Repository Summary
| Checkout URI | https://github.com/clearpath-gbp/acado-release.git |
| VCS Type | git |
| VCS Version | upstream-patched |
| Last Updated | 2015-03-16 |
| Dev Status | MAINTAINED |
| CI status | No Continuous Integration |
| Released | RELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Packages
| Name | Version |
|---|---|
| acado | 1.2.1 |
README
ACADO Toolkit 
Toolkit for Automatic Control and Dynamic Optimization
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 interface. The object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines.
More information about the toolkit can be found at the homepage.
CONTRIBUTING
Repository Summary
| Checkout URI | https://github.com/clearpath-gbp/acado-release.git |
| VCS Type | git |
| VCS Version | upstream-patched |
| Last Updated | 2015-03-16 |
| Dev Status | MAINTAINED |
| CI status | No Continuous Integration |
| Released | RELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Packages
| Name | Version |
|---|---|
| acado | 1.2.1 |
README
ACADO Toolkit
Toolkit for Automatic Control and Dynamic Optimization
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 interface. The object-oriented design allows for convenient coupling of existing optimization packages and for extending it with user-written optimization routines.
More information about the toolkit can be found at the homepage.