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传统飞机驾驶员最优控制模型采用卡尔曼滤波,无法反映飞行员对未知环境的适应能力,在飞行试验中有时存在与飞行员实际评分不一致的现象。为此,采用自适应状态估计理论对传统驾驶员最优控制模型进行了修正,提出了基于自适应飞机驾驶员最优控制模型的飞行品质评估方法。通过对比飞行试验和模型仿真结果表明了这一评估方法的可行性,所采用的修正加权系数得到的评分结果精度更高。研究结果表明,飞行员评分与指标函数加权系数比值相关,采用变化加权系数比值得到的评估结果与飞行员实际评分更为吻合。随着飞机动态特性的变差,这一比值将不断增大,飞行员将投入更多精力进行飞行状态监测,进而导致飞行员降低对飞行品质的主观评价。
The traditional pilot’s optimal control model using Kalman filter can not reflect the ability of pilots to adapt to the unknown environment. In the flight test, there are some discrepancies with the pilot’s actual score. Therefore, adaptive state estimation theory is used to modify the traditional driver’s optimal control model, and a flight quality assessment method based on the adaptive pilot’s optimal control model is proposed. By comparing the results of flight test and model simulation, the feasibility of this evaluation method is demonstrated. The correction weighting coefficient is used to get a higher accuracy of the scoring result. The results show that the pilot rating is related to the ratio of the index function weighting factors, and the assessment results obtained by using the change weighting coefficient ratio are in good agreement with the pilot actual rating. As the dynamic characteristics of the aircraft deteriorate, this ratio will continue to increase, and pilots will devote more effort to flight status monitoring, which will result in pilots lowering the subjective assessment of flight quality.