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At present, bio-inspired geomagnetic navigation is mostly based on evolutionary strategy, which requires long navigation time and low efficiency. To solve this problem, a bio-inspired geomagnetic navigation method for AUV based on evolutionary gradient search is proposed. Combining the bionic evolutionary search algorithm with the classical gradient algorithm to search the function extremum can not only ensure the global optimization of the search, but also have fast convergence, which can improve the efficiency of bio-inspired geomagnetic navigation. The simulation results show that this method does not need prior geomagnetic information and can complete navigation tasks according to the geomagnetic trend. Comparing with the evolutionary search strategy, the effectiveness and superiority of the evolutionary gradient search strategy are verified.

Priori geomagnetic information is important to the geomagnetic navigation. However in practice, the precision of the geomagnetic information is a greatly constraint to the development of the geomagnetic navigation. In order to solve this problem, this paper present a geomagnetic gradient bionic navigation method based on parallel approach without any priori information. Inspired by the evidence that many creatures can navigate using the Earth magnetic field, the navigation process can be considered as a convergence of multi-objective problem, and develop the bionics navigation model. By introducing the parallel approach method to the navigation process, the heading angle can be estimated with the information of magnetic field gradient. The simulation results show the proposed method is able to navigation effectively without magnetic priori information, just rely on the actual geomagnetic measurement, which has implies potential application in the future.

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.