与えられた2次元入出力データからシステムの状態空間モデルを求める一逐次近似法

概要

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This paper proposed a state-space approximation method using successive approximation for given 2-D input-output data. The state-space model considered here is the most general 2-D state-space Roesser's model. First, the relations between the Markov parameter and the state-space model, the parameter and coefficients of denominator of system function, and the parameter and 2-D input-output data, are investigated. Next, for given 2-D input-output data a method, which approximates the state-space model so that square sum of errors of output data is minimized, is presented by using the above relations. The proposed method gives the minimal realization of system in the least square error sense and the algorithm is relatively simple. Finally, an example is given to show the effectiveness of our algorithm.
東海大学の論文