| Aerodynamical parameters in longitudinal model of a certain type of aeroplane are identified in the paper. Longitudinal movement linear and non-linear equation are adopted here as identification model based on analysis of aeroplane characteristics, which is verified by means of the data actually acquired from flight tests. Moreover ,discussion and analysis are further made pointing the identification results and the problems found in identification process.1. After choosing the model for identifying, in view of the characteristics of the measured data and the requirement of parameter identification ,recognition,rejection and rectification unreasonable data is the first job in this part, then a low pass filter is designed to filter high-frequency noise in data, and smooth data by means of moving-orthogonal polynomial smoother algorithm which is put forward by the author, this method is somewhat better in avoiding the linear equationgs when we seek equation roots with the method of reverse matrix .2. Distinct identification methods are adopted according to different models. At the first, the subsystem of non-linear model is indetified with method of LS, longitudinal linear model is identified in Maximum Likelihood (M.L) algorithm. In the second, parameter identification to non-linear model is presented by means of ML and Extended Kalman Filter (E.K.F) method, in allusion to the contradiction between computing efficiency and the precision of identification, an Extended Quasi-Linear Optimum Smoothing Filter (E.Q.L.O.S.F) is advanced in this thesis, the precision of identification is obviously enhanced with no more additive calculation. At last, the results of above three algorithms are combined and ptimized based on genetic algorithm.3. In order to fleetly and exactly get the results of identification, at the same time ruduce the requirement of speciality level for users, the software about pre-processing flight test data and identifying aerodynamical parameters is introduced. |
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