基于运动试验平台的MOEA/D改进洗出算法仿真及试验

洗出算法参数的调整很大程度上影响其性能，针对目前经典洗出算法应用于飞行模拟器时参数调整的不足，提出一种基于MOEA/D多目标优化的改进洗出算法。将人体感知误差、洗出位移、模拟加速度误差作为优化目标，以运动空间为限制条件，采用基于分解的多目标优化算法对洗出算法参数进行同步寻优，并利用模糊隶属度函数得到最优解。为验证其有效性，建立飞行模拟器运动试验平台，将采用不同优化方法的洗出算法应用其中进行对比分析。仿真及试验结果表明，改进洗出算法归位反应时间最短，相位延迟降低3.5 s,稳定性提高30%,且修正了感觉峰值，优化了54.6%的工作空间，实现了模拟器在模拟极限运动时有足够的运动空间和更高的动感逼真度。

Simulation and experiments of MOEA/D improved washout algorithm based on motion test platform

The parameter adjustment of the washout algorithm greatly affects its performance. To address the shortcomings of the current classical washout algorithm when it is applied to flight simulators, an improved washout algorithm based on MOEA/D multi-objective optimization was proposed. Taking the human perception error, washout displacement and simulation acceleration error as the optimization objectives, and using the motion space as the restriction condition, the parameters of the washout algorithm were optimized synchronously by adopting the multi-objective optimization algorithm based on decomposition, and the optimal solution was obtained by using the fuzzy membership function. In order to verify the effectiveness of the improved algorithm, a flight simulator motion test platform was established and the washout algorithms with different optimization methods were applied to the platform for comparative analysis. Simulation and experimental results show that the improved algorithm had the shortest return reaction time. Moreover, the phase delay was reduced by 3.5 s, the stability increased by 30%, the sensory peak value was corrected, and the workspace was optimized by 54.6%, so that the simulator has enough movement space and higher dynamic fidelity when simulating extreme motion.