Sensor Fault Diagnosis and Fault Tolerant Control of Quadrotor UAV Based on Genetic Algorithm

The quadrotor drone is small in size and light in weight, the mechanical structure is simple, and the requirements for the working environment are low. The development of a quadrotor UAV technology is also the focus of the current technical personnel. The author proposes a four-rotor UAV sensor faul...

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Bibliographic Details
Published in:Journal of sensors 2022-03, Vol.2022, p.1-8
Main Authors: Hua, Lianghao, Zhang, Jianfeng, Li, Dejie, Xi, Xiaobo, Shah, Mohd Asif
Format: Article
Language:English
Subjects:
Aircraft
Back propagation networks
Background noise
Design
Drones
Expected values
Failure
Fault diagnosis
Fault tolerance
Genetic algorithms
Mathematical models
Neural networks
Sensors
Training
Unmanned aerial vehicles
Weight reduction
Working conditions
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Summary:The quadrotor drone is small in size and light in weight, the mechanical structure is simple, and the requirements for the working environment are low. The development of a quadrotor UAV technology is also the focus of the current technical personnel. The author proposes a four-rotor UAV sensor fault diagnosis and fault-tolerant control based on genetic algorithm and introduces common sensor failures, and based on the improved BP neural network of the GA algorithm, the genetic algorithm is improved. This paper uses a classical BP algorithm, a classical GA-BP algorithm, and an improved GA-BP algorithm for training. Using a total of 150 sets of training data and training function using LevenbregMarquardt (trainlm), MeanSquaredError (performance function using mse), in the same noise background, the improved GA-BP algorithm has the highest detection rate, the classical GA-BP algorithm followed, and classical BP algorithm is the worst. Therefore, using the improved GA-BP algorithm, various errors of the sensor can be detected quickly and accurately.
ISSN:1687-725X
1687-7268
DOI:10.1155/2022/8626722