Industrial motors are driven by proportional–integral–derivative controllers to simultaneously achieve rapid tuning and excellent control performance using precision control technology. However, existing automatic and manual tuning methods have limitations in providing optimal performance. Therefore, securing customized optimal gains that can induce the user's desired response is essential. In this study, Bayesian optimization techniques were applied to search for optimal gains and observed changes in control performance resulting from the adjustment of weight ratios within the objective function. The experimental results confirmed that response characteristics can be effectively controlled by tuning these weights. This study demonstrates the potential for designing customized control responses that consider user requirements.
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Kim et al. (2026) studied this question.
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