The Estimation Method Of Parameter Identification For Aircraft Stochastic Control System

In order to make the aircraft can accurately operate according to the preset orbit, in the phase of aircraft design, we desperately need to apply the estimation method of parameter identification to aircraft stochastic control system. The estimation of aircraft flight test data and aircraft orbital parameter identification technology has been increasingly accepted and importance attached by people, and has been an important means of determining the characteristics of the aircraft orbit. It can not only provide orbital mathematical model reflects the actual flight characteristics and the external environment for aircraft design, but also can verify the result of theoretical calculation and correct the ground test data. Therefore, to explore the orbit parameter identification method has an important theory significance and actual value. There are two main research fields in this paper: first, the application of least square method in parameter identification in the process of orbit for spacecraft stochastic control system, second, the application of Kalman filter theory in parameter identification for Multi tube rocket navigation stochastic control system. The basic content as follows:(1) Study on the method of accurate estimation of prior parameter based on theleast square method;(2) Establish the barycenter model of the spacecraft control system;(3) The Application of Least Square Method in the Identification of StochasticControl System;(4) Study on extend filtering theory of continuous linear, nonlinear based onKalman filter;(5) Establish the Multi tube rocket stochastic control system model;(6) Determine the initial state of the Multi tube rocket based on thequasi-linear Kalman filter;(7) Take MATLAB as the tool to simulate and analysis the experiment. Through the application of identification in the stochastic control system,and analysis the design and key process, get the simulation curve bysimulation, the results show that both of the two estimation methods of parameteridentification for aircraft stochastic control system are have a high identification accuracy and a good convergence, can be extended to other aircraft stochastic control systems for its strong practical value.