Title :
Adaptive PID controller based on online LSSVR with kernel tuning
Author :
Uçak, Kemal ; Öke, Gülay
Author_Institution :
Dept. of Control Eng., Istanbul Tech. Univ., Istanbul, Turkey
Abstract :
In this paper, the effects of tuning the kernel bandwidth for an online LSSVM are investigated. LSSVM is used to obtain a model of the system, and based on this model information, an adaptive PID is designed to control the plant. The kernel parameter determines how the measured input is mapped to the feature space and a better plant model can be achieved by discarding redundant or irrelevant features, therefore introducing adaptability in kernel parameters improves modeling performance. The purpose of this paper is to find the optimal kernel bandwidth to improve the modeling performance of the LSSVM and consequently control performance obtained by adaptive PID which is designed based on the Jacobian information attained by the LSSVM. The proposed method has been evaluated by simulations carried out on a continuously stirred tank reactor (CSTR), and the results show that there is an improvement both in modeling and control performances.
Keywords :
adaptive control; chemical engineering; chemical reactors; control system synthesis; least squares approximations; regression analysis; support vector machines; three-term control; CSTR; Jacobian information; adaptive PID controller; continuously stirred tank reactor; feature space; kernel parameter; kernel tuning; least square support vector regression; online LSSVR; optimal kernel bandwidth; plant model; Adaptation models; Bandwidth; Indexes; Kernel; Support vector machines; Training data; Tuning; Adaptive PID; Feature Selection; Kernel Parameter; Online LSSVR;
Conference_Titel :
Innovations in Intelligent Systems and Applications (INISTA), 2011 International Symposium on
Conference_Location :
Istanbul
Print_ISBN :
978-1-61284-919-5
DOI :
10.1109/INISTA.2011.5946117