 Differential algebraic equation

In mathematics, differential algebraic equations (DAEs) are a general form of (systems of) differential equations for vector–valued functions x in one independent variable t,
where is a vector of dependent variables and the system has as many equations, . They are distinct from ordinary differential equation (ODE) in that a DAE is not completely solvable for the derivatives of all components of the function x.
This difference is more clearly visible if the system may be rewritten so that instead of x we consider a pair (x,y) of vectors of dependent variables and the DAE has the form

 where , , and .
Every solution of the second half g of the equation defines a unique direction for x via the first half f of the equations, while the direction for y is arbitrary. But not every point (x,y,t) is a solution of g. The variables in x and the first half f of the equations get the attribute differential. The components of y and the second half g of the equations are called the algebraic variables or equations of the system. The term algebraic in the context of DAEs only means free of derivatives and is not related to (abstract) algebra.
The solution of a DAE consists of two parts, first the search for consistent initial values and second the computation of a trajectory. To find consistent initial values it is often necessary to consider the derivatives of some of the component functions of the DAE. The highest order of a derivative that is necessary in this process is called the differentiation index. The equations derived in computing the index and consistent initial values may also be of use in the computation of the trajectory.Contents
Other forms of DAEs
The distinction of DAEs to ODEs becomes apparent if some of the dependent variables occur without their derivatives. The vector of dependent variables may then be written as pair (x,y) and the system of differential equations of the DAE appears in the form
where
 x, a vector in , are dependent variables for which derivatives are present (differential variables),
 y, a vector in , are dependent variables for which no derivatives are present (algebraic variables),
 t, a scalar (usually time) is an independent variable.
 F is a vector of n + m functions that involve subsets these n + m variables and n derivatives.
As a whole, the set of DAEs is a function
Initial conditions must be a solution of the system of equations of the form
Examples
The pendulum in Cartesian coordinates (x,y) with center in (0,0) and length L has the EulerLagrange equations
where λ is a Lagrange multiplier. The momentum variables u and v should be constrained by the law of conservation of energy and their direction should point along the circle. Neither condition is explicit in those equations. Differentiation of the last equation leads to
restricting the direction of motion to the tangent of the circle. The next derivative of this equation implies
and the derivative of that last identity simplifies to which implicitly implies the conservation of energy since after integration the constant is the sum of kinetic and potential energy.
To obtain unique derivative values for all dependent variables the last equation was three times differentiated. This gives a differentiation index of 3, which is typical for constrained mechanical systems.
If initial values (x_{0},u_{0}) and a sign for y are given, the other variables are determined via , and if then v = − ux / y and λ = (gy − u^{2} − v^{2}) / L^{2}. To proceed to the next point it is sufficient to get the derivatives of x and u, that is, the system to solve is now
This is a semiexplicit DAE of index 1. Another set of similar equations may be obtained starting from (y_{0},v_{0}) and a sign for x.
Semiexplicit DAE of index 1
DAE of the form
are called semiexplicit. The index1 property requires that g is solvable for y. In other words, the differentiation index is 1 if by differentiation of the algebraic equations for t an implicit ODE system results,
which is solvable for if .
Every sufficiently smooth DAE is almost everywhere reducible to this semiexplicit index1 form.
Numerical treatment of DAE and applications
A major problem in the solution of DAEs is the problem of index reduction. Most numerical solvers require ordinary differential equations of the form
However it is a nontrivial task to convert arbitrary DAE systems into ODEs. Techniques which can be employed include Pantelides algorithm and dummy variable substitution.
Numerical solution of DAEs
Many physical systems are naturally described by a set of DAEs. Software can be used to attempt to solve these problems. The table below lists a number of software packages for the numerical solution of DAEs.
Name Brief info ACADO Automatic Control and Dynamic Optimization (C++ and Matlab) APMonitor Any index DAEs (Index 0 to 3 Pendulum example) DASSL/DASPK Up to index1 DAEs (and a special form of index2), sequential solution approach EMSO Jacobian (software) MATLAB Up to index1 DAEs with ode15s, sequential solution approach Modelica Applications in the auto industry OdePkg Used with Octave DAETS Use Structural Analysis and Taylor methods See also
 Delay differential equation
 Algebraic differential equation, a different concept despite the similar name
References
 Hairer, E.; Wanner, G. (1996). Solving Ordinary Differential Equations II: Stiff and DifferentialAlgebraic Problems (2nd revised ed.). Berlin: SpringerVerlag.
 Ascher, Uri M.; Petzold, Linda R. (1998). Computer Methods for Ordinary Differential equations and DifferentialAlgebraic equations. Philadelphia: SIAM. ISBN 0898714125.
 Kunkel, Peter; Mehrmann, Volker Ludwig (2006). Differentialalgebraic equations: analysis and numerical solution. Zürich, Switzerland: European Mathematical Society. ISBN 3037190175, 9783037190173. http://books.google.co.uk/books?id=iRZPqCwkI_IC.
 G. Fábián; D.A. van Beek; J.E. Rooda (2001). "Index Reduction and Discontinuity Handling using Substitute Equations". Mathematical and Computer Modelling of Dynamical Systems 7 (2): 173–187. http://se.wtb.tue.nl/~vanbeek/pub/mcmds01.pdf.
 Ilie, Silvana; Corless, Robert M.; Reid, Greg (2006). "Numerical Solutions of Differential Algebraic Equations of Index −1 Can Be Computed in Polynomial Time". Numerical Algorithms 41 (2): 161–171.
 Nedialkov, Ned S.; Pryce, John D. (2005). "Solving DifferentialAlgebraic Equations by Taylor Series (I): Computing Taylor Coefficients". BIT. http://www.cas.mcmaster.ca/~nedialk/PAPERS/DAEs/taylcoeff_I/taylorcoeffsdae.pdf.
 Nedialkov, Ned S.; Pryce, John D. (2005). "Solving DifferentialAlgebraic Equations by Taylor Series (II): Computing the System Jacobian". BIT. http://www.cas.mcmaster.ca/~nedialk/PAPERS/DAEs/taylcoeff_II/sysjac.pdf.
 Nedialkov, Ned S.; Pryce, John D. (2007). "Solving DifferentialAlgebraic Equations by Taylor Series (III): the DAETS Code". Journal of Numerical Analysis, Industrial and Applied Mathematics (JNAIAM) 1 (1): 1–30. ISSN 1790–8140. http://www.cas.mcmaster.ca/~nedialk/PAPERS/DAEs/daets/daets_color.pdf.
Categories: Differential equations
 Numerical analysis
 Differential calculus

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