Multi-Objective Optimization and Global Design for Active Magnetic Dry Friction Damper Actuators

Abstract

To address the tradeoff among high force, fast response, and compact volume in active magnetic dry friction dampers, this paper proposes a systematic multi-objective optimization framework centered on an interpretable global design surface. A parametric analytical model mapping the electromechanical couplings is established and validated via ANSYS simulations. To solve the high-dimensional conflict, an improved genetic algorithm integrating an adaptive mutation strategy and a random immigration mechanism is developed, significantly enhancing global convergence and population diversity. The framework progresses from bi-objective to tri-objective optimization, executing high-precision explicit mathematical regressions on the generated Pareto fronts. Furthermore, a system-level transient dynamic validation under sudden unbalance is implemented on a benchmark rotor platform, rigorously verifying that the optimized actuator parameters (300 N, 2 ms) successfully suppress the initial peak amplitude by 20.39% and curtail the settling time by 73.58% compared to nonoptimized configurations. The results demonstrate that the proposed framework successfully transforms discrete optimization datasets into an invertible and continuous engineering decision surface, providing a reliable design paradigm for aerospace electromagnetic actuators.