TY - JOUR
T1 - Experimental study of intelligent controllers under uncertainty using type-1 and type-2 fuzzy logic
AU - Sepúlveda, Roberto
AU - Castillo, Oscar
AU - Melin, Patricia
AU - Rodríguez-Díaz, Antonio
AU - Montiel, Oscar
N1 - Funding Information:
The authors thank the Comisión de Operación y Fomento de Actividades Académicas del I.P.N., Instituto Tecnológico de Tijuana, and UABC for supporting our research activities.
PY - 2007/5/15
Y1 - 2007/5/15
N2 - Uncertainty is an inherent part in control systems used in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional fuzzy systems cannot fully handle the uncertainties present in control systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us with more parameters and more design degrees of freedom. This paper deals with the design of control systems using type-2 fuzzy logic for minimizing the effects of uncertainty produced by the instrumentation elements, environmental noise, etc. The experimental results are divided in two classes, in the first class, simulations of a feedback control system for a non-linear plant using type-1 and type-2 fuzzy logic controllers are presented; a comparative analysis of the systems' response in both cases was performed, with and without the presence of uncertainty. For the second class, a non-linear identification problem for time-series prediction is presented. Based on the experimental results the conclusion is that the best results are obtained using type-2 fuzzy systems.
AB - Uncertainty is an inherent part in control systems used in real world applications. The use of new methods for handling incomplete information is of fundamental importance. Type-1 fuzzy sets used in conventional fuzzy systems cannot fully handle the uncertainties present in control systems. Type-2 fuzzy sets that are used in type-2 fuzzy systems can handle such uncertainties in a better way because they provide us with more parameters and more design degrees of freedom. This paper deals with the design of control systems using type-2 fuzzy logic for minimizing the effects of uncertainty produced by the instrumentation elements, environmental noise, etc. The experimental results are divided in two classes, in the first class, simulations of a feedback control system for a non-linear plant using type-1 and type-2 fuzzy logic controllers are presented; a comparative analysis of the systems' response in both cases was performed, with and without the presence of uncertainty. For the second class, a non-linear identification problem for time-series prediction is presented. Based on the experimental results the conclusion is that the best results are obtained using type-2 fuzzy systems.
KW - Fuzzy control
KW - Interval type-2 fuzzy sets
KW - System identification
KW - Type-2 fuzzy logic systems
UR - http://www.scopus.com/inward/record.url?scp=33847666532&partnerID=8YFLogxK
U2 - 10.1016/j.ins.2006.10.004
DO - 10.1016/j.ins.2006.10.004
M3 - Artículo
SN - 0020-0255
VL - 177
SP - 2023
EP - 2048
JO - Information Sciences
JF - Information Sciences
IS - 10
ER -