A framework for direct optimal control, model predictive control, state and parameter estimation...
|8 Apr 2010||David||
ACADO Toolkit is a software environment and algorithm collection 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, state and parameter estimation and robust optimization. ACADO Toolkit is implemented as self-contained C++ code and comes along with user-friendly Matlab interfaces. The object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines.
ACADO Toolkit for Matlab is a Matlab interface for ACADO Toolkit. It brings the ACADO Integrators and algorithms for direct optimal control, model predictive control and parameter estimation to Matlab. ACADO Toolkit for Matlab uses the ACADO Toolkit C++ code base and implements methods to communicate with this code base.
The key properties of ACADO Toolkit for Matlab are:
* No knowledge of C++ required: No C++ knowledge (both syntax and compiling) should be required to use the interface. Therefore ACADO Toolkit for Matlab is the perfect way to start using ACADO Toolkit when you are familiar with Matlab but
* Familiar Matlab syntax and workspace: The interface should not be an identical duplicate of the C++ version but should make use of Matlab style notations. On the one hand, it should be possible to directly use variables and matrices stored in the
* Use Matlab black box models: Although the ACADO Toolkit supports a symbolic syntax to write down dierential (algebraic) equations the main property of the interface is to link (existing) Matlab black box models to ACADO Toolkit. Moreover, in addition to Matlab black box models also C++ black box models can be used in the interface.
* Cross-platform: The interface should work on the most popular platforms around: Linux, Windows and Mac (more about this in Section 1.4).