Fuzzy clustering-based envelope division and gain scheduling method for flying-wing unmanned aerial vehicle

Abstract

The invention discloses a fuzzy clustering-based envelope division and gain scheduling method for flying-wing unmanned aerial vehicle, and solves the problem that a conventional linear interpolation gain scheduling mechanism cannot deal with the nonlinear characteristic of a large envelope of an unmanned aerial vehicle. According to the method, a fuzzy clustering algorithm is adopted to obtain a typical flight state and a membership matrix of an unmanned aerial vehicle, and an optimal flight envelope division mechanism is determined; and the speed and the dynamic pressure are selected as scheduling variables, and a T-S fuzzy gain scheduling strategy is designed based on a Sigmoid type membership function. According to the method, continuous output and stable transition of unmanned aerial vehicle control gain are achieved, and stable flight control of the unmanned aerial vehicle in a full envelope range is ensured.

Description

technical field [0001] The invention relates to a novel envelope division and control gain scheduling method of a flying-wing unmanned aerial vehicle, belonging to the technical field of aircraft flight control. Background technique [0002] The flight envelope of the flying-wing UAV is large, and the aerodynamic force and moment vary widely with height and dynamic pressure. The nonlinear and unmodeled dynamic characteristics seriously affect the quality and stability of the flight control. The traditional fixed control structure and control parameters The method can no longer meet the control requirements of flying wing UAV. The non-linear problem in the flight process of the flying wing UAV in the full envelope needs to be solved urgently. [0003] Linear gain scheduling solves the problem of poor adaptability of fixed control law, but there are still the following problems to be solved: how to select a typical operating point, the traditional method is to select the oper...

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Problems solved by technology

[0003] Linear gain scheduling solves the problem of poor adaptability of fixed control law, but there are still the following problems to be solved: how to select a typical operating point, the traditional method is to select the operating point by trial and error, which is time-consuming and extremely dependent on the designer experience; how to schedule the controller parameters, the method of obtaining the controller parameters through linear interpolation, due to the unmodeled dynamic characteristics of the UAV, the control quality is poor or even unstable in certain flight states

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