Article ID: | iaor201112226 |
Volume: | 32 |
Issue: | 3 |
Start Page Number: | 298 |
End Page Number: | 312 |
Publication Date: | May 2011 |
Journal: | Optimal Control Applications and Methods |
Authors: | Houska Boris, Diehl Moritz, Ferreau Hans Joachim |
Keywords: | programming: dynamic, time series: forecasting methods |
In this paper the software environment and algorithm collection ACADO Toolkit is presented, which implements tools for automatic control and dynamic optimization. It provides a general framework for using a great variety of algorithms for direct optimal control, including model predictive control as well as state and parameter estimation. The ACADO Toolkit is implemented as a self-contained C++ code, while the object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines. We discuss details of the software design of the ACADO Toolkit 1.0 and describe its main software modules. Along with that we highlight a couple of algorithmic features, in particular its functionality to handle symbolic expressions. The user-friendly syntax of the ACADO Toolkit to set up optimization problems is illustrated with two tutorial examples: an optimal control and a parameter estimation problem.