Virtual Time-response based Iterative Gain Evaluation and Redesign

Abstract 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 the 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 proposes a new 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.