V. Rajagopalan, R. Samsi, A. Ray, J. Mayer, and C. Lagoa (USA)
Symbolic Dynamics, Finite State Automata,Nonlinear Sys tems.
This paper deals with the early detection of small param eter variations in non-linear systems. The objective is to detect these variations, before they manifest themselves as a sudden change in the phase behavior. It is assumed that these parameter variations occur slowly in time. Early de tection of slow time-scale anomalous behavior in nonlinear dynamical system is achieved by observing and inferring time series data of the state or output variables, at the fast time-scale. The detection algorithm makes use of Symbolic Dynamics and Finite State Automata. As an example, we consider the Duffing equation which is a second order non linear differential equation. The methodology is validated both in simulation and experiment. This concept can be fur ther extended to dynamical systems of higher complexity.
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