TY - JOUR
T1 - Optimal design of interval type 2 fuzzy controllers based on a simple tuning algorithm
AU - Cortes-Rios, J. C.
AU - Gomez-Ramirez, E.
AU - Ortiz-De-La-Vega, H. A.
AU - Castillo, O.
AU - Melin, P.
PY - 2014/1/1
Y1 - 2014/1/1
N2 - Evolutionary algorithms are one of the most common choices reported in the literature for the tuning of fuzzy logic controllers based on either type-1 or type-2 fuzzy systems. An alternative to evolutionary algorithms is the simple tuning algorithm (STA-FLC), which is a methodology designed to improve the response of type-1 fuzzy logic controllers in a practical, intuitive and simple ways. This paper presents an extension of the simple tuning algorithm for fuzzy logic controllers based on the theory of type-2 fuzzy systems by using a parallel model implementation, it also includes a mechanism to calculate the feedback gain, new integral criteria parameters, and the effect of the AND/OR operator combinations on the fuzzy rules to improve the algorithm applicability and performance. All these improvements are demonstrated with experiments applied to different types of plants.
AB - Evolutionary algorithms are one of the most common choices reported in the literature for the tuning of fuzzy logic controllers based on either type-1 or type-2 fuzzy systems. An alternative to evolutionary algorithms is the simple tuning algorithm (STA-FLC), which is a methodology designed to improve the response of type-1 fuzzy logic controllers in a practical, intuitive and simple ways. This paper presents an extension of the simple tuning algorithm for fuzzy logic controllers based on the theory of type-2 fuzzy systems by using a parallel model implementation, it also includes a mechanism to calculate the feedback gain, new integral criteria parameters, and the effect of the AND/OR operator combinations on the fuzzy rules to improve the algorithm applicability and performance. All these improvements are demonstrated with experiments applied to different types of plants.
KW - Fuzzy controllers
KW - Parameter tuning algorithm
KW - Type-2 fuzzy logic
UR - http://www.scopus.com/inward/record.url?scp=84904558626&partnerID=8YFLogxK
U2 - 10.1016/j.asoc.2014.06.015
DO - 10.1016/j.asoc.2014.06.015
M3 - Article
AN - SCOPUS:84904558626
SN - 1568-4946
VL - 23
SP - 270
EP - 285
JO - Applied Soft Computing
JF - Applied Soft Computing
ER -