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Journal of System Simulation

Abstract

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.

First Page

436

Last Page

448

CLC

TP391.9

Recommended Citation

Wang Hui, Peng Le. Improved Multi-objective Swarm Algorithm to Optimize Wash-out Motion and its Simulation Experiment[J]. Journal of System Simulation, 2024, 36(2): 436-448.

Corresponding Author

Peng Le

DOI

10.16182/j.issn1004731x.joss.22-1193

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