| On-Line Tuning Scheme for the Generalized Predictive Controller via Simulation Optimization |
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| 引用本文： | 李少远. On-Line Tuning Scheme for the Generalized Predictive Controller via Simulation Optimization[J]. 系统工程与电子技术(英文版), 2003, 14(2) |
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| 作者姓名： | 李少远 |
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| 作者单位： | Li Shaoyuan Institute of Automation，Shanghai Jiaotong University，Shanghai 200030，P. R. China |
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| 基金项目： | ThisprojectwassupportedbytheNationalNaturalScienceFoundationofChina (6 0 0 74 0 0 4 ) |
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| 摘 要： | 1 .INTRODUCTIONModelpredictivecontrol(MPC)isacomputercontrolalgorithmthatsolvesanon lineoptimizationproblemateachsamplinginstant.Overthepastmorethan 2 0years,thepopularityofMPCforindustrialprocesscontrolapplicationshasbeenincreasingcontinuouslywiththeeffectivenessimprovementofvariousad vancedcontroltechnologieshavingbeendemonstratedinindustrialapplications[1 ,2 ] .Oneofthemainrea sonsforthesuccessofMPCintheindustrialprocessisitsabilitytoobtainagoodperformancestartingfromratherintuitive…
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On-Line Tuning Scheme for the Generalized Predictive Controller via Simulation Optimization |
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| Li Shaoyuan Institute of Automation,Shanghai Jiaotong University,Shanghai ,P. R. China. On-Line Tuning Scheme for the Generalized Predictive Controller via Simulation Optimization[J]. Journal of Systems Engineering and Electronics, 2003, 14(2) |
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| Authors: | Li Shaoyuan Institute of Automation Shanghai Jiaotong University Shanghai P. R. China |
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| Affiliation: | Institute of Automation, Shanghai Jiaotong University, Shanghai 200030, P. R. China |
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| Abstract: | Predictive control has recently received much attention from researchers. However a challenging problem to be solved is how to tune the parameters of the predictive controller. So far, only few guidelines related to tuning of the parameters of predictive controllers have been provided in literature. In practice, these parameters are generally off-line determined by the designers' experience. From the point of view of process control, it is difficult to find out the optimal parameters for the control system based on a single quadratic performance index, which is used in the standard predictive control algorithm. The fuzzy decision-making function is investigated in this paper. Firstly, M control actions are achieved by unconstrained predictive control algorithm, and fuzzy goals and fuzzy constraints are then calculated and the global satisfaction degree is obtained by fuzzy inference. Moreover, the weighting coefficient λ in the cost function is tuned using simulation optimization according to the fuzzy criteria. |
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| Keywords: | Predictive control Simulation optimization Fuzzy decision-making. |
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