Controlling Chaos in Unidimensional Maps Using Macroevolutionary Algorithms

We introduce a simple search algorithm that explores the parameter of periodically perturbed discrete maps in order to find desired orbits through chaos control. The method has been applied to one-dimensional maps but is easily extendable to higher-dimensional systems. Here, we consider two types of chaos control involving proportional pulses in the system variables [Phys. Rev. Lett. 72, 1455 (1994)] and constant feedback [Phys. Rev. E 51, 6239 (1995)], the first case being presented in detail. It is shown that our method allows a rapid exploration of parameter space and the finding of high-fitness (i.e., controlled) solutions close to the target orbits, even when high periodicities are required.