Computer-Assisted Proofs in Solving Linear Parametric Problems

Consider a linear system A(p)x = b(p) whose input data depend on a number of uncertain parameters p = (p1,...,pk) varying within given intervals [p]. The objective is to verify by numerical computations monotonic (and convexity/concavity) dependence of a solution component xi(p) with respect to a parameter pj over the interval box [p], or more general, to prove if some boundary inf / sup xi(p) for all p isin [p] is attained at the end-points of [p]. Such knowledge is useful in many applications in order to facilitate the solution of some underlying linear parametric problem involving uncertainties. In this paper we present a technique, for proving the desired properties of the parametric solution, which is alternative to the approaches based on extreme point computations. The proposed computer-aided proof is based on guaranteed interval enclosures for the partial derivatives of the parametric solution for all p isin [p]. The availability of self-validated methods providing guaranteed enclosure of a parametric solution set by floating-point computations is a key for the efficiency and the expanded scope of applicability of the proposed approach. Linear systems involving nonlinear parameter dependencies, and dependencies between A(p) and b(p), as well as non-square linear parametric systems can be handled successfully. Presented are details of the algorithm design and mathematica tools implementing the proposed approach. Numerical examples from structural mechanics illustrate its application.

[1]  Arnold Neumaier,et al.  Linear Systems with Large Uncertainties, with Applications to Truss Structures , 2007, Reliab. Comput..

[2]  Vom Fachbereich Mathematik,et al.  Interval Analysis of Analog Circuits with Component Tolerances Intervall-Analyse analoger Schaltungen mit Bauteiletoleranzen , 2005 .

[3]  Evgenija D. Popova,et al.  Parametric Interval Linear Solver , 2004, Numerical Algorithms.

[4]  Ramon E. Moore Methods and applications of interval analysis , 1979, SIAM studies in applied mathematics.

[5]  Bounding the Response of Mechanical Structures with Uncertainties in All the Parameters , 2006 .

[6]  Evgenija D. Popova Generalization of a Parametric Fixed‐Point Iteration , 2004 .

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

[8]  Evgenija D. Popova Solving Linear Systems Whose Input Data Are Rational Functions of Interval Parameters , 2006, Numerical Methods and Applications.

[9]  Siegfried M. Rump 10. Computer-Assisted Proofs and Self-Validating Methods , 2005, Accuracy and Reliability in Scientific Computing.

[10]  B. Ross Barmish,et al.  An extreme point result for convexity, concavity and monotonicity of parameterized linear equation solutions , 2004 .

[11]  Evgenija D. Popova,et al.  Quality of the Solution Sets of Parameter‐Dependent Interval Linear Systems , 2002 .

[12]  Siegfried M. Rump,et al.  Solving Algebraic Problems with High Accuracy , 1983, IMACS World Congress.

[13]  S. Rump Verification methods for dense and sparse systems of equations , 1994 .

[14]  Z. Kulpa,et al.  Analysis of linear mechanical structures with uncertainties by means of interval methods , 1998 .

[15]  Evgenija D. Popova,et al.  Improved Solution Enclosures for Over- and Underdetermined Interval Linear Systems , 2005, LSSC.