DocumentCode
2047171
Title
Fuzzy control: cloning and Kalman-based learning
Author
Cortesão, Rui ; Koeppe, Ralf ; Nunes, Urbano ; Hirzinger, Gerd
Author_Institution
Inst. of Syst. & Robotics, Coimbra Univ., Portugal
Volume
2
fYear
2002
fDate
2002
Firstpage
981
Abstract
A different perspective of fuzzy control is introduced based on evolutionary concepts and Kalman gain properties. No explicit verbal (if-then) rules are needed. The fuzzy controller emerges directly from state space design through a cloning process. State feedback gains are cloned into proportional fuzzy controllers. Each state variable is associated with a fuzzy rule. Kalman techniques are the basis for rule learning, reshaping the cloned fuzzy rules. Simulations with a rotary inverted pendulum are presented to test the method.
Keywords
Kalman filters; fuzzy control; learning (artificial intelligence); pendulums; state feedback; state-space methods; Kalman gain; cloning process; evolutionary concepts; feedback gains; fuzzy control; rotary inverted pendulum; rule learning; state feedback; state space; Cloning; Control systems; Fuzzy control; Fuzzy logic; Fuzzy systems; Kalman filters; Orbital robotics; Proportional control; State feedback; State-space methods;
fLanguage
English
Publisher
ieee
Conference_Titel
American Control Conference, 2002. Proceedings of the 2002
ISSN
0743-1619
Print_ISBN
0-7803-7298-0
Type
conf
DOI
10.1109/ACC.2002.1023145
Filename
1023145
Link To Document