基于一种模型联合降阶的控制器降阶方法

Controller Reduction Method Based on a Model Synthetically Descending

提出了基于一种模型联合降阶的控制器降阶方法,这种方法根据线性系统包含原理的约束与聚集两类条件,将平衡法与奇异值分解法相结合形成更加简洁、有效的控制器降阶方法。与单一的基于Hankel范数法和Schmr均衡法相比较,具有更好的灵敏度和鲁棒性。仿真结果表明这种控制器降阶的方法是可行的。

In this paper we introduce a controller reduction method based on a model synthetically descending way ,This method according to two types of restriction and aggregation conditions of the inclusion principle ,a con-cise and effective controller reduction method was obtained by a model descending way synthesized the balanced method and the singular value decomposition .Simulation results show that this method is feasible .