| A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control |
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| 作者姓名： | 杜晓宁 Xi Yugeng Li Shaoyuan |
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| 作者单位： | InsituteofAutomation,ShanghaiJiaotongUniversity,Shanghai200030,P.R.China |
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| 基金项目： | 国家高技术研究发展计划(863计划)，国家自然科学基金 |
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| 摘 要： | Model Predictive Control(MPC) is a popular technique and has been successfully used in various industrial applications.Howver,the big drawback of MPC involved in the formidable online computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs.This paper develops an aggregation optimization strategy for MPC that can imporove the computational efficiency of MPC.FOr the regulation problem.an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action.
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| 关 键 词： | 自动化 模型预测控制 有效聚集策略 |
A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control |
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| Xi Yugeng,Li Shaoyuan.A Computationally Efficient Aggregation Optimization Strategy of Model Predictive Control[J].High Technology Letters,2002,8(2):68-71. |
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| Authors: | Xi Yugeng Li Shaoyuan |
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| Abstract: | Model Predictive Control (MPC) is a popular technique and has been successfully used in various industrial applications. However, the big drawback of MPC involved in the formidable on-line computational effort limits its applicability to relatively slow and/or small processes with a moderate number of inputs. This paper develops an aggregation optimization strategy for MPC that can improve the computational efficiency of MPC. For the regulation problem, an input decaying aggregation optimization algorithm is presented by aggregating all the original optimized variables on control horizon with the decaying sequence in respect of the current control action. |
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| Keywords: | Model Predictive Control (MPC) on-line computational effor |
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