Coupling Evolutionary Algorithms With Nonlinear Dynamical Systems: An Efficient Tool for Excitation Design and Optimization
Many chaotic dynamical systems can produce time series with a wide range of temporal and spectral properties as a function of only a few fixed parameters. This malleability invites their use as tools for shaping or designing inputs used to drive a separate dynamical system of interest. By specifying an objective function and employing an evolutionary algorithm to manipulate the parameters governing the dynamics of the forcing system, the output of the driven system is made to approach an optimal response subject to desired constraints. The technique's versatility is demonstrated for two different applications: damage detection in structures and phase-locked loop disruption.
evolutionary algorithms nonlinear dynamics damage detection phase-locked loops chaos differential evolution