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Dynamic optimization with CasADi

Author

  • Joel Andersson
  • Johan Åkesson
  • Moritz Diehl

Summary, in English

We demonstrate how CasADi, a recently devel- oped, free, open-source, general purpose software tool for nonlinear optimization, can be used for dynamic optimization in a flexible, interactive and numerically efficient way.

CasADi is best described as a minimalistic computer al- gebra system (CAS) implementing automatic differentiation (AD) in eight different flavors. Similar to algebraic modeling languages like AMPL or GAMS, it includes high-level interfaces to state-of-the-art numerical codes for nonlinear program- ming, quadratic programming and integration of differential- algebraic equations. CasADi is implemented in self-contained C++ code and contains full-featured front-ends to Python and Octave for rapid prototyping.

In this paper, we discuss CasADi from the perspective of the developer or advanced user of algorithms for dynamic optimization for the first time, leaving out details on the implementation of the tool. We demonstrate how the tool can be used to model highly complex dynamical systems directly or import existing models formulated in the algebraic modeling language AMPL or the physical modeling language Modelica. Given this symbolic representation of the process models, the resulting optimal control problem can be solved using a vari- ety of methods, including transcription methods (collocation), methods with embedded integrators (multiple shooting) as well as indirect methods.

Publishing year

2012

Language

English

Pages

681-686

Publication/Series

IEEE 51st Annual Conference on Decision and Control (CDC), 2012

Document type

Conference paper

Publisher

IEEE - Institute of Electrical and Electronics Engineers Inc.

Topic

  • Control Engineering

Conference name

51st IEEE Conference on Decision and Control, 2012

Conference date

2012-12-10 - 2012-12-13

Conference place

Maui, Hawaii, United States

Status

Published

Project

  • LCCC

Research group

  • LCCC

ISBN/ISSN/Other

  • ISSN: 0743-1546
  • ISBN: 978-1-4673-2065-8