| Robustly stable model predictive control based on parallel support vector machines with linear kernel |
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| 作者姓名： | 包哲静 钟伟民 皮道映 孙优贤 |
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| 作者单位： | State Key Laboratory of Industrial Control Technology Zhejiang University，State Key Laboratory of Chemical Engineering East China University of Science and Technology，State Key Laboratory of Industrial Control Technology Zhejiang University，State Key Laboratory of Industrial Control Technology Zhejiang University，Hangzhou 310027 China，Shanghai 200237 China，Hangzhou 310027 China，Hangzhou 310027 China |
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| 基金项目： | 国家重点基础研究发展计划(973计划);国家自然科学基金 |
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| 摘 要： | Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin.
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| 关 键 词： | 平行线 模型预测控制 稳定性 机械 |
| 收稿时间： | 20 December 2006 |
| 修稿时间： | 2006-12-20 |
Robustly stable model predictive control based on parallel support vector machines with linear kernel |
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| Bao Zhe-jing , Zhong Wei-min , Pi Dao-ying and Sun You-xian.Robustly stable model predictive control based on parallel support vector machines with linear kernel[J].Journal of Central South University of Technology,2007,14(5):701-707. |
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| Authors: | Bao Zhe-jing Zhong Wei-min Pi Dao-ying and Sun You-xian |
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| Affiliation: | 1. State Key Laboratory of Industrial Control Technology, Zhejiang University, Hangzhou 310027, China; 2. State Key Laboratory of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China |
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| Abstract: | Robustly stable multi-step-ahead model predictive control (MPC) based on parallel support vector machines (SVMs) with linear kernel was proposed. First, an analytical solution of optimal control laws of parallel SVMs based MPC was derived, and then the necessary and sufficient stability condition for MPC closed loop was given according to SVM model, and finally a method of judging the discrepancy between SVM model and the actual plant was presented, and consequently the constraint sets, which can guarantee that the stability condition is still robust for model/plant mismatch within some given bounds, were obtained by applying small-gain theorem. Simulation experiments show the proposed stability condition and robust constraint sets can provide a convenient way of adjusting controller parameters to ensure a closed-loop with larger stable margin. |
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| Keywords: | parallel support vector machines model predictive control stability robustness |
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