Abstract：To address the issues of strong subjectivity and low optimization efficiency in traditional empirical tuning methods for proportional integral (PI) controller parameters, this paper proposes a multi-objective hybrid elite particle swarm optimization (MOHEPSO) algorithm for parameter optimization of the three-phase rectifier system controller. This method integrates three core modules: an entropy-weighted method for elite particle selection (enhancing global search through information entropy minimization), a roulette wheel mechanism for high-quality particle optimization (guiding refined local search), and a dominance-based adaptive adjustment strategy (dynamically balancing global/local optimization capabilities). These components collectively construct an intelligent algorithmic framework with synergistic optimization characteristics. Simulation results demonstrate that, compared to conventional multi-objective particle swarm optimization (MOPSO) and particle swarm optimization (PSO), the proposed method achieves better performance in Matlab/Simulink simulations. Significant improvements are observed in key metrics including settling time, overshoot, and steady- state error, thereby validating its remarkable advantages in power electronics system optimization.
邢云, 王子为. 基于多目标混合精英粒子群算法的三相整流系统控制器参数优化[J]. 电气技术, 2026, 27(3): 1-12.
XING Yun, WANG Ziwei. Optimization of parameters for a three-phase rectifier system controller based on multi-objective hybrid elite particle swarm optimization algorithm. Electrical Engineering, 2026, 27(3): 1-12.
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2026, Vol. 27 
