Multi-Step Model Predictive Control Based on Online Support Vector Regression Optimized by Multi-Agent Particle Swarm Optimization Algorithm |
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Authors: | Xianlun Tang Nianci Liu Yali Wan Fei Guo |
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Institution: | 1.College of Automation,Chongqing University of Posts and Telecommunications,Chongqing,China;2.Chongqing Financial Assets Exchange,Chongqing,China |
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Abstract: | As optimization of parameters affects prediction accuracy and generalization ability of support vector regression (SVR) greatly and the predictive model often mismatches nonlinear system model predictive control, a multi-step model predictive control based on online SVR (OSVR) optimized by multi-agent particle swarm optimization algorithm (MAPSO) is put forward. By integrating the online learning ability of OSVR, the predictive model can self-correct and adapt to the dynamic changes in nonlinear process well. |
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