OpenOCL v5.08 now supports multi-stage problems. Multi-stage problems arrise when the dynamics change during the trajectory (spacecraft re-entry, multiple stages of a rocket), or they can be used to model. We also created some channels for you to ask questions or share your work with OpenOCL!
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.
Modeling is an integral part of engineering and probably any other domain. With the popularity of machine learning a new type of black box model in form of artificial neural networks is on the way of replacing in parts models of the traditional approaches. However we think that this does not mean that traditional models will be less significant, but they might get even more important in some domains. Traditional models can for example be used to feed the deep learning algorithms that (at the moment) are hungry for large amounts of data, by generating data using classical modeling approaches.
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.
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.
Mustafa Alp from the Polytechnic University of Milan sent us a great video of his implementation with the OpenOCL toolbox.
Minor release OpenOCL 3.20 with a fix for the Simulator.
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.