9513071 Tufillaro A program of research is described whose goal is to enhance the modeling and control of low dimensional nonlinear systems that exhibit chaotic behavior. In order to achieve this goal the first objective is to develop a series of procedures for building models that accurately describe the time evolution of these systems. The models are global discrete mappings and ordinary differential equations constructed only from experimental time series data. The second major objective is to exploit synchronization between the fitted models and measured time series as a means of carrying out model verification and control. The third objective is to explore the use of topological procedures to constrain and fine tune these models. The proposed research will significantly enhance the ability to detect, model, and control the dynamics of chaotic systems using observed time series data. This project is a collaborative effort involving the close interaction of several research groups in nonlinear science (UCSD, GIT). ***
