In this talk we review the simple but effective OGY method for the control of chaotic dynamics from a control engineering perspective. An important ingredient in this method is to estimate the effort required to identify a sufficiently accurate local representation for the dynamics that need to be stabilised. Using ideas from linear system identification and ergodicity theory for chaotic dynamics we arrive at an estimate of the data complexity to achieve a deisred control result.
The estimates have implications for the reconstruction of low dimensional chaotic maps via local linear maps over tesselations.
A promising application area is in secure data communication.