CARMAモデルを用いた一般化最小分散評価に基づく直接的制御器パラメータ調整法

抄録

The paper proposes a direct control parameter tuning method using a generalized minimum variance (GMV) evaluation in regulatory control. In the method the performance index is calculated using the squared difference between an estimated variance of generalized output and a desired generalized output variance would be minimized. A one-shot closed loop experimental input and output data by an initial controller generate the estimated variance of generalized output instead of using a plant model. Therefore, the proposed method does not require an extra plant test for the identification of the plant model and/or control parameter tuning. Furthermore, since the GMV evaluation consisting of weighted output and control signal is employed, excessive high gain control parameters can be avoided. The feature can be expected to improve stability of the closed loop system. The efficiency of the proposed method is demonstrated from a numerical example.