Title :
Intelligent adaptive steering control for electric unicycles
Author :
Li, Yi-Yu ; Tsai, Ching-Chih ; Lin, Chih-Min
Author_Institution :
Dept. of Electr. Eng., Nat. Chung-Hsing Univ., Taichung, Taiwan
Abstract :
This paper presents an intelligent adaptive steering control using linear quadratic regulation (LQR) approach and fuzzy cerebella model articulation control (CMAC) method for an electrical unicycle. The fuzzy CMAC is employed to on-line learn unknown frictions between the wheel and the terrain surfaces. The LQR approach is used to design a state feedback controller, in order to simultaneously achieve self-balancing and velocity control for the unicycle with different riders. The performance and merit of the proposed method are well exemplified by conducting simulations on a laboratory-built electric unicycle.
Keywords :
adaptive control; cerebellar model arithmetic computers; electric vehicles; fuzzy control; intelligent control; learning systems; linear quadratic control; state feedback; velocity control; CMAC method; LQR approach; fuzzy cerebella model articulation control method; intelligent adaptive steering control; laboratory-built electric unicycle; linear quadratic regulation approach; online learn unknown frictions; self-balancing control; state feedback controller; terrain surfaces; velocity control; wheel surfaces; Adaptation models; Friction; Mathematical model; State feedback; Vehicles; Velocity control; Wheels; Electric unicycle; fuzzy CMAC; linear quadratic regulation (LQR); state feedback;
Conference_Titel :
Systems, Man, and Cybernetics (SMC), 2012 IEEE International Conference on
Conference_Location :
Seoul
Print_ISBN :
978-1-4673-1713-9
Electronic_ISBN :
978-1-4673-1712-2
DOI :
10.1109/ICSMC.2012.6378112
