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Distributed adaptive control of chaos

In recent years, methods have been proposed for controlling chaotic systems around unstable orbits embedded in chaotic attractors. These methods require local linear models of the systems which may be obtained either theoretically or in some cases experimentally. In this paper we present a nonlinear local model based approach to the control of chaos, and describe actual and potential benefits in terms of reduced time to control, a larger region of effective control and a well-founded approach to determining the control law.