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	<updated>2026-04-20T18:02:14Z</updated>
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		<id>https://projectswiki.eleceng.adelaide.edu.au/projects/index.php?title=Projects:2019s2-23301_Robust_Formation_Control_for_Multi-Vehicle_Systems&amp;diff=12878</id>
		<title>Projects:2019s2-23301 Robust Formation Control for Multi-Vehicle Systems</title>
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		<updated>2019-09-22T06:59:12Z</updated>

		<summary type="html">&lt;p&gt;A1756542: &lt;/p&gt;
&lt;hr /&gt;
&lt;div&gt;[[Category:Projects]]&lt;br /&gt;
[[Category:Final Year Projects]]&lt;br /&gt;
[[Category:2019s2|23301]]&lt;br /&gt;
Abstract here&lt;br /&gt;
== Introduction ==&lt;br /&gt;
The formation behaviour&lt;br /&gt;
&lt;br /&gt;
=== Project team ===&lt;br /&gt;
==== Project students ====&lt;br /&gt;
* Abdul Rahim Mohammad&lt;br /&gt;
* Jie Yang&lt;br /&gt;
* Kamalpreet Singh&lt;br /&gt;
* Zirui Xie&lt;br /&gt;
==== Supervisors ====&lt;br /&gt;
*Peng Shi&lt;br /&gt;
*Cheng-Chew Lim&lt;br /&gt;
==== Advisors ====&lt;br /&gt;
*Xin Yuan&lt;br /&gt;
*Bing Yan&lt;br /&gt;
*Yuan Sun&lt;br /&gt;
*Yang Fei&lt;br /&gt;
&lt;br /&gt;
=== Objectives ===&lt;br /&gt;
Formation control of multi-agent systems (MASs) has been widely used for cooperative tasks in such applications as terrain exploration, mobile networks and traffic control. However, the communication-induced problems and the high failure risk of increasingequipment has created a number of challenges for the security of MASs. The  objective  of  this  project  is  to  design  a  robust  formation  control  strategy  for  a  multi-vehicle  system  against communication/physical failures (e.g., network attacks, link failures, packet dropouts, sensor/actuator faults). The  vehicles  are  designed  to  detect  the  local  environments  by  visual  navigation  and  achieve  a  self-organisation formation.  The  robust  fault-tolerant  control  strategy  is  investigated  to  deal  with  at  least  one  network  problem  or physical  failure.  The  effectiveness  of  the  formation  control  strategy  and  its  robustness  should  be  verified  by  both simulations  and  experiments.  Potential  applications  are  in  large  flexibility  MASs  and  high-security  Cyber-Physical Systems.Currently,  our  lab  is  equipped  with  a  multi-vehicle  platform,  consisting  of  quadrotors,  ground  robots  and  camera location systems. Algorithms are developed by either Matlab Code or C language. MATLAB, Simulink, OpenGL, Motive and Visual Studio are possiblesoftware to be chosen for this project .&lt;br /&gt;
&lt;br /&gt;
== Background ==&lt;br /&gt;
=== Topic 1 ===&lt;br /&gt;
&lt;br /&gt;
== Method ==&lt;br /&gt;
&lt;br /&gt;
== Results ==&lt;br /&gt;
&lt;br /&gt;
== Conclusion ==&lt;br /&gt;
&lt;br /&gt;
== References ==&lt;br /&gt;
[1] Wooldridge, M (2002). An Introduction to MultiAgent Systems. John Wiley &amp;amp; Sons. ISBN 978-0-471-49691-5&lt;br /&gt;
&lt;br /&gt;
[2] Balaji, P., &amp;amp; Srinivasan, D. (2010). An introduction to multi-agent systems. Studies in Computational Intelligence, 310, 1-27.&lt;br /&gt;
&lt;br /&gt;
[3] Hong-Jun M., &amp;amp; Guang-Hong Y. (2016). Adaptive Fault Tolerant Control of Cooperative Heterogeneous Systems With Actuator Faults and Unreliable Interconnections. IEEE Transactions on Automatic Control, 61(11), 3240-3255.&lt;br /&gt;
&lt;br /&gt;
[4] Oh k, Park M, &amp;amp; Ahn H. (2015). A survey of multi-agent formation control. Automatica, 53, 424-440.&lt;br /&gt;
&lt;br /&gt;
[5] Khatib, O. (1986). Real-Time Obstacle Avoidance for Manipulators and Mobile Robots. The International Journal of Robotics Research, 5(1), 90–98. https://doi.org/10.1177/027836498600500106&lt;br /&gt;
&lt;br /&gt;
[6] Autonomous Ground Vehicles Self-Guided Formation Control https://github.com/vitsensei/Trionychid-Formation-Control&lt;/div&gt;</summary>
		<author><name>A1756542</name></author>
		
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