A Novel Algorithm Based on Bayesian Optimization for Run-to-Run Control of Short-Stroke Reluctance Actuators

摘要

There is great interest in minimizing the impact forces and bounces of reluctance actuators during commutations, in order to reduce acoustic noise and mechanical wear. In that regard, a model-free run-to-run control algorithm is presented to decrease the contact velocity, by exploiting the repetitive operations of these devices. The problem is mathematically formulated and the algorithm is expressed in pseudocode. As the main contribution of this paper, a search method is proposed for the run-to-run strategy based on Bayesian optimization. Adjustments are carried out for its application in run-to-run control, e.g. the removal of stored points and the definition of a new acquisition function. For validation, simulations are performed using a dynamic model of a commercial solenoid valve, and defining the input parametrization. The results show the improvement of the proposed method with respect to a state-of-the-art search.