Nonlinear System Identification and Characterization

The term "system identification" can address various levels of the modeling stage. At one extreme, the goal might be to find the number of active states in a system. In one viewpoint, a dimensionality study on nonlinear-system data often starts with the reconstruction of the phase space from a single observable. We have studied the application of delay phase-space reconstructions to chaotic stick-slip systems. Another viewpoint might involve the usage of proper orthogonal decompostion (POD), which can be helpful in determining the number of active modes in an oscillatory system, and also an optimal representation of the form of the modes, which may help in the reduced-order modeling. Our activity in POD is on a separate page.

At the other extreme is parametric identification, in which the actual form of a dynamical system model is known, but unknown parameters need to be identified. We have extended the harmonic-balance identification method to chaotic systems by extracting the unstable periodic orbits from a chaotic set, treating them as periodic solutions to a differential equation with unknown parameters, and balancing harmonics of these unstable solutions to estimate parameters.  We are also investigating ways of extracting damping parameters in free and forced vibration systems--see the friction page.

Support:  NASA Langley Research Center, 4/01-11/02

Publications