智能多目标优化控制及其应用

INTELLIGENT MULTIOBJECTIVE OPTIMAL CONTROL AND ITS APPLICATION

  • 摘要: 本文首先提出了MLMO原则,即被控过程的规模越大,越复杂,要获得满意的控制效果所须达到的控制目标就越多,为了对复杂的具有变化特性的过程进行有效的建模与控制,提出了过程划分的方法,之后又提出了具有后果相关性的模糊多目标预测控制(FMPC),用以实现对具有不确定性的复杂过程实现多目标的优化控制,最后将过程划分技术、FMPC方法与专家系统技术结合起来,提出了智能多目标优化控制方法(IMOC),并将其应用于对列车运行过程的控制,仿真结果证明了所提方法的有效性和优越性.

     

    Abstract: In this papcr, the MLMO principle that more large and more complcx the controlled process is, more objcctivcs there are to be satisfied to control the process-with high quality is proposed. The concept and the approach of process partition are also proposed to model the complcx process with varying characterigtics. To multiobjcctivcly control the process with linguisitic uncertainty, the result-related fuzzy multiobjcctivc predictive control approach(FMPC) is put forward and finally the intelligent multiobjcctivc optimal control(IMOC) which includes the process partition method, FMPC and the expert system technique is prcscnted and applied to the control of the train-travelling process with good results.

     

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