InitDAE is a prototype written in Python that computes consistent initial values of differential–algebraic equations (DAE), determines their index and a related condition number that permits the diagnosis of singularities. The algorithm for the consistent initialization uses a projector based constrained optimization approach and the inherent differentiations are provided by automatic differentiation (AD), using AlgoPy. Consequently, a detailed description of the local structural properties of the DAE becomes possible using the SVD. InitDAE has been conceived for academic purposes and is well-suited for examples of moderate size. In this article we give an overview of the algorithm, show actual features and discuss future possibilities, in particular the integration with Taylor series methods.
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References in zbMATH (referenced in 3 articles , 1 standard article )
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- Estévez Schwarz, Diana; Lamour, René: InitDAE: computation of consistent values, index determination and diagnosis of singularities of DAEs using automatic differentiation in Python (2021)
- Estévez Schwarz, Diana; Lamour, René: A projector based decoupling of DAEs obtained from the derivative array (2020)
- Schwarz, Diana Estévez; Lamour, René; März, Roswitha: Singularities of the robotic arm DAE (2020)