基于输入输出数据的一体化多模型建模与控制

Integrated Multi-Model Modeling and Control Method Based on Input-Output Data

针对复杂非线性系统,提出了一种完全基于输入输出数据的一体化多模型建模与预测控制设计方法。首先,利用模糊空间划分对输入数据进行在线聚类;然后,采用最小二乘法在每一个聚类点处建立一个局部模型,并将模糊空间划分与多模型建模相结合,利用即时输入输出数据对局部模型的数量以及每一个局部模型的参数进行在线更新,从而实现对复杂非线性系统的在线建模;最后,在此基础上进行预测控制器的设计,将系统建模与控制器的设计包含在一个控制系统设计框架以内,对模型不确定性具有更好的鲁棒性。仿真实验的结果表明了该方法的有效性。

An integrated multi-model modeling and control method based totally on the input-output data was proposed for the complex nonlinear system.Firstly,fuzzy partition was employed for on-line clustering of the input-output data;and then,the Least-Squares（LS） algorithm was used to construct a local model for each clustering.The fuzzy partition was combined with multi-model modeling,the parameters of each local model and the quantity of the local models were updated on-line by using the real-time data,so as to realize the on-line modeling of the complex nonlinear system.Finally,a predictive controller based on the multiple models was designed.The system modeling and design of controller were then included in a framework,which increased robustness of the control system.Simulation result showed the effectiveness of the proposed method.