Multi-Objective Optimization of 12-Pole Radial Active Magnetic Bearings with Preference-Based MOEA/D Algorithm

In this paper, the multi-objective optimization of the 12-pole radial active magnetic bearing (RAMB) is investigated. In the optimization of the RAMB, the decision-maker is more interested in the Pareto-optimal solutions in a certain region. This paper proposes a decomposition-based and preference-based multi-objective evolutionary algorithm (MOEA/D-Pref). The proposed MOEA/D-Pref not only allows the number of Pareto-optimal solutions to be more concentrated in the region of interest but also preserves solutions in other regions. These preserved solutions enable decision-makers to observe a more complete Pareto front, thus gaining more comprehensive insights. In this paper, a mathematical model of the 12-pole RAMB is established, and, with the help of this model and the proposed algorithm, the optimal design of the 12-pole RAMB is completed. The difference between the current stiffness coefficients of the optimized RAMB, calculated by the proposed algorithm and by the finite element method, is 2.3%. The difference between the displacement stiffness coefficient of the optimized RAMB as calculated by the proposed algorithm and by the finite element method is 3.9%. These differences, being less than 4%, are relatively low and verify the reliability of the mathematical model established.