Dynamic Property Analysis And Automation Design Of Operation Point For UAV

Due to the complex nonlinear characteristic of the Unmanned Aerial Vehicle (UAV), it is a key point to design flight control laws that could satisfy the requirements of UAV. The most common systematic approach to the design of flight control laws is based on the linearization model of UAV in different operating points. Therefore, the chosen operating points are very cristical for their affection to flight quality directly. Based on the analysis of the key factors to the operating points, the mechanism of the selecting operating points is studied in detail. And the automation selection is finished by fuzzy clustering technology.The 6-dof nonlinear mathematical model for UAV is constructed firstly in Matlab/Simulink environment in order to obtain the UAV envelope. After the model is linearized on UAV envelope using the small perturbation theory, two kinds of parameters are chosen as the cluster prototype, which is consisted of damping ratio, oscillator frequency and the aerodynamic derivatives.Based Gustafson-Kessel algorithm, two kinds of cluster prototyes are applied for clustering. The feasibility of clustering results is verified by the location of the zeros/poles, damping ratio and the oscillator frequency of UAV.In order to verify the validation of automation selection, gain scheduling controller is developed by combination of control parameters and the fuzzy membership matrix. The nonlinear simulation on the whole envelope is carried out in Matlab/ Simulink environment, and simulation results show that the gain-scheduling controller meets the quality requirement of UAV. Therefore, the feasibility and validation of automation selection technology of operating points is conformed.