Proceedings ArticleDOI
On-line predictive control based on LS-SVM
Bicheng Lei,Wanliang Wang,Zuxin Li +2 more
- pp 7870-7873
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TLDR
An on-line predictive control based on least squares support vector machine (LS-SVM) is proposed and the results of simulation indicate that the method has enough rapid speed to establish on- line model and strong robustness to external disturbance and parameters variation.Abstract:
Aim at the robustness of predictive control and on-line modeling, an on-line predictive control based on least squares support vector machine (LS-SVM) is proposed. In order to carry out on-line learning, the training data threshold is set through discussing the theory of LS-SVM and the character of control system. Then the model of the on-line predictive control system is established, and the analytical solution of control variable is deduced integrating the method of model predictive control (MPC). The results of simulation indicate that the method has enough rapid speed to establish on-line model and strong robustness to external disturbance and parameters variation.read more
Citations
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Proceedings ArticleDOI
Application of Soft Sensor Based on LS-SVM on Estimation of Alumina Powder Flow
Chunyan Lu,Wei Li,Weirong Liu +2 more
TL;DR: In this paper, the soft sensor technique is applied in the estimation accuracy of the alumina powder flow in the process of conveying in electrolytic aluminum plant for the production of alumina can not be precise measured on-line.
Proceedings ArticleDOI
Predictive function control based on the LS-SVM for marine steam turbine system
TL;DR: A predictive function control based on LS-SVM is developed, which has good robustness to disturbance and parameters variation and the results of simulation indicate that the method has strong robusts to external disturbance and parameter variation.
Proceedings ArticleDOI
A nonlinear MIMO system identification based on improved Multi-Kernel Least Squares Support Vector Machines (Improved Multi-Kernel LS-SVM)
TL;DR: A new method for the identification of nonlinear Multiple Input-Multiple Output (MIMO) systems based on Constrained Particle Swarm Optimization (CPSO) is proposed and results show that the CPSO can quickly obtain the optimal parameters and therefore satisfying the required precision.
SVM with Quadratic Polynomial Kernel Function Based Nonlinear Model One-step-ahead Predictive Control
TL;DR: In this paper, a support vector machine (SVM) with quadratic polynomial kernel function based nonlinear model one-step-ahead predictive controller is presented, which is established with black-box identification method.
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