自動抽出関数展開モデルと遺伝的アルゴリズムを用いた連続時間非線形システムの同定

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  • Identification of Continuous-time Nonlinear Systems Using a Model Expanded by a Basis of Automatic Choosing Functions and Genetic Algorithm
  • ジドウ チュウシュツ カンスウ テンカイ モデル ト イデンテキ アルゴリズム オ モチイタ レンゾク ジカン ヒセンケイ システム ノ ドウテイ

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In this paper a new identification algorithm based on a model expanded by a basis of automatic choosing functions (ACF) for continuous-time nonlinear systems is proposed. The Butterworth filter is introduced as a delayed state variable filter, in order to evaluate higher order derivatives of input and output signals. A data region or a whole domain of signals is divided into some subdomains and the unknown nonlinear function to be estimated is approximately represented by a linear local equation on each subdomain. Then these linear local equations are united into a single one by the ACF of sigmoid type smoothly. The resulting model is linear in unknown parameters, which are easily estimated by the least-squares method. The model structure and the state variable filter are properly determined by genetic algorithm. Simulation results are shown to demonstrate the effectiveness of the proposed method.

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