Fault detection method of unmanned aerial vehicle flight control system

Abstract

The invention relates to a fault detection method of an unmanned aerial vehicle flight control system. Online detection of the fault of the actuator and the sensor of the fixed-ring unmanned aerial vehicle flight control system can be realized by the method. An unmanned aerial vehicle flight control system continuous nonlinear fault model is established on the basis of the unmanned aerial vehiclekinetic equation and the fault type; and then the unmanned aerial vehicle flight control system continuous nonlinear fault model is converted into an unmanned aerial vehicle flight control discrete time-varying fault model with the help of a nonlinear observer, and unmanned aerial vehicle flight control system fault detection is realized by using an equivalent space method. The robustness indicator is designed by aiming at the problem of poor robustness of the conventional equivalent space method under unknown interference so as to enhance the robustness of system fault detection. The extendedKalman filtering equation is utilized in the Krein space to realize recursive computation of the residual evaluation function to reduce the computational burden by aiming at the problem of high computational burden of online fault detection of the conventional equivalent space method. According to the method, quick alarm of the fault of the sensor and the actuator of the unmanned aerial vehicle can be realized so as to provide an effective basis for fault detection of the unmanned aerial vehicle flight control system.

Description

technical field [0001] The invention relates to a fault detection method for a UAV flight control system, which is used for online fault detection of sensors and actuators in the UAV flight control system, and belongs to the technical field of UAV system fault diagnosis. Background technique [0002] In recent years, as an important branch of analytical redundancy, model-based fault detection methods have been widely used in the fault detection of UAV flight control systems, and have achieved fruitful results. The model-based fault detection method uses the inherent analytical relationship between the input and output variables of the system, obtains the residual sequence through the actual output of the system and the theoretical output of the algorithm, and judges the fault state of the system accordingly. It can deeply understand the dynamic performance of the system according to the analytical mathematical model of the system. The advantage is that the calculation amount...

AI Technical Summary

Problems solved by technology

Among them, in order to reduce the problem of poor robustness of the traditional equivalent space method under the condition of unknown external non-white noise interference, the robustness of the fault detection is improved by using the optimization of the robust index; for the fault detection calculation of the traditional equivalent space method For large amount of problems, use Krein space projection to reduce the calculation amount of fault detection

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