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A Geometric Index Reduction Method for DAE Systems Gabriela Jeronimo (1) Joint work with L. DAlfonso (1) , F. Ollivier (2) , A. Sedoglavic (3) and P. Solern o (1) (1) Universidad de Buenos Aires, Argentina (2) Ecole Polytechnique, France


  1. A Geometric Index Reduction Method for DAE Systems Gabriela Jeronimo (1) Joint work with L. D’Alfonso (1) , F. Ollivier (2) , A. Sedoglavic (3) and P. Solern´ o (1) (1) Universidad de Buenos Aires, Argentina (2) ´ Ecole Polytechnique, France (3) Universit´ e de Lille I, France DART IV – October 2010 Gabriela Jeronimo Index reduction for DAE systems

  2. DAE systems Consider a Differential Algebraic Equation (DAE) system  f 1 ( X , . . . , X ( e ) )  = 0  . . (Σ) = .   f n ( X , . . . , X ( e ) ) = 0 X ( k ) := { x ( k ) 1 , . . . , x ( k ) n } for every k ∈ Z ≥ 0 , F := f 1 , . . . , f n polynomials with coefficients in C or C ( t ). Gabriela Jeronimo Index reduction for DAE systems

  3. DAE systems Consider a Differential Algebraic Equation (DAE) system  f 1 ( X , . . . , X ( e ) )  = 0  . . (Σ) = .   f n ( X , . . . , X ( e ) ) = 0 X ( k ) := { x ( k ) 1 , . . . , x ( k ) n } for every k ∈ Z ≥ 0 , F := f 1 , . . . , f n polynomials with coefficients in C or C ( t ). � � ∂ F If det � = 0, (Σ) is equivalent to an ODE system: ∂ X ( e ) � X ( e ) = G ( X , . . . , X ( e − 1) ) . ( � Σ) = Gabriela Jeronimo Index reduction for DAE systems

  4. DAE systems Consider a Differential Algebraic Equation (DAE) system  f 1 ( X , . . . , X ( e ) )  = 0  . . (Σ) = .   f n ( X , . . . , X ( e ) ) = 0 X ( k ) := { x ( k ) 1 , . . . , x ( k ) n } for every k ∈ Z ≥ 0 , F := f 1 , . . . , f n polynomials with coefficients in C or C ( t ). � � ∂ F If det � = 0, (Σ) is equivalent to an ODE system: ∂ X ( e ) � X ( e ) = G ( X , . . . , X ( e − 1) ) . ( � Σ) = � � ∂ F What can be done when det = 0? ∂ X ( e ) Gabriela Jeronimo Index reduction for DAE systems

  5. Semi-explicit systems   x 1 ˙ = g 1 ( X )    . . . X = ( x 1 , . . . , x n ) (Σ 0 ) :=  ˙ = g n − 1 ( X )  x n − 1   g ( X ) = 0 Gabriela Jeronimo Index reduction for DAE systems

  6. Semi-explicit systems   x 1 ˙ = g 1 ( X )    . . . X = ( x 1 , . . . , x n ) (Σ 0 ) :=  ˙ = g n − 1 ( X )  x n − 1   g ( X ) = 0 From the last equation: n − 1 � ∂ g ∂ g ( X ) g i ( X ) + ∂ g ∂ t ( X ) + ( X ) ˙ x n = 0 . ∂ x i ∂ x n i =1 Gabriela Jeronimo Index reduction for DAE systems

  7. Semi-explicit systems   x 1 ˙ = g 1 ( X )    . . . X = ( x 1 , . . . , x n ) (Σ 0 ) :=  ˙ = g n − 1 ( X )  x n − 1   g ( X ) = 0 From the last equation: n − 1 � ∂ g ∂ g ( X ) g i ( X ) + ∂ g ∂ t ( X ) + ( X ) ˙ x n = 0 . ∂ x i ∂ x n i =1 If ∂ g � = 0, we can solve ˙ x n = g n ( X ). ∂ x n Gabriela Jeronimo Index reduction for DAE systems

  8. Semi-explicit systems   x 1 ˙ = g 1 ( X )    . . . X = ( x 1 , . . . , x n ) (Σ 0 ) :=  ˙ = g n − 1 ( X )  x n − 1   g ( X ) = 0 From the last equation: n − 1 � ∂ g ∂ g ( X ) g i ( X ) + ∂ g ∂ t ( X ) + ( X ) ˙ x n = 0 . ∂ x i ∂ x n i =1 If ∂ g � = 0, we can solve ˙ x n = g n ( X ). ∂ x n The first n − 1 equations plus this one form an ODE system. Gabriela Jeronimo Index reduction for DAE systems

  9. Differentiation index of DAE systems The differentiation index of a DAE system is an integer σ ∈ Z ≥ 0 which measures the implicitness of the given system. Gabriela Jeronimo Index reduction for DAE systems

  10. Differentiation index of DAE systems The differentiation index of a DAE system is an integer σ ∈ Z ≥ 0 which measures the implicitness of the given system. σ = minimum number of differentiations of the system required in order to obtain an ODE. Gabriela Jeronimo Index reduction for DAE systems

  11. Differentiation index of DAE systems The differentiation index of a DAE system is an integer σ ∈ Z ≥ 0 which measures the implicitness of the given system. σ = minimum number of differentiations of the system required in order to obtain an ODE. Examples. For a DAE system F ( X , ˙ X , . . . , X ( e ) ) = 0 such that � � ∂ F det � = 0, we have σ = 0. ∂ X ( e ) Gabriela Jeronimo Index reduction for DAE systems

  12. Differentiation index of DAE systems The differentiation index of a DAE system is an integer σ ∈ Z ≥ 0 which measures the implicitness of the given system. σ = minimum number of differentiations of the system required in order to obtain an ODE. Examples. For a DAE system F ( X , ˙ X , . . . , X ( e ) ) = 0 such that � � ∂ F det � = 0, we have σ = 0. ∂ X ( e ) For a semi-explicit DAE system, σ = 1. Gabriela Jeronimo Index reduction for DAE systems

  13. Index reduction problem Given a high-index DAE system (Σ), obtain an equivalent DAE system (Σ 0 ) with low index (preferably 0 or 1, and semi-explicit). Gabriela Jeronimo Index reduction for DAE systems

  14. Index reduction problem Given a high-index DAE system (Σ), obtain an equivalent DAE system (Σ 0 ) with low index (preferably 0 or 1, and semi-explicit). Motivation: low-index DAE systems are easier to solve than high-index DAE systems. Gabriela Jeronimo Index reduction for DAE systems

  15. Index reduction problem Given a high-index DAE system (Σ), obtain an equivalent DAE system (Σ 0 ) with low index (preferably 0 or 1, and semi-explicit). Motivation: low-index DAE systems are easier to solve than high-index DAE systems. Previous work: [Gear 1988, 1989], [Brenan-Campbell-Petzold 1996], [Kunkel-Mehrmann 2006]. Gabriela Jeronimo Index reduction for DAE systems

  16. Index reduction problem Given a high-index DAE system (Σ), obtain an equivalent DAE system (Σ 0 ) with low index (preferably 0 or 1, and semi-explicit). Motivation: low-index DAE systems are easier to solve than high-index DAE systems. Previous work: [Gear 1988, 1989], [Brenan-Campbell-Petzold 1996], [Kunkel-Mehrmann 2006]. Tools: Computation of successive derivatives of the equations, rewriting techniques relying on the Implicit Function Theorem, etc. Gabriela Jeronimo Index reduction for DAE systems

  17. Our main results  f 1 ( X , X (1) , . . . , X ( e ) ) = 0   . . (Σ) = with certain assumptions . .   f n ( X , X (1) , . . . , X ( e ) ) = 0 Gabriela Jeronimo Index reduction for DAE systems

  18. Our main results  f 1 ( X , X (1) , . . . , X ( e ) ) = 0   . . (Σ) = with certain assumptions . .   f n ( X , X (1) , . . . , X ( e ) ) = 0 (Σ) is generically equivalent to a first order semi-explicit DAE system with differentiation index 1  ˙ = g 1 ( U , v )  u 1    . . . (Σ 0 ) := U = ( u 1 , . . . , u r )  ˙ = g r ( U , v )  u r   q ( U , v ) = 0 Gabriela Jeronimo Index reduction for DAE systems

  19. Our main results  f 1 ( X , X (1) , . . . , X ( e ) ) = 0   . . (Σ) = with certain assumptions . .   f n ( X , X (1) , . . . , X ( e ) ) = 0 (Σ) is generically equivalent to a first order semi-explicit DAE system with differentiation index 1  ˙ = g 1 ( U , v )  u 1    . . . (Σ 0 ) := U = ( u 1 , . . . , u r )  ˙ = g r ( U , v )  u r   q ( U , v ) = 0 a probabilistic algorithm to compute the differentiation index of (Σ) and the associated system (Σ 0 ). Gabriela Jeronimo Index reduction for DAE systems

  20. Remarks (Σ) and (Σ 0 ) are equivalent in the sense that almost all analytic solution of (Σ) can be obtained from an analytic solution of (Σ 0 ) and conversely. Gabriela Jeronimo Index reduction for DAE systems

  21. Remarks (Σ) and (Σ 0 ) are equivalent in the sense that almost all analytic solution of (Σ) can be obtained from an analytic solution of (Σ 0 ) and conversely. Our algorithms rely on: Gabriela Jeronimo Index reduction for DAE systems

  22. Remarks (Σ) and (Σ 0 ) are equivalent in the sense that almost all analytic solution of (Σ) can be obtained from an analytic solution of (Σ 0 ) and conversely. Our algorithms rely on: an alternative characterization of the differentiation index ([DAlJeSo08]), Gabriela Jeronimo Index reduction for DAE systems

  23. Remarks (Σ) and (Σ 0 ) are equivalent in the sense that almost all analytic solution of (Σ) can be obtained from an analytic solution of (Σ 0 ) and conversely. Our algorithms rely on: an alternative characterization of the differentiation index ([DAlJeSo08]), the polynomial time Kronecker algorithm for the computation of geometric resolutions of algebraic polynomial systems ([GiLeSa01], [Schost03]). Gabriela Jeronimo Index reduction for DAE systems

  24. Assumptions on the system Gabriela Jeronimo Index reduction for DAE systems

  25. Assumptions on the system K { X } = K [ x ( j ) : 1 ≤ i ≤ n , j ∈ N 0 ] with the derivation δ induced i by δ ( x ( j ) ) = x ( j +1) . i i Gabriela Jeronimo Index reduction for DAE systems

  26. Assumptions on the system K { X } = K [ x ( j ) : 1 ≤ i ≤ n , j ∈ N 0 ] with the derivation δ induced i by δ ( x ( j ) ) = x ( j +1) . i i [ F ] = [ f 1 , . . . , f n ] ⊂ K { X } differential ideal associated with (Σ). Gabriela Jeronimo Index reduction for DAE systems

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