Structural identifiability analysis via symmetries of differential equations

Results and derivations are presented for the generation of a local Lie algebra that represents the 'symmetries' of a set of coupled differential equations. The subalgebra preserving the observation defined on the model structure is found, thus giving all transformations of the system that preserve its structure. It is shown that this is equivalent to the similarity transformation approach (Evans, Chapman, Chappell, & Godfrey, 2002) for structural identifiability analysis and as such is a method of generating such transformations for this approach. This provides another method for performing structural identifiability analysis on nonlinear state-space models that has the possibility of extension to PDE type models. The analysis is easily automated and performed in Mathematica, and this is demonstrated by application of the technique to a number of practical examples from the literature.

[1]  Keith R. Godfrey,et al.  Identifiability of uncontrolled nonlinear rational systems , 2002, Autom..

[2]  Peter A. Clarkson,et al.  BRIAN J. CANTWELL: 612 pp., £95.00 (US$130.00)/£35.95 (US$50.00)(P), ISBN 0-521-77183-8/0-521-77740-2(P) (Cambridge University Press, 2002) , 2004 .

[3]  P. L. Sachdev Self-Similarity and Beyond: Exact Solutions of Nonlinear Problems , 2000 .

[4]  Lennart Ljung,et al.  On global identifiability for arbitrary model parametrizations , 1994, Autom..

[5]  P. Olver Applications of lie groups to differential equations , 1986 .

[6]  Eva Riccomagno,et al.  Structural identifiability analysis of some highly structured families of statespace models using differential algebra , 2004, Journal of mathematical biology.

[7]  Maria Pia Saccomani,et al.  Parameter identifiability of nonlinear systems: the role of initial conditions , 2003, Autom..

[8]  Keith Godfrey,et al.  Compartmental Models and Their Application , 1983 .

[9]  Donal O'Shea,et al.  Ideals, varieties, and algorithms - an introduction to computational algebraic geometry and commutative algebra (2. ed.) , 1997, Undergraduate texts in mathematics.

[10]  H P Wynn,et al.  Differential algebra methods for the study of the structural identifiability of rational function state-space models in the biosciences. , 2001, Mathematical biosciences.

[11]  David A. Cox,et al.  Ideals, Varieties, and Algorithms: An Introduction to Computational Algebraic Geometry and Commutative Algebra, 3/e (Undergraduate Texts in Mathematics) , 2007 .

[12]  Alexandre Sedoglavic A probabilistic algorithm to test local algebraic observability in polynomial time , 2001, ISSAC '01.

[13]  Stephen Wolfram,et al.  The Mathematica Book , 1996 .

[14]  Ghislaine Joly-Blanchard,et al.  Equivalence and identifiability analysis of uncontrolled nonlinear dynamical systems , 2004, Autom..

[15]  R. A. Nicolaides,et al.  MAPLE: A Comprehensive Introduction , 1996 .