Towards Integrating Hybrid DAEs with a High-Index DAE Solver

J.D. Pryce and N.S. Nedialkov have developed a Taylor series method and a C++ package, DaeTs, for solving numerically an initial-value problem differential-algebraic equation (DAE) that can be of high index, high order, nonlinear, and fully implicit. Numerical results have shown this method to be efficient and very accurate, and particularly suitable for problems that are of too high an index for present DAE solvers. However, DaeTs cannot be applied to systems of DAEs that change at points it time, also called hybrid or multi-mode DAEs. This paper presents methods for extending Daets with the capability to integrate hybrid DAEs. Methods for event location and consistent initializations are given. Daets is applied to simulate a model of a parallel robot: a hybrid system of index-3 DAEs with closed-loop control

Graph theory, irreducibility, and structural analysis of differential-algebraic equation systems

The $\Sigma$-method for structural analysis of a differential-algebraic equation (DAE) system produces offset vectors from which the sparsity pattern of a system Jacobian is derived. This pattern implies a block-triangular form (BTF) of the DAE that can be exploited to speed up numerical solution. The paper compares this fine BTF with the usually coarser BTF derived from the sparsity pattern of the \sigmx. It defines a Fine-Block Graph with weighted edges, which gives insight into the relation between coarse and fine blocks, and the permitted ordering of blocks to achieve BTF. It also illuminates the structure of the set of normalised offset vectors of the DAE, e.g.\ this set is finite if and only if there is just one coarse block

Towards Integrating Hybrid DAEs with a High-Index DAE Solver

J.D. Pryce and N.S. Nedialkov have developed a Taylor series method and a C++ package, DaeTs, for solving numerically an initial-value problem differential-algebraic equation (DAE) that can be of high index, high order, nonlinear, and fully implicit. Numerical results have shown this method to be efficient and very accurate, and particularly suitable for problems that are of too high an index for present DAE solvers. However, DaeTs cannot be applied to systems of DAEs that change at points it time, also called hybrid or multi-mode DAEs. This paper presents methods for extending Daets with the capability to integrate hybrid DAEs. Methods for event location and consistent initializations are given. Daets is applied to simulate a model of a parallel robot: a hybrid system of index-3 DAEs with closed-loop control

How AD Can Help Solve Differential-Algebraic Equations

A characteristic feature of differential-algebraic equations is that one needs to find derivatives of some of their equations with respect to time, as part of so called index reduction or regularisation, to prepare them for numerical solution. This is often done with the help of a computer algebra system. We show in two significant cases that it can be done efficiently by pure algorithmic differentiation. The first is the Dummy Derivatives method, here we give a mainly theoretical description, with tutorial examples. The second is the solution of a mechanical system directly from its Lagrangian formulation. Here we outline the theory and show several non-trivial examples of using the "Lagrangian facility" of the Nedialkov-Pryce initial-value solver DAETS, namely: a spring-mass-multipendulum system, a prescribed-trajectory control problem, and long-time integration of a model of the outer planets of the solar system, taken from the DETEST testing package for ODE solvers

Multibody dynamics in natural coordinates through automatic differentiation and high-index DAE solving

The Natural Coordinates (NCs) method for Lagrangian modelling and simulation of multibody systems is valued for giving simple, sparse models. We describe our version of it and compare with the classical approach of Jal´on and Bayo (JBNCs). Our NCs use the high-index differential-algebraic equation solver Daets. Algorithmic differentiation, not symbolic algebra, forms the equations of motion from the Lagrangian. We obtain significantly smaller equation systems than JBNCs, at the cost of a non-constant mass matrix for fully 3D models—a minor downside in the Daets context. Examples in 2D and 3D are presented, with numerical results

Conversion methods for improving structural analysis of differential-algebraic equation systems

Differential-algebraic equation systems (DAEs) are generated routinely by simulation and modeling environments. Before a simulation starts and a numerical method is applied, some kind of structural analysis (SA) is used to determine which equations to be differentiated, and how many times. Both Pantelides's algorithm and Pryce's Σ-method are equivalent: if one of them finds correct structural information, the other does also. Nonsingularity of the Jacobian produced by SA indicates a success, which occurs on many problems of interest. However, these methods can fail on simple, solvable DAEs and give incorrect structural information including the index. This article investigates Σ-method's failures and presents two conversion methods for fixing them. Both methods convert a DAE on which the Σ-method fails to an equivalent problem on which this SA is more likely to succeed

DAESA—A Matlab tool for structural analysis of differential-algebraic equations: theory

DAESA, Differential-Algebraic Equations Structural Analyzer, is a MATLAB tool for structural analysis of differential-algebraic equations (DAEs). It allows convenient translation of a DAE system into MATLAB and provides a small set of easy-to-use functions. DAESA can analyze systems that are fully nonlinear, highindex, and of any order. It determines structural index, number of degrees of freedom, constraints, variables to be initialized, and suggests a solution scheme. The structure of a DAE can be readily visualized by this tool. It also can construct a block-triangular form of the DAE, which can be exploited to solve it efficiently in a block-wise manner. This paper describes the theory and algorithms underlying the code

Making big steps in trajectories

We consider the solution of initial value problems within the context of hybrid systems and emphasise the use of high precision approximations (in software for exact real arithmetic). We propose a novel algorithm for the computation of trajectories up to the area where discontinuous jumps appear, applicable for holomorphic flow functions. Examples with a prototypical implementation illustrate that the algorithm might provide results with higher precision than well-known ODE solvers at a similar computation time