仮想時間応答を評価するAI的データ駆動制御V-Tigerの実用化

抄録

Since Artificial Intelligence (AI) has won over human pros such as Chess, Shogi and Go, expectations for AI have been increasing dramatically. One of the reasons why AI has developed so much is the tremendous increase in processing speed of computers, which makes it possible to virtually repeat simulated competitions such as Othello, Shogi, Go and so on in the computer very fast. Finally, AI has gained strength over human pros. Also in control engineering, if gain tuning experiments of controllers can be virtually performed in a computer, it can be expected to dramatically improve control performance with an AI-like approach. This paper practicalizes the method called ‘Virtual Time-response based Iterative Gain Evaluation and Redesign’ (V-Tiger) which iterates 1) to calculate virtual time responses of the closed loop system when a certain controller is inserted based on one-shot experimental data, 2) to measure the overshoot and settling time from the virtual time responses, and 3) to evaluate and redesign the controller gain considering the stability margin.