Support Vector Machine Based Identification of Inverse Dynamic Model of Thermal System and Its Application
The problem of inverse dynamics of thermal system which mean that the input is deduced from the output has become the key part of control of nonlinear system. To research and apply inverse dynamics of thermal system, it is crucial problem to establish its model. Support vector machine is a learning method based on statistical learning theory and structural risk minimization, which also has good generalization ability in the case of small-sample. The on-line identification for inverse dynamics of thermal object based on least squares support vector machine is realized and a control method is designed. Simulation results for superheated temperature object show that the inverse dynamic model based on least squares support vector machine has good identification precision and quite perfect generalization and traceable ability, the controller that is designed can also acquire good control performance.
Inverse dynamics Support vector machine Identification Control
Shuguang Shen Guangjun Wang Hong Chen
School of Power Engineering , Chongqing University, Chongqing, 400044, China
国际会议
2007杭州国际动力工程会议(The International Conference on Power Engineering 2007)
杭州
英文
2007-10-23（万方平台首次上网日期，不代表论文的发表时间）