An Adaptive Approach for Multi-Agent Formation Control in MANET Based on CPS Perspective

From Cyber Physical System (CPS) perspective, it is nature for the system to tightly couple the communications and computing aspects with its physical dynamics. In this paper, we investigate this characteristic for multi-agent formation control in Mobile Ad-hoc Network (MANET). We manage to measure the real time wireless network congestion, implement a wireless QoS mechanism to provide different network channel access priorities and come up with the emergency calculation. Based on these, we present our adaptive approach for formation control. To examine the benefit of our approach, we use a co-simulation tool that we have developed for evaluating networked control & cyber physical system to study a specific scenario, in which five follower agents plus one leader perform a specific formation within a MANET with different congestion conditions. Through simulation experiments, it is showed that our approach could adaptively adjust sample periods and network channel access priorities according to real time dynamics emergencies and the network traffics condition, so as to optimize network utilization and improve the formation control performance

[1]  Tucker R. Balch,et al.  Behavior-based formation control for multirobot teams , 1998, IEEE Trans. Robotics Autom..

[2]  Jiangping Hu,et al.  Leader-following coordination of multi-agent systems with coupling time delays , 2007, 0705.0401.

[3]  Qun Li,et al.  Global clock synchronization in sensor networks , 2006, IEEE Transactions on Computers.

[4]  R. Murray,et al.  Graph rigidity and distributed formation stabilization of multi-vehicle systems , 2002, Proceedings of the 41st IEEE Conference on Decision and Control, 2002..

[5]  George W. Irwin,et al.  Wireless networked control systems with QoS-based sampling , 2007 .

[6]  Reza Olfati-Saber,et al.  Consensus and Cooperation in Networked Multi-Agent Systems , 2007, Proceedings of the IEEE.

[7]  YangQuan Chen,et al.  Formation control: a review and a new consideration , 2005, 2005 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[8]  A. M. Abdullah,et al.  Wireless lan medium access control (mac) and physical layer (phy) specifications , 1997 .

[9]  Mario Gerla,et al.  MANET QoS support without reservations , 2011, Secur. Commun. Networks.

[10]  Michael D. Lemmon,et al.  Almost sure stability of networked control systems under exponentially bounded bursts of dropouts , 2011, HSCC '11.

[11]  Feng-Li Lian,et al.  Network architecture and communication modules for guaranteeing acceptable control and communication performance for networked multi-agent systems , 2006, IEEE Transactions on Industrial Informatics.

[12]  Yih-Chun Hu,et al.  Exploiting congestion information in network and higher layer protocols in multihop wireless ad hoc networks , 2004, 24th International Conference on Distributed Computing Systems, 2004. Proceedings..

[13]  Shreyas Sundaram,et al.  The Wireless Control Network: A New Approach for Control Over Networks , 2011, IEEE Transactions on Automatic Control.

[14]  Mo-Yuen Chow,et al.  Behavioral control based adaptive bandwidth allocation in a system of Unmanned Ground Vehicles , 2010, IECON 2010 - 36th Annual Conference on IEEE Industrial Electronics Society.

[15]  Jingdong Xu,et al.  NCCPIS: A Co-simulation Tool for Networked Control and Cyber-Physical System Evaluation , 2012, NPC.

[16]  Dragan Obradovic,et al.  Variable sampling rate in networked control systems , 2007, ALCOSP.

[17]  Yuan Xue,et al.  Optimal Cross-Layer Design of Sampling Rate Adaptation and Network Scheduling for Wireless Networked Control Systems , 2012, 2012 IEEE/ACM Third International Conference on Cyber-Physical Systems.

[18]  Hannes Hartenstein,et al.  Broadcast reception rates and effects of priority access in 802.11-based vehicular ad-hoc networks , 2004, VANET '04.

[19]  Daniel Lopez-Echevarria.  Variable sampling compensation of networked control systems with delays using neural networks , 2011 .

[20]  Insup Lee,et al.  Cyber-physical systems: The next computing revolution , 2010, Design Automation Conference.

[21]  Edward A. Lee.  CPS foundations , 2010, Design Automation Conference.

[22]  Yixin Chen,et al.  Near Optimal Rate Selection for Wireless Control Systems , 2012, 2012 IEEE 18th Real Time and Embedded Technology and Applications Symposium.

[23]  Kevin C. Almeroth,et al.  Rate Adaptation in Congested Wireless Networks through Real-Time Measurements , 2010, IEEE Transactions on Mobile Computing.

[24]  Richard M. Murray,et al.  DISTRIBUTED COOPERATIVE CONTROL OF MULTIPLE VEHICLE FORMATIONS USING STRUCTURAL POTENTIAL FUNCTIONS , 2002 .

[25]  Kevin C. Almeroth,et al.  Understanding link-layer behavior in highly congested IEEE 802.11b wireless networks , 2005, E-WIND '05.

[26]  Hariharan Krishnan,et al.  Design of cooperative vehicle safety systems based on tight coupling of communication, computing and physical vehicle dynamics , 2010, ICCPS '10.

[27]  Qi Chen,et al.  Overhaul of ieee 802.11 modeling and simulation in ns-2 , 2007, MSWiM '07.

[28]  Simon Hallé,et al.  Automated highway systems : platoons of vehicles viewed as a multiagent system , 2005 .

[29]  Zhou Chao,et al.  Formation control for large scale multi-agent systems while preserving network connectivity , 2011, 2011 International Conference on Electronics, Communications and Control (ICECC).