Distributed optimization of heterogeneous UAV cluster PID controller based on machine learning

Yan Li

doi:10.1016/j.compeleceng.2022.108059

Distributed optimization of heterogeneous UAV cluster PID controller based on machine learning

2022-07-01

23

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AI

DOI：10.1016/j.compeleceng.2022.108059

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Abstract

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To resolve the problem of membership value and the control effect reliant on expert knowledge, a PID control approach based on an adaptive fuzzy PID-UAV attitude controller is proposed. The experimental findings demonstrate that the Unmanned Aerial Vehicle (UAV) is stable at the desired height of 2 m within 6 s after takeoff, and that altitude control can be accomplished with a single PID controller. It has been established that the control system has the advantages of high precision and ease of implementation, but the fuzzy controller has the advantages of minimal overshoot and transient response, as well as the ability to achieve precise and rapid behaviour control. When obtaining continuous square wave instructions, fuzzy PID has more obvious advantages than regular PID. The system has superior tracking and antiinterference, can achieve stable control faster, and has great dynamic and static properties.

Keywords:

UAV

PID controller

Distribution optimization

Distributed optimization of heterogeneous UAV cluster PID controller based on machine learning

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