针对国内大型飞机结冰防护需求，开展针对大型结冰研究样机的H∞算法参数辨识结冰探测研究。首先通过参数调节选取一组合适的H∞算法参数，利用考虑测量噪声的结冰研究样机飞行仿真数据验证H∞算法的辨识能力，由结果对比发现辨识算法能够跟踪飞机气动导数随结冰累积过程的变化趋势，辨识精度较高，其最大归一化平方根（RMS）误差仅为真值的11%；分析了H∞算法对81种不同结冰累积过程的辨识能力，通过结果分析发现结冰累积时间较长且结冰速度较慢的情况辨识效果较差，结冰累积时间在100~300 s之间辨识精度较高；最后利用蒙特卡罗仿真分析了不同测量噪声大小对H∞算法辨识精度和跟踪延时的影响，给出了3个纵向气动导数在随机误差影响下的辨识误差和跟踪延时的统计结果，发现在给定噪声标准差变化范围内，升力和俯仰力矩关于迎角的导数能够得到较为准确的辨识结果，二者的归一化平方根误差均值仅为各自真值的1.8%和4%，其预报延时均值最大仅为3 s和9.5 s。
H∞ parameter identification for inflight icing detection is discussed in this paper for the development of the de-icing and anti-icing system of a large icing research prototype. First, the H∞ method parameters are tuned and chosen.Then the method is evaluated by the airplane's longitudinal simulation data with measurement noises. The identification results show that the method can track the time-varying aerodynamic parameters in the ice accretion process, and that the maximum normalized Root Mean Square(RMS) error 11% indicates high accuracy of identification.The 81 different ice accretion processes are then identified by the H∞ method.The results show that when the ice accretion process changes slowly and lasts long the identification accuracy is relatively poor, and that when the ice accretion time is between 100-300 s the accuracy is relatively high. The accuracy of H∞ algorithm in the different standard deviations of measurement noises is analyzed by Monte Carlo simulation.The error and delay statistic characteristics of the three longitudinal aerodynamic derivatives show that the identification accuracy of derivatives of lift and pitching moment to angle of attack is relatively high as their mean normalized RMS errors are 1.8% and 4% respectively, and their mean delays are 3 s and 9.5 s respectively.
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