Minimum Energy Control of Quadrotor UAV: Synthesis and Performance Analysis of Control System with Neurobiologically Inspired Intelligent Controller (BELBIC)
[ 1 ] Instytut Robotyki i Inteligencji Maszynowej, Wydział Automatyki, Robotyki i Elektrotechniki, Politechnika Poznańska | [ P ] pracownik
2022
artykuł naukowy
angielski
- UAV
- quadrotor
- optimization
- minimum energy control
- brain emotional learning
- BELBIC
EN There is a strong trend in the development of control systems for multi-rotor unmanned aerial vehicles (UAVs), where minimization of a control signal effort is conducted to extend the flight time. The aim of this article is to shed light on the problem of shaping control signals in terms of energy-optimal flights. The synthesis of a UAV autonomous control system with a brain emotional learning based intelligent controller (BELBIC) is presented. The BELBIC, based on information from the feedback loop of the reference signal tracking system, shows a high learning ability to develop an appropriate control action with low computational complexity. This extends the capabilities of commonly used fixed-value proportional–integral–derivative controllers in a simple but efficient manner. The problem of controller tuning is treated here as a problem of optimization of the cost function expressing control signal effort and maximum precision flight. The article introduces several techniques (bio-inspired metaheuristics) that allow for quick self-tuning of the controller parameters. The performance of the system is comprehensively analyzed based on results of the experiments conducted for the quadrotor model.
13.10.2022
7566-1 - 7566-23
Article number: 7566
CC BY (uznanie autorstwa)
otwarte czasopismo
ostateczna wersja opublikowana
13.10.2022 (Data domniemana)
w momencie opublikowania
publiczny
140
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