Title :
Adaptive inverse control based on online SVR
Author :
Yang, YinChao ; Xi, Bin
Author_Institution :
Dept. of Inf. Sci. & Technol., Xiamen Univ., Xiamen, China
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;
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
DOI :
10.1109/ICCSE.2009.5228375
