Abstract
Abstract Aiming at a class of nonlinear process, an internal model control (IMC) scheme based on least squares support vector machines (LS-SVM) is proposed in this paper. By using LS-SVM algorithm and selecting the Gaussian kernel function, the internal model and its inversion of the nonlinear process are constructed, and the shortcomings of process identification and modeling based on neural network could be overcome. Then, combing with LS-SVM, the structure of internal model control was designed. The simulation results show that the nonlinear process identification based on LS-SVM has higher precision and better generalization than RBF neural network (NN) method, and IMC based on LS-SVM could achieve a good dynamic performance and robustness.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
