Agent Based Adaptive Cooperative Models and Mechanisms of Multiple Autonomous Cyber-Physical Systems

Networked cooperation is one primarily problem for autonomous Cyber-Physical Systems(CPS) that feature cyber-physical fusion, and smart behavior. After analyzing current contributions, a three-level task model, with which missions can be recognized and mapped to tasks, is studied firstly in this paper. And then, based on a designed uniform model of the surroundings, external missions and internal computational resources, two hybrid models, which are autonomously cooperative and real-time reactive by taking advantages of agent and adaptive control, are illuminated respectively. Further, a hierarchal cooperation mechanism of CPS fleet is put forward. With this mechanism, the dynamic topologies of a fleet will be more flexible and dependable, and by adopting an intelligent algorithm, all tasks mapped from a mission can be autonomously assigned to suitable members under decentralized consultation or centralized allocation mode. In this paper, an optimized genetic algorithm is employed to illustrate the process of proposed mechanisms.

[1]  B. Heck,et al.  An approach to the adaptive mode transition control of unmanned aerial vehicles , 2003, Proceedings of the 2003 American Control Conference, 2003..

[2]  Bo Chen,et al.  A Review of the Applications of Agent Technology in Traffic and Transportation Systems , 2010, IEEE Transactions on Intelligent Transportation Systems.

[3]  O. Khatib,et al.  Real-Time Obstacle Avoidance for Manipulators and Mobile Robots , 1985, Proceedings. 1985 IEEE International Conference on Robotics and Automation.

[4]  D. Caveney,et al.  Architecture and Application Abstractions for Multi-Agent Collaboration Projects , 2005, Proceedings of the 44th IEEE Conference on Decision and Control.

[5]  Clark Weissman.  MLS-PCA: a high assurance security architecture for future avionics , 2003, 19th Annual Computer Security Applications Conference, 2003. Proceedings..

[6]  Long Cheng,et al.  Decentralized Robust Adaptive Control for the Multiagent System Consensus Problem Using Neural Networks , 2009, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Pei-Chuan Zhou,et al.  Robot collaboration through agent cooperation in a smart environment , 2012, 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM).

[8]  D. P. Schrage,et al.  Software-enabled control for intelligent UAVs , 1999, Proceedings of the 1999 IEEE International Symposium on Computer Aided Control System Design (Cat. No.99TH8404).

[9]  Brian C. Williams,et al.  Model-based programming of intelligent embedded systems and robotic space explorers , 2003, Proc. IEEE.

[10]  He Huang,et al.  Multi-agent Cooperation: A Description Logic View , 2005, PRIMA.

[11]  Hesham Rakha,et al.  Optimizing Driverless Vehicles at Intersections , 2012 .