We consider the influence of white noise on achieving consensus in a stochastic version of the well known Cucker-Smale model for flocking in multi-agent swarm systems. Our main results based on extensive numerical simulations suggest that while low intensity white noise has little appreciable effects on convergence to consensus in the system, the presence of high intensity white noise can fundamentally alter the flocking characteristics of the model. In particular, our results indicate that the numerical upper bound on a critical system parameter value that guarantees flocking in the deterministic model is no longer valid in the presence of high intensity white noise. In addition, the results also suggest that, interestingly, the influence of noise is independent of the number of agents in the swarm. Finally, we suggest a novel approach using the classical Fokker-Planck formalism as a direction of further analytical work aimed at validating our numerical results.
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ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference
October 17–19, 2012
Fort Lauderdale, Florida, USA
Conference Sponsors:
- Dynamic Systems and Control Division
ISBN:
978-0-7918-4531-8
PROCEEDINGS PAPER
A Numerical Study of the Stochastic Cucker-Smale Flocking Model
Subramanian Ramakrishnan,
Subramanian Ramakrishnan
Villanova University, Villanova, PA
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Balaji R. Sharma,
Balaji R. Sharma
University of Cincinnati, Cincinnati, OH
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Manish Kumar
Manish Kumar
University of Toledo, Toledo, OH
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Subramanian Ramakrishnan
Villanova University, Villanova, PA
Balaji R. Sharma
University of Cincinnati, Cincinnati, OH
Manish Kumar
University of Toledo, Toledo, OH
Paper No:
DSCC2012-MOVIC2012-8860, pp. 333-338; 6 pages
Published Online:
September 17, 2013
Citation
Ramakrishnan, S, Sharma, BR, & Kumar, M. "A Numerical Study of the Stochastic Cucker-Smale Flocking Model." Proceedings of the ASME 2012 5th Annual Dynamic Systems and Control Conference joint with the JSME 2012 11th Motion and Vibration Conference. Volume 3: Renewable Energy Systems; Robotics; Robust Control; Single Track Vehicle Dynamics and Control; Stochastic Models, Control and Algorithms in Robotics; Structure Dynamics and Smart Structures; Surgical Robotics; Tire and Suspension Systems Modeling; Vehicle Dynamics and Control; Vibration and Energy; Vibration Control. Fort Lauderdale, Florida, USA. October 17–19, 2012. pp. 333-338. ASME. https://doi.org/10.1115/DSCC2012-MOVIC2012-8860
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