Release of OpenOCL v4.33 Getting started with OpenOCL is now easier than ever. Just download the .mltbx package and install it as a Matlab Add-in. OpenOCL is then automatically setup with your Matlab path. You don’t need to download any dependencies as CasADi will be downloaded automatically at the first run of OpenOCL. You can also install OpenOCL by browsing Matlab Add-Ons or at File Exchange. We have changed the license from v4.29 onwards to...
Release of OpenOCL v4.20
With the release of OpenOCL 4.20 the non-linear program which is constructed from the optimal control problem definition now has a block sparse structure.
This should enable the use of better structure exploiting solvers. Ipopt’s performance might improve as well. Parameters will not destroy the block sparsity structure.
Get the new release here.
Release of OpenOCL v4.00 We release OpenOCL 4.00 which from now on only support one way to define a dynamical system and optimal control problem. The old style of inheriting from OclSystem and OclOCP is not supported anymore. Get the new version of the toolbox here. The examples and documentation were updated accordingly. You now define a System as e.g. system = OclSystem(@varsfun, @eqfun); you can also use a keyword/named parameter list (in arbitrary order)...
Minor release OpenOCL v3.20
Minor release OpenOCL 3.20 with a fix for the Simulator. Download the toolbox from here.
In the upcoming weeks we are expecting a major release where the backend of OpenOCL is implemented in C++, and following that OpenOCL will become a Python interface.
New release OpenOCL v3.11 We are happy to announce that OpenOCL v3 is ready and released. It contains many improvements with respect to the previous version and also some API changes. If you come from an earlier version see the release notes that contains a list of changes below. Otherwise you can directly go to the download page of OpenOCL v3.11 or pull the latest version from the master branch. Also note that the URL...