Vol.63, No.1, 2020, pp.469-487, doi:10.32604/cmc.2020.05746
OPEN ACCESS
ARTICLE
Sliding-Mode PID Control of UAV Based on Particle Swarm Parameter Tuning
  • Yunping Liu1, 2, *, Xingxing Yan1, Fei Yan1, Ze Xu1, Weiyan Shang3
1 School of Automation, Nanjing University of Information Science and Technology, Collaborative Innovation Center of Atmospheric Environment and Equipment, Nanjing, 210044, China.
2 Department of Mechanical and Industrial Engineering, Ryerson University, Toronto, M5B 2K3, Canada.
3 Department of Mechanical and Manufacturing Engineering, University of Manitoba, Winnipeg, R3T 5V6, Canada.
* Corresponding Author: Yunping Liu. Email: liuyunping@nuist.edu.cn.
Received 10 January 2019; Accepted 23 January 2019; Issue published 30 March 2020
Abstract
Due to the coupled motion between the rotor unmanned aerial vehicle (UAV) and the manipulator, the underactuation characteristics of the system itself, and the influence of external uncertainties, the stability of the rotor UAV’s manipulator control system is difficult to control. Based on the dynamic model of the rotor UAV, the stability of the whole UAV manipulator control system is improved by using the piecewise cost function, the compression factor particle swarm optimization (PSO) algorithm and the sliding mode PID to establish the sliding mode PID control stability method based on the PSO. Compared with the sliding mode PID control method, this method solves the serious buffeting problem in the sliding mode control, reduces the influence of the external disturbance and realizes the attitude stabilization control of the UAV manipulator quickly and accurately, thus shortens the system adjustment time and improves the anti-interference ability.
Keywords
Manipulator, dynamic model, compression factor, particle swarm, sliding mode PID, UAV.
Cite This Article
Liu, Y., Yan, X., Yan, F., Xu, Z., Shang, W. (2020). Sliding-Mode PID Control of UAV Based on Particle Swarm Parameter Tuning. CMC-Computers, Materials & Continua, 63(1), 469–487.
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