Adaptive inverse control based on online SVR

Author

Yang, YinChao ; Xi, Bin

Author_Institution

Dept. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China

fYear

2009

fDate

25-28 July 2009

Firstpage

519

Lastpage

522

Abstract

At present, the control of a dynamic system is generally done by means of feedback. This paper proposes a new method that use online SVR to achieve feedforward control for both linear and nonlinear plants. Online SVR is a new method when a new sample is added to (or removed from) the training set, it didn´t need retraining from scratch for each new data point. Therefore, it is an efficient algorithm. It has some advantages such as low computation, good approximation properties and so on. The Simulation results given in this paper shows that the algorithm has good control performance.

Keywords

adaptive control; feedback; feedforward; nonlinear control systems; adaptive inverse control; dynamic system control; feedback; feedforward control; linear plants; nonlinear plants; online SVR; Adaptive control; Computer science; Control systems; Neural networks; Nonlinear dynamical systems; Open loop systems; Programmable control; Signal processing algorithms; Support vector machines; Transfer functions; SVR; adaptive inverse control; inverse-model identification; linear control; nonlinear control;

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.2009.5228375

Filename

5228375