Comparison of systems with complex behavior

Abstract We present a formalism for comparing the asymptotic dynamics of dynamical systems with physical systems that they model based on the spectral properties of the Koopman operator. We first compare invariant measures and discuss this in terms of a “statistical Takens” theorem proved here. We also identify the need to go beyond comparing only invariant ergodic measures of systems and introduce an ergodic–theoretic treatment of a class of spectral functionals that allow for this. The formalism is extended for a class of stochastic systems: discrete Random Dynamical Systems. The ideas introduced in this paper can be used for parameter identification and model validation of driven nonlinear models with complicated behavior. As an illustration we provide an example in which we compare the asymptotic behavior of a combustion system measured experimentally with the asymptotic behavior of a class of models that have the form of a random dynamical system.

[1]  T. Lieuwen,et al.  Experimental investigation of limit cycle oscillations in an unstable gas turbine combustor , 2000 .

[2]  F. Takens,et al.  Mixed spectra and rotational symmetry , 1993 .

[3]  I. Singer,et al.  Bases in Banach Spaces II , 1970 .

[4]  Anne E. Trefethen,et al.  Hydrodynamic Stability Without Eigenvalues , 1993, Science.

[5]  Paul R. Halmos,et al.  Approximation theories for measure preserving transformations , 1944 .

[6]  O. Junge,et al.  On the Approximation of Complicated Dynamical Behavior , 1999 .

[7]  G. Berkooz An observation on probability density equations, or, when do simulations reproduce statistics? , 1994 .

[8]  V. Araújo Random Dynamical Systems , 2006, math/0608162.

[9]  S. C. Reddy,et al.  Energy growth in viscous channel flows , 1993, Journal of Fluid Mechanics.

[10]  Lorenz Halbeisen,et al.  On bases in Banach spaces , 2005 .

[11]  D. Broomhead,et al.  Takens embedding theorems for forced and stochastic systems , 1997 .

[12]  Domenico D'Alessandro,et al.  Statistical properties of controlled fluid flows with applications to control of mixing , 2002, Systems & control letters (Print).

[13]  A. Mees,et al.  Constructing invariant measures from data , 1995 .

[14]  M. Dahleh,et al.  Energy amplification in channel flows with stochastic excitation , 2001 .

[15]  Michael Dellnitz,et al.  On the isolated spectrum of the Perron-Frobenius operator , 2000 .

[16]  Mehmet Emre Çek,et al.  Analysis of observed chaotic data , 2004 .

[17]  John B. Shoven,et al.  I , Edinburgh Medical and Surgical Journal.

[18]  Igor Mezic,et al.  On the geometrical and statistical properties of dynamical systems : theory and applications , 1994 .

[19]  Umesh Vaidya,et al.  Controllability for a class of area-preserving twist maps , 2004 .

[20]  Michael C. Mackey,et al.  Chaos, Fractals, and Noise , 1994 .

[21]  Andrzej Banaszuk,et al.  Active Control of Combustion Instabilities in Gas Turbine Engines for Low Emissions. Part II: Adaptive Control Algorithm Development, Demonstration and Performance Limitations , 2000 .

[22]  Andrea Garulli,et al.  Integrating Identification and Qualitative Analysis for the Dynamic Model of a Lagoon , 2003, Int. J. Bifurc. Chaos.

[23]  F. Takens Detecting strange attractors in turbulence , 1981 .

[24]  Joshua D. Reiss,et al.  Construction of symbolic dynamics from experimental time series , 1999 .

[25]  L. Gustavsson Energy growth of three-dimensional disturbances in plane Poiseuille flow , 1981, Journal of Fluid Mechanics.

[26]  Wolfgang Kliemann,et al.  Lyapunov exponents of control flows , 1991 .

[27]  J. McWilliams,et al.  Stochasticity and Spatial Resonance in Interdecadal Climate Fluctuations , 1997 .

[28]  R. Mañé,et al.  Ergodic Theory and Differentiable Dynamics , 1986 .

[29]  Alexandre J. Chorin,et al.  Non-Markovian Optimal Prediction , 2001, Monte Carlo Methods Appl..

[30]  Vanden Eijnden E,et al.  Models for stochastic climate prediction. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[31]  Aurel Wintner,et al.  Harmonic Analysis and Ergodic Theory , 1941 .

[32]  Kathryn M. Butler,et al.  Three‐dimensional optimal perturbations in viscous shear flow , 1992 .

[33]  Barry Simon,et al.  Topics in Ergodic Theory , 1994 .

[34]  I. Mezić,et al.  Ergodic theory and experimental visualization of invariant sets in chaotically advected flows , 2002 .

[35]  R. Moeckel,et al.  Measuring the distance between time series , 1997 .

[36]  C. Caramanis What is ergodic theory , 1963 .

[37]  Jeffrey M. Cohen,et al.  Active Control of Combustion Instabilities in Gas Turbine Engines for Low Emissions. Part I: Physics-Based and Experimentally Identified Models of Combustion Instability , 2000 .

[38]  Stephen Wiggins,et al.  A method for visualization of invariant sets of dynamical systems based on the ergodic partition. , 1999, Chaos.

[39]  Edwin Hewitt,et al.  Real And Abstract Analysis , 1967 .

[40]  Tim Lieuwen,et al.  Experimental investigation of the nonlinear flame response to flow disturbances in a gas turbine combustor , 2001 .