制御系の並列学習(重根フィルタ)による同定

概要

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This paper proposes a method of process identification with the aid of multiple eigenvalue filter deduced from learning control which has been described in the former paper "On parallel Learning in Control Systems (Derivation of Multiple Eigenvalue Filter)". The feedback control system model is copied to i (i=1, 2, …, k) systems corresponding to learning times. The actuating signal of the first model is added to the actuating signal of the second model, and then, the actuating signal of the second model is added to the actuating signal of the third model. Likewise, the actuating signal of the k - 1-th model is added to the actuating signal of the k-th model. Thus obtained k-th model is equivalent to the system which has a filter as series compensator composed by the sum of i (i=0, 1, 2, …, k) multiple of the left side of the characteristic equation. This paper calls the sum "multiple eigenvalue filter". It is shown hat resolution of dynamic characteristics is much improved by Fourier integral of input/output of the multiple eigenvalue filter, instead of input/output in a controlled system.
一般社団法人日本機械学会の論文
1994-05-25