针对飞行模拟器经典洗出算法参数设置保守、运动空间有限和模拟逼真度不足的问题。根据人体前庭系统感知原理,引入带通滤波分路对经典算法的结构重新设计,结合粒子群算法(PSO)对结构改进前后的洗出算法各通道滤波器自然截止频率进行优化。然后在Matlab/Simulink中建立联合仿真模型,结果表明：经PSO优化的两算法在感知相位误差、运动范围方面均有良性变化,而改进洗出算法提升效果更明显且具有更好的参数寻优性能,有效的提高了飞行模拟器的动感逼真度。

To solve the problems of conservative parameter setting, limited motion space, and insufficient simulation fidelity of the classic washout algorithm of the flight simulator. Based on the perception principle of the human vestibular system, the bandpass filtering shunt was introduced to redesign the structure of the classic algorithm, and the particle filter algorithm (PSO) was used to optimize the natural cut-off frequency of each channel filter of the washout algorithm before and after the structural improvement. Then, a joint simulation model is established in Matlab / Simulink. The results show that the two algorithms optimized by PSO have benign changes in perceived phase error and range of motion, and the improved washout algorithm has more obvious effects and better parameter optimization performance, effectively improving the dynamic fidelity of the flight simulator.

TP391.9

国家自然科学基金委员会与中国民用航空局联合资助项目(U1733128)。