Journal of the Korean Institute of Intelligent Systems (한국지능시스템학회논문지)

Korean Institute of Intelligent Systems (한국지능시스템학회)
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A Balanced Model Reduction for Uncertain Nonlinear Systems

불확실한 비선형 시스템의 균형화된 모델축소

  • Published : 2006.04.01
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Abstract

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

이 연구는 T-S 퍼지 접근법을 이용하여 불확실한 비선형 시스템의 균형화된 모델 차수 축소 방법을 제시한다. 일반화된 가제어성, 가관측성 그래미안을 정의하고 이들을 이용하여 균형화된 상태공간 모델을 얻는다. 균형화된 상태공간 모델로부터 상태변수 뿐만 아니라 불확실한 요소를 절삭하여 간략화된 모델을 얻는 기법을 제시하고 모델오차의 상한치를 제시한다. 균형화된 상해공간은 선형행렬 부등식의 해를 구하여 구현할 수 있으며 제시한 방법의 효용성을 보여주기 위하여 수치 예를 보여준다.

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References

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