Noise in the modeling and control of dynamical systems

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Abstract
We demonstrate how noise can be an effective tool in modeling systems whose experimental data sets would normally be limited to a small region of the reconstructed state space. In fact, for systems with stable fixed points, using noise to extend the accessible state-space volume may be the only possibility for constructing a model. We find that noise can also be useful in modeling limit cycles when multiple systems generate the same closed trajectory and the model that represents the true dynamics is desired. We discuss the implications of our method for nonlinear control theory about which important questions on the effects of noise in real-time modeling have arisen.

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