Open AccessParameter tuning of active disturbance rejection control in quad tilt rotor based on particle swarm optimization
Author(s) -
Zhigang Wang,
Guangqiang Wu,
Jianbo Li
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1780/1/012023
Subject(s) - particle swarm optimization , control theory (sociology) , active disturbance rejection control , computer science , rotor (electric) , controller (irrigation) , mode (computer interface) , domain (mathematical analysis) , control (management) , algorithm , artificial intelligence , mathematics , engineering , nonlinear system , physics , mechanical engineering , mathematical analysis , agronomy , quantum mechanics , state observer , biology , operating system
The quad tilt rotor (QTR) has complex dynamics characteristics, especially in transition mode. It is difficult to model the QTR dynamics and the environmental factors have a great influence on it. To solve the problem of control in transition mode of QTR, this paper carries out the design of the controller based on active disturbance rejection control (ADRC). ADRC has many parameters to be tuned, and the coupling effect is more serious, so it is very difficult to tune parameters. Particle swarm optimization (PSO) algorithm has faster computing speed and better global search ability in dynamic and multi-objective optimization. So, using PSO algorithm to realize self-tuning of ADRC parameters in ADRC parameters tuning. By comparing the control performance of ADRC before and after optimization, the rationality and effectiveness of ADRC parameters tuning algorithm in QTR are verified in both time domain and frequency domain.