Theory and observation of nonlinear dynamical systems: Application to ocean and e...
Deep learning strategies applied to closed-loop control of unsteady flows
Abstract
We apply basic theories of chaos and turbulence to investigate the control of chaotic dynamical systems. For hamiltonian systems, we investigate the transition to chaos and the onset and break of transport barriers, as observed in magnetically confined plasmas and particle accelerators. We also investigate the turbulence onset in magnetically confined plasmas and interpret control experiments in tokamaks and helimaks. Moreover, we also investigate chaotic dissipative systems, found in applied physics and engineering, and identify dynamical properties of these systems in the parameter space. We perform experiments on the Matsumoto-Chua circuit, faucet formation, bubble formation, mechanical systems (parametric pendula), and plasma turbulence and MHD instabilities in tokamaks. We also investigate the synchronization in neural networks, and the occurrence of chimeras and plasticity in these systems, and the syncrhronization of a network of non linear oscillators. (AU)
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