关键词: 多目标优化, 人工蜂群算法, 洗出算法, 参数优化, 动感逼真度

Abstract:

Addressing the issues such as signal loss, distraction, and bad wash-out effect caused by improper parameter selection in classic wash-out algorithms, an improved multi-objective artificial bee colony algorithm is proposed to optimize the filter parameters of the classical wash-out algorithm to improve the effect. For the problems in the initialization and local optimization of traditional swarm algorithm, Circle mapping and Pareto local optimization algorithm are introduced. The human perception error model, acceleration difference model, and displacement model are established, and the model function is used as the objective function, the parameters of the classical wash-out algorithm is optimized by the improved multi-objective artificial bee colony algorithm. A simulation model is established to simulate and verify the optimized wash-out algorithm, and a flight simulator motion test platform is applied to test and verify the algorithm. The results show that, with the optimized washout algorithm, the washout fidelity is effectively improved, the error peak is reduced, the phase delay is improved, and the motion space is saved.

Key words: multi-objective optimization, artificial bee colony algorithm, wash-out algorithm, parameter optimization, dynamic fidelity