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Current aerodynamic parameter identification methods take the consistency between the response of the motion model reconstructed with the identified aerodynamic parameters and flight data as an optimization index. Since there is only one index constraint in aerodynamic parameter optimization, and more than ten aerodynamic parameters to be identified simultaneously have different sensitivity to the optimization index, the accuracy of identification results of parameters with low sensitivity is poor, especially for those with small absolute value. To solve these problems, a new idea, having aerodynamic parameters solved by balance equations and identified in stages, is proposed. Based on the motion characteristics of different lateral-directional maneuvers, the scheme of combined maneuvers is designed, and the step-by-step identification procedure is established. An estimation method of angular acceleration with angular velocity equivalent model is proposed to solve the problem that angular acceleration cannot be measured directly. A lateral-directional aerodynamic parameter identification method using segmented adaptation of flight data and identification models is established based on the identifiability of flight data. The lateral-directional aerodynamic parameter identification results of a large civil aircraft show the identification results can be obtained with higher accuracy by adopting the proposed identification method and the flight test scheme.

This paper is dedicated to solving the model reconstruction problem of Boolean networks (BNs) based on incomplete information. By resorting to semi-tensor product, the issue of finding logical functions is converted into designing corresponding structure matrices. In line with desired attractors, two circumstances, standard BNs and delayed BNs, are taken into consideration, and several new results are presented. For the model reconstruction of standard BNs, an algebraic condition is put forward and an algorithm is developed for reconstructing unknown logical functions. For the model reconstruction of delayed BNs, an augmented system is deduced, based on which, several criteria and the corresponding algorithm are proposed. Finally, as an application to gene regulatory networks, the results obtained in this paper are used to analyze the WNT5A network and the apoptosis network.