引言rn实际的工业过程对象,大部分都呈现出很强的非线性特性,其控制过程十分复杂.虽然近年来,对非线性技术的研究已经取得了很多的成果.但是非线性系统精确建模困难[1]、非线性微分方程求解烦琐等问题仍然阻碍着非线性控制器的发展.针对这些问题,很多学者根据处理复杂问题使用的分解合成策略,提出了多模型方法[2].多模型方法的基本思想是把整个操作区间用某种划分方法分成若干个子区间,每个子区间上建立对应的子模型,在系统运行时,使用子模型代替全局模型.%Multi-model predictive control has become an effective method for handling the process of nonlinear system. But the system using traditional multi-model predictive control has slow rise time and slow convergence speed when it is used for the MIMO nonlinear system solving the condition with large scale transition of operating condition. To solve these problems, a new structure of multi-model called multi-hierarchical model has been presented. This structure consists of many layers that each layer is comprised of multiple models. The number of sub-models in each layer is different. Under the condition of the same global operation space, the upper layer has a smaller number of sub-models, and the lower layer has a larger number of sub-models. Because of this structure, the models chosen from different layers can deal with the large scale transition of operating condition. In this paper, a new model switching method between different layers is presented. This method uses the error of output and the variation of output error as the rules for layer switching. In the end of this paper, the simulation results of pH neutralization process which is a MIMO nonlinear system demonstrate that the multi-hierarchical model using the new model switching method is superior to single-hierarchical model with faster rise time, better convergence speed and stability.
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