The mission of ODYS is to transform abstract mathematical models and numerical algorithms into concrete software solutions that allow customers to optimize their products and processes. We aim at spreading the use of model predictive control and real-time optimization in companies and institutions, being confident that they are key to improve product performance while cutting costs, saving resources, and contributing to a cleaner environment. To achieve this mission, ODYS carefully customizes its software solutions to understand and meet the unique needs of its clients.
Founded by leading researchers in model predictive control and embedded optimization, ODYS leverages on a background of more than twenty years of research expertise. Such know-how is now offered by ODYS as an advanced consulting service to the market.
The name ODYS captures the core technology of the company: Optimization of Dynamical Systems. With our products, the dynamics of a process are controlled continuously by numerical optimization algorithms, that maximize performances under the best use of the available resources.
Dr. Daniele Bernardini received his master’s degree in Computer Engineering in 2007 and his Ph.D. in Information Engineering in 2011 from the University of Siena, Italy, specializing in automatic control. In 2011-2015 he was with the Dynamical Systems, Control and Optimization (DYSCO) research unit at IMT Lucca as a post-doctoral fellow. His main research interests are in model predictive control, stochastic control, networked control systems, hybrid systems, and their application to problems in the automotive, aerospace, and energy domains. See his Google Scholar webpage.
Prof. Alberto Bemporad received his master’s degree in Electrical Engineering in 1993 and his Ph.D. in Control Engineering in 1997 from the University of Florence, Italy. After being with the ETH Zurich, Switzerland, the University of Siena, Italy, and the University of Trento, Italy, in 2011 he joined the IMT Institute for Advanced Studies Lucca, Italy, as a full professor. He was the Director of the institute in 2012-2015. He has published about 300 scientific contributions in control systems, optimization, and their application in several domains. He is author or coauthor of various MATLAB toolboxes for model predictive control design, including the Model Predictive Control Toolbox (The Mathworks, Inc.) and the Hybrid Toolbox. He is IEEE Fellow since 2010. More details on his personal webpage and Google Scholar webpage.