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Aiming at the high-speed flight of the UAVs cooperative formation, when a single UAV has occurred, need to exit the formation flight and be close or super close to form of the formation quickly. A fast close cooperative formation controller design method is proposed to make up for low the fighting robustness, and be shortcomings of timeliness poorly and analyze the dynamic characteristic of UAV formation flight. Taking the external factors known into consideration, setting up for the longitude maneuver of nonlinear thrust vector and unsteady aerodynamic model, according to the formation velocity, flat tail rudder angle and thrust vector and pitch angle velocity for corresponding input commend signals for the controller to research the dynamic characteristic of UAV formation flight. Meanwhile, the formation flight distance error is the convergence to a fixed value, and the stability of the cooperative formation flight is good. The simulation of results show that the controller can effectively improve the speed of the close or super close to formation, and maintain the stability of the formation flight, which provides a method of the close or super close formation flight controller design.

To deal with the problem of the difficult optimization search and expensive computational cost caused by large-scale design variables, the hierarchical optimization design system based on the global sensitivity analysis method is established in this paper. The M-OAT method is used to analyze the global sensitivity of the design variables, according to the sensitivity information to layer design variables, then optimize the design variables in each hierarchy. Through the study of the hierarchical optimization design of airfoils and wings, compared with the normal parameter optimization design system, the hierarchical optimization design system based on the global sensitivity analysis method can reduce effectively the number of design variables in a single optimization, reduce the difficulty of the optimization search, improve the convergence speed of the optimization, gain better optimization results at the same time. For optimization design with large-scale design variables, the hierarchical optimization design system based on the global sensitivity analysis method is a sort of effective ways of design.