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Package Summary
| Tags | No category tags. |
| Version | 1.2.3 |
| License | LGPL3 |
| Build type | CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Checkout URI | https://github.com/tud-cor/acado.git |
| VCS Type | git |
| VCS Version | tudelft-stable |
| Last Updated | 2019-03-28 |
| Dev Status | UNMAINTAINED |
| CI status | Continuous Integration |
| Released | RELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Ronald Ensing
Authors
- Milan Vukov
- Rien Quirynen
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.
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Recent questions tagged acado at Robotics Stack Exchange
Package Summary
| Tags | No category tags. |
| Version | 1.2.3 |
| License | LGPL3 |
| Build type | CMAKE |
| Use | RECOMMENDED |
Repository Summary
| Checkout URI | https://github.com/tud-cor/acado.git |
| VCS Type | git |
| VCS Version | tudelft-stable |
| Last Updated | 2019-03-28 |
| Dev Status | UNMAINTAINED |
| CI status | Continuous Integration : 0 / 0 |
| Released | RELEASED |
| Tags | No category tags. |
| Contributing |
Help Wanted (0)
Good First Issues (0) Pull Requests to Review (0) |
Package Description
Additional Links
Maintainers
- Ronald Ensing
Authors
- Milan Vukov
- Rien Quirynen
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.