzzy sets is able to improve the control performance. Experimental results show that better control can be achieved using a type-2 FLC with fewer fuzzy sets/rules so one benefit of type-2 FLC is a lower trade-off between modeling accuracy and interpretability. © 2006 Elsevier Ltd. All rights reserved.|
|Source Title:||Engineering Applications of Artificial Intelligence|
|Appears in Collections:||Staff Publications|
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