Title :
System identification via a virtual higher-resolution fuzzy model
Author :
Chow, K.M. ; Rad, A.B.
Author_Institution :
Dept. of Electr. Eng., Hong Kong Polytech. Univ., Kowloon, Hong Kong
Abstract :
A fuzzy identification algorithm with an inherent knowledge generalization mechanism is reported in this paper. In the proposed identification algorithm, a low-resolution fuzzy model is used to mimic the effect of a virtual higher-resolution model. The gradient descent optimization method is then applied to update the rule-base by using the difference between the actual system output and the model output. Simulation studies are included to demonstrate the performance of the algorithm
Keywords :
fuzzy logic; fuzzy systems; generalisation (artificial intelligence); gradient methods; identification; optimisation; truth maintenance; algorithm performance; fuzzy identification algorithm; gradient descent optimization method; knowledge generalization mechanism; low-resolution fuzzy model; model output; rule-base updating; simulation; system identification; system output; virtual higher-resolution fuzzy model; Databases; Fuzzy sets; Fuzzy systems; Humans; Indexing; Input variables; Optimization methods; System identification; Time varying systems; Tuners;
Conference_Titel :
Fuzzy Information Processing Society, 1999. NAFIPS. 18th International Conference of the North American
Conference_Location :
New York, NY
Print_ISBN :
0-7803-5211-4
DOI :
10.1109/NAFIPS.1999.781743
