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 | 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 | 1.2.3 |
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/tud-cor/acado.git |
VCS Type | git |
VCS Version | tudelft-stable |
Last Updated | 2019-03-28 |
Dev Status | UNMAINTAINED |
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 | 1.2.3 |
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.