TY - GEN
T1 - An adaptive internal model control based on LS-SVM
AU - Sun, Changyin
AU - Song, Jinya
PY - 2007
Y1 - 2007
N2 - Based on least squares support vector machines regression algorithm, reverse model of system model is constructed, and adaptive internal model controller is developed in this paper. First, least squares support vector machine (LS-SVM) regression model and its training algorithm are introduced, provides SMO-based on pruning algorithms for LS-SVM. Then it is used in adaptive internal model control (IMC) for constructing internal model and designing the internal model controller. At last, LS-SVM regression based adaptive internal model control is used to control a benchmark nonlinear system. Simulation results show that the controller has simple structure, good control performance and robustness.
AB - Based on least squares support vector machines regression algorithm, reverse model of system model is constructed, and adaptive internal model controller is developed in this paper. First, least squares support vector machine (LS-SVM) regression model and its training algorithm are introduced, provides SMO-based on pruning algorithms for LS-SVM. Then it is used in adaptive internal model control (IMC) for constructing internal model and designing the internal model controller. At last, LS-SVM regression based adaptive internal model control is used to control a benchmark nonlinear system. Simulation results show that the controller has simple structure, good control performance and robustness.
UR - https://www.scopus.com/pages/publications/38049103034
U2 - 10.1007/978-3-540-72395-0_61
DO - 10.1007/978-3-540-72395-0_61
M3 - 会议稿件
AN - SCOPUS:38049103034
SN - 9783540723943
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 479
EP - 485
BT - Advances in Neural Networks - ISNN 2007 - 4th International Symposium on Neural Networks, ISNN 2007, Proceedings
PB - Springer Verlag
T2 - 4th International Symposium on Neural Networks, ISNN 2007
Y2 - 3 June 2007 through 7 June 2007
ER -