手動制御準定常特性の因果律的最適同定法による測定

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  • Identification of Quasi-Stationary Manual Tracking System Using Posterior Optimal Method
  • シュドウ セイギョ ジュン テイジョウ トクセイ ノ インガリツテキ サイテキ

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There have been various researches on identifying the dynamics of manual control characteristics based on the linearity assumption. However, all of these have required the additional assumption of stationarity. That is to say, manual control characteristics have been identified as time average over a certain time span.<br>Incidentally, the dynamics of human controller would gradually vary through learning as well as fatigue. Therefore, this variation was tried to be identified with respect to the pursuit manual tracking characteristics using discrete weighting function.<br>Continuous random process was used as reference input, the cutoff frequency of which is approximately equal to 0.8Hz, and CRT was used as the display. Input and output signals of the system were simultaneously sampled with an AD-converter, and processed by a fast algorithm called “a posteriori optimal method for system identification”, which we have developed recently to track variation of system dynamics.<br>The variation of pursuit manual tracking characteristics has been acquired as sequences of sampled weighting functions, and tendency in learning or fatigue has been shown qualitatively. This is the first result accompanied not only by a common prior certification on the identification error as for the ensemble average but also by a posteriori certification on the error of realized sample.

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