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

fYear

2012

fDate

14-17 Oct. 2012

Firstpage

2457

Lastpage

2462

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;

fLanguage

English

Publisher

ieee

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

Type

conf

DOI

10.1109/ICSMC.2012.6378112

Filename

6378112