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Virtual Time-response based Iterative Gain Evaluation and Redesign

机译：基于虚拟时间响应的迭代增益评估和重新设计

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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.
机译：由于人工智能（AI）赢得了诸如国际象棋，Shogi和Go等人的优势，因此对AI的期望急剧增加。为什么AI已经开发的原因之一是计算机处理速度的巨大增加，这使得几乎可以重复模拟的竞争，例如奥赛罗，Shogi，在计算机上的速度非常快。最后，AI已经获得了人类优势的力量。同样在控制工程中，如果可以在计算机中实际上执行控制器的增益调整实验，则可以预期使用类似AI的方法显着提高控制性能。本文提出了一种称为“虚拟时间响应的迭代增益评估和重新设计”（V-Tiger）的新方法，它迭代：1）来计算基于一个 - 基于一个 - 输入某个控制器时闭环系统的虚拟时间响应拍摄实验数据，2）从虚拟时间响应和3）以考虑稳定性边缘来评估和重新设计控制器增益的过冲和稳定时间。

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