.. Metacontrol documentation master file, created by sphinx-quickstart on Sat May 2 15:39:54 2020. You can adapt this file completely to your liking, but it should at least contain the root `toctree` directive. Metacontrol: A metamodel based toolbox for self-optimizing control structure selection ====================================================================================== Metacontrol is a Python based software which assembles several methodologies into a single bundle so that a fast implementation of the Self-Optimizing Control (SOC) technique can be achieved. .. list-table:: * - .. figure:: /images/feature_aspen.png :scale: 45% :align: center .. Use the process models that you created in Aspen Plus. - .. figure:: /images/feature_kriging.png :scale: 45% :align: center .. Generate Kriging surrogate models of your processes. * - .. figure:: /images/feature_opt.png :scale: 45% :align: center .. Optimize your kriging surrogate models. - .. figure:: /images/feature_soc.png :scale: 45% :align: center .. Generate the best self-optimizing control structures. How to cite us ============== .. _our_papers: Our papers ----------- Please, cite the related papers: #. `Metamodel-Based Numerical Techniques for Self-Optimizing Control `_; **BibTeX Entry:** .. code-block:: none @article{alves2018metamodel, title={Metamodel-Based Numerical Techniques for Self-Optimizing Control}, author={Alves, Victor MC and Lima, Felipe S and Silva, Sidinei K and Araujo, Antonio CB}, journal={Industrial \& Engineering Chemistry Research}, volume={57}, number={49}, pages={16817--16840}, year={2018}, publisher={ACS Publications} } #. `Metacontrol: A Python based application for self-optimizing control using metamodels `_; **BibTeX Entry:** .. code-block:: none @article{lima2020metacontrol, title={Metacontrol: A Python based application for self-optimizing control using metamodels}, author={Lima, Felipe Souza and Alves, Victor Manuel Cunha and de Araujo, Antonio Carlos Brandao}, journal={Computers \& Chemical Engineering}, volume = {140}, pages = {106979}, year = {2020}, issn = {0098-1354}, doi = {https://doi.org/10.1016/j.compchemeng.2020.106979}, url = {http://www.sciencedirect.com/science/article/pii/S0098135420303355}, publisher={Elsevier} } And become a watcher/stargazer on `GitHub `_ to receive updates! Features ============== Open-Source ============== *Metacontrol* is **open-source**, under the **GPL v3.0** license. We believe that open code just makes scientific development clearer and generally better. Want to inspect our code? Maybe change it for your specific desire? Have a suggestion? Go for it. Share with us! Built in Python ================ The scientific world and data scientists are moving in a accelerated pace to Python programming language. *Metacontrol* was built from scratch using it. Using state-of-the-art packages such as `Numpy `_, `Scipy `_, `pyQT `_, `pandas `_ and many others, a concise and standalone software is available. You will **not** need any other software, apart from the process simulators (obviously), to run our application. Support for Optimization using metamodels ========================================== One crucial step of Self-Optimizing Control methodology is to optimize a process model. We use the the famous `IpOpt `_ Optimization package (using a `Python Interface `_) in order to do it. Therefore, you can also use *Metacontrol* to optimize processes that you modeled in Aspen Plus. Usage of Kriging metamodels ============================ Kriging interpolators are widely used in the scientific community for prediction, optimization and data obtainment. We use it for optimization and high-order data obtainment purposes. It is proven to generate robust precitions and results. For further details, check :ref:`our_papers`. State-of-the-art Self-Optimizing Control techniques ==================================================== Standing on the shoulders of giants, *Metacontrol* uses the most recent formulations in the SOC area available that are capable of quickly pre-screening the most promising candidate controlled variables from a given universe of possible combinations. This includes the exact local Method with explicit solution from :cite:`alstad09` and even branch-and-bound algorithms :cite:`kariwala2009` under the hood. Documentation Contents ================================== .. toctree:: :maxdepth: 2 intro overview/mtc gui/gui_index.rst examples/tutorials theory/theory_index zbibliography Contact ======== .. figure:: /images/felipe_profile.jpg :align: center .. | Felipe Lima, Msc. | Federal University of Campina Grande | email: felipe.lima@eq.ufcg.edu.br   .. figure:: /images/victor_profile.jpg :align: center .. | Victor Alves, Msc. | Federal University of Campina Grande | email: victor.alves@eq.ufcg.edu.br