基于Hankel范数模型降价的控制对象的名义模型选择

NOMINAL MODEL SELECTION FOR CONTROL PLANT BASED ON HANKEL NORM MODEL REDUCTION

研究了控制对象具有多个模型时，求取其适合鲁棒控制器设计的名义模型的问题．提出了一种基于Ｈａｎｋｅｌ范数模型降阶的名义模型选择算法．

This paper investigates the problem concerning with plant nominal model selection when a batch of plant models have been supplied, with the nominal model intended use as robust controller design. A selection algorithm is proposed which is based on frequency weighted Hankel norm model reduction. An illustrative example shows that compared with the plant nominal model seleted intuitively, the approximation error of the plant nominal model obtained through the proposed algorithm is smaller, even though its complexity remains unchanged.