Adaptive inverse control based on recusive least-squares algorithm

Author

Lu, Ao ; Bin, Xi

Author_Institution

Dept. of Automatization, Xiamen Univ., Xiamen, China

fYear

2009

fDate

25-28 July 2009

Firstpage

542

Lastpage

544

Abstract

In recent years, adaptive inverse control is a very vivid field because of its advantages. It is quite different from the traditional control. Adaptive inverse control adopts feedback in parameters tuning of the system, not the signal flow. In this paper, we apply the recursive least-squares (RLS) algorithm to the adaptive inverse control to achieve the learning of the inverse model quickly. Besides, we compare it with the least mean-square (LMS) algorithm. The results show that when SNR is high, the convergence rate of RLS algorithm is faster than the LMS algorithm.

Keywords

adaptive control; feedback; least squares approximations; adaptive inverse control; feedback; recusive least-squares algorithm; system parameter tuning; Adaptive algorithm; Adaptive control; Automatic control; Computer science; Computer science education; Control systems; Error correction; Least squares approximation; Programmable control; Resonance light scattering; LMS algorithm; RLS algorithm; adaptive inverse control; minimum phase system;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer Science & Education, 2009. ICCSE '09. 4th International Conference on

Conference_Location

Nanning

Print_ISBN

978-1-4244-3520-3

Electronic_ISBN

978-1-4244-3521-0

Type

conf

DOI

10.1109/ICCSE.2009.5228372

Filename

5228372