Multivariable adaptive control based consensus flight control system for UAVs formation

Abstract Formation flight contributes to improving the attack, reconnaissance and survival ability of the multiple unmanned aerial vehicles (UAVs). This paper studies a multivariable adaptive control based consensus flight method for UAVs formation. A majority of existing research is focused on the leader-following consensus problem assuming that only the parameters of followers are uncertain. However, they do not consider the leader dynamic uncertainty and the unknown external disturbances. Therefore, this paper addresses the problem of the UAVs consensus flight control with parametric uncertainties and unknown external disturbances for both the leader and follower. A multivariable model reference adaptive control (MRAC) based consensus flight control scheme is designed for UAVs formation, which enables the follower UAV to track the leader UAV. The stability of the multivariable MRAC based consensus flight control system is analyzed. Simulation results show that the proposed adaptive consensus flight control scheme has stronger robustness and adaptivity than the fixed control scheme.

[1]  Derek James Bennet,et al.  Autonomous three-dimensional formation flight for a swarm of unmanned aerial vehicles , 2011 .

[2]  Jiang Ju,et al.  Monte Carlo approach to the analysis of UAVs control system , 2014, Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.

[3]  Dan Wang,et al.  Distributed model reference adaptive control for cooperative tracking of uncertain dynamical multi‐agent systems , 2013, IET Control Theory & Applications.

[4]  S. Darbha,et al.  Sampling-Based Path Planning for a Visual Reconnaissance Unmanned Air Vehicle , 2012 .

[5]  Gang Tao,et al.  Adaptive control of piecewise linear systems: The state tracking case , 2012, Proceedings of the 2010 American Control Conference.

[6]  Yu Liu,et al.  A multivariable MRAC scheme with application to a nonlinear aircraft model , 2011, Autom..

[7]  Gao Chen,et al.  Information fusion distributed navigation for UAVs formation flight , 2014, Proceedings of 2014 IEEE Chinese Guidance, Navigation and Control Conference.

[8]  Randal W. Beard,et al.  A decentralized scheme for spacecraft formation flying via the virtual structure approach , 2003, Proceedings of the 2003 American Control Conference, 2003..

[9]  Lorenz A. Schmitt,et al.  Collision-Avoidance Framework for Small Fixed-Wing Unmanned Aerial Vehicles , 2014 .

[10]  K. Khorasani,et al.  Adaptive formation control of UAVs in the presence of unknown vortex forces and leader commands , 2006, 2006 American Control Conference.

[11]  Ya Zhang,et al.  An adaptive backstepping design for formation tracking motion in an unknown Eulerian specification flowfield , 2017, J. Frankl. Inst..

[12]  Daobo Wang,et al.  UAV flight trajectory control based on information fusion control method , 2010, 2010 International Conference on Networking, Sensing and Control (ICNSC).

[13]  Eugene Lavretsky,et al.  Combined/Composite Model Reference Adaptive Control , 2009, IEEE Transactions on Automatic Control.

[14]  Yingmin Jia,et al.  Adaptive leader-following consensus control of multi-agent systems using model reference adaptive control approach , 2012 .

[15]  Choon Seong Chua.  Generic UAV modeling to obtain its aerodynamic and control derivatives , 2008 .

[16]  Dan Wang,et al.  Adaptive Dynamic Surface Control for Formations of Autonomous Surface Vehicles With Uncertain Dynamics , 2013, IEEE Transactions on Control Systems Technology.

[17]  Mario Innocenti,et al.  Dynamic and control issues of formation flight , 2004 .

[18]  Sai-Ming Li,et al.  GLOBALLY STABLE AUTOMATIC FORMATION FLIGHT CONTROL IN TWO DIMENSIONS , 2001 .

[19]  Gang Tao,et al.  Aircraft Turbulence Compensation Using Adaptive Multivariable Disturbance Rejection Techniques , 2015 .

[20]  Irene M. Gregory,et al.  Predictor-Based Model Reference Adaptive Control , 2009 .

[21]  Gang Tao,et al.  Multivariable adaptive control: A survey , 2014, Autom..

[22]  Gang Sun,et al.  Distributed Neural Network Control for Adaptive Synchronization of Uncertain Dynamical Multiagent Systems , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[23]  Ju Jiang,et al.  Cooperative path replanning method for multiple unmanned aerial vehicles with obstacle collision avoidance under timing constraints , 2015 .

[24]  Bin Zuo,et al.  UAV tight formation flight modeling and autopilot designing , 2004, Fifth World Congress on Intelligent Control and Automation (IEEE Cat. No.04EX788).

[25]  Mario Innocenti,et al.  Autonomous formation flight , 2000 .

[26]  Zan-Zan Wang,et al.  A geometric extension design for spherical formation tracking control of second-order agents in unknown spatiotemporal flowfields , 2017 .

[27]  Z. Zhen,et al.  Multivariable adaptive distributed leader-follower flight control for multiple UAVs formation , 2017 .

[28]  Daizhan Cheng,et al.  Leader-following consensus of multi-agent systems under fixed and switching topologies , 2010, Syst. Control. Lett..

[29]  Gang Tao,et al.  Adaptive Control Design and Analysis , 2003 .

[30]  Yue Xu,et al.  Adaptive control for leader-following consensus problem , 2016, 2016 IEEE Chinese Guidance, Navigation and Control Conference (CGNCC).

[31]  Anuradha M. Annaswamy,et al.  Design and Verification of an Adaptive Controller for the Generic Transport Model , 2009 .

[32]  浦黄忠，等,et al.  Flight Control System of Unmanned Aerial Vehicle , 2015 .

[33]  Chen Gao,et al.  A self-organized search and attack algorithm for multiple unmanned aerial vehicles , 2016 .