DocumentCode :
1604017
Title :
A new method for adaptive model-based control of non-linear plants using type-2 fuzzy logic and neural networks
Author :
Melin, Patricia ; Castillo, Oscar
Author_Institution :
Dept. of Comput. Sci., Tijuana Inst. of Technol., Mexico
Volume :
1
fYear :
2003
Firstpage :
420
Abstract :
We describe in this paper adaptive model-based control of non-linear plants using type-2 fuzzy logic and neural networks. First, the general concept of adaptive model-based control is described. Second, the use of type-2 fuzzy logic for adaptive control is described. Third, a neuro-fuzzy approach is proposed to learn the parameters of the fuzzy system for control. A specific non-linear plant is used to test the hybrid approach for adaptive control. A specific plant was used as test bed in the experiments. The non-linear plant that was considered is the "Pendubot", which is a non-linear plant similar to the two-link robot arm. The results of the type-2 fuzzy logic approach for control were good, both in accuracy and efficiency.
Keywords :
control nonlinearities; end effectors; fuzzy control; fuzzy systems; mechatronics; model reference adaptive control systems; neurocontrollers; Pendubot; adaptive model-based control; hybrid approach; mathematical model; mechatronics system; neural networks; neuro-fuzzy approach; nonlinear plants; two-link robot arm; type-2 fuzzy logic; Adaptive control; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Mathematical model; Neural networks; Payloads; Programmable control; Testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems, 2003. FUZZ '03. The 12th IEEE International Conference on
Print_ISBN :
0-7803-7810-5
Type :
conf
DOI :
10.1109/FUZZ.2003.1209400
Filename :
1209400
Link To Document :
بازگشت