Guiding a self-adjusting system through chaos

The authors studied the parametric controls of self-adjusting systems with numerical models. The authors investigated the situation where the target dynamics changes slowly and passes through a chaotic region. The authors found that feedback destabilizes controls if the target is chaotic. If the control is unstable, the system migrates to the closest nonchaotic target, i.e., it adapts to the edge of chaos. For weak controls, the deviation between system dynamics and target is larger, but the system dynamics is less chaotic and therefore more predictable.