PMID: 11308751Apr 20, 2001Paper

Learning to control a complex multistable system

Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics
S Gadaleta, G Dangelmayr

Abstract

In this paper the control of a periodically kicked mechanical rotor without gravity in the presence of noise is investigated. In recent work it was demonstrated that this system possesses many competing attracting states and thus shows the characteristics of a complex multistable system. We demonstrate that it is possible to stabilize the system at a desired attracting state even in the presence of high noise level. The control method is based on a recently developed algorithm [S. Gadaleta and G. Dangelmayr, Chaos 9, 775 (1999)] for the control of chaotic systems and applies reinforcement learning to find a global optimal control policy directing the system from any initial state towards the desired state in a minimum number of iterations. Being data-based, the method does not require any information about governing dynamical equations.

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Citations

Feb 9, 2005·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Paulo Cesar RechJason A C Gallas
May 17, 2017·Physical Review. E·Kiran YadavManish Dev Shrimali
Oct 30, 2014·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Jürgen Jost, Wei Li
Feb 28, 2002·Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics·Jesús Marín, Ricard V Solé

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