Abstract
Model reduction is important in control and instrumentation. Numerous papers on model reduction have been published. In this paper model reduction methods are classified into three categories according to their underlying principles. The three categories are continued fraction expansion, dominant mode, and optimum fitting. Given numerical examples, the effectiveness and the merit of simplified models are evaluated on the basis of the simulation of the step response and the least sum of squares of the sample errors.
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