Proportional integral derivative (PID) controllers are important and widelyused tools in system control. Tuning of the controller gains is a laborioustask, especially for complex systems such as combustion engines. To minimizethe time of an engineer for tuning of the gains in a simulation software, wepropose to formulate a part of the problem as a black-box optimization task. Inthis paper, we summarize the properties and practical limitations of tuning ofthe gains in this particular application. We investigate the latest methods ofblack-box optimization and conclude that the Covariance Matrix AdaptationEvolution Strategy (CMA-ES) with bi-population restart strategy, elitist parentselection and active covariance matrix adaptation is best suited for this task.Details of the algorithm's experiment-based calibration are explained as wellas derivation of a suitable objective function. The method's performance iscompared with that of PSO and SHADE. Finally, its usability is verified on sixmodels of real engines.
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