Next Article in Journal
Smoothness of Gait in Healthy and Cognitively Impaired Individuals: A Study on Italian Elderly Using Wearable Inertial Sensor
Next Article in Special Issue
UAV Positioning Mechanisms in Landing Stations: Classification and Engineering Design Review
Previous Article in Journal
Railway Axle Condition Monitoring Technique Based on Wavelet Packet Transform Features and Support Vector Machines
Previous Article in Special Issue
Flight and Interaction Control of an Innovative Ducted Fan Aerial Manipulator
 
 
Article

Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System

1
Department of electrical engineering, College of engineering, University of Baghdad, Baghdad 10001, Iraq
2
Robotics and Internet-of-Things Lab (RIOTU), Prince Sultan University, Riyadh 11586, Saudi Arabia
3
Faculty of Computers and Artificial Intelligence, Benha University, Benha 13518, Egypt
4
Department of Control and Systems Engineering, University of Technology, Baghdad 10001, Iraq
*
Author to whom correspondence should be addressed.
Sensors 2020, 20(12), 3576; https://doi.org/10.3390/s20123576
Received: 20 April 2020 / Revised: 16 June 2020 / Accepted: 17 June 2020 / Published: 24 June 2020
(This article belongs to the Special Issue Unmanned Aerial Vehicle Control, Networks, System and Application)
A consensus control law is proposed for a multi-agent system of quadrotors with leader–follower communication topology for three quadrotor agents. The genetic algorithm (GA) is the proposed optimization technique to tune the consensus control parameters. The complete nonlinear model is used without any further simplifications in the simulations, while simplification in the model is used to theoretically design the controller. Different case studies and tests are done (i.e., trajectory tracking formation and switching topology) to show the effectiveness of the proposed controller. The results show good performance in all tests while achieving the consensus of the desired formations. View Full-Text
Keywords: hybrid control system; nonlinear PID; active disturbance rejection control; quadrotor system; unmanned aerial vehicle hybrid control system; nonlinear PID; active disturbance rejection control; quadrotor system; unmanned aerial vehicle
Show Figures

Figure 1

MDPI and ACS Style

Najm, A.A.; Ibraheem, I.K.; Azar, A.T.; Humaidi, A.J. Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System. Sensors 2020, 20, 3576. https://doi.org/10.3390/s20123576

AMA Style

Najm AA, Ibraheem IK, Azar AT, Humaidi AJ. Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System. Sensors. 2020; 20(12):3576. https://doi.org/10.3390/s20123576

Chicago/Turabian Style

Najm, Aws Abdulsalam, Ibraheem Kasim Ibraheem, Ahmad Taher Azar, and Amjad J. Humaidi. 2020. "Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System" Sensors 20, no. 12: 3576. https://doi.org/10.3390/s20123576

Find Other Styles
Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Access Map by Country/Region

1
Back to TopTop