Seminars

In the context of optimal control and sampled-data model predictive control, we discuss a few phenomena that are better understood when using continuous-time models (stability, discontinuous feedbacks, bang-bang control, path-following, impulsive systems).
We also show how nonlinear optimal control problems can be more efficiently solved when a continuous-time model is used until a later stage, by using recently developed adaptive grid refinement techniques.

Fernando A.C.C. Fontes is Associate Professor in the Department of Electrical and Computer Engineering, Faculty of Engineering, University of Porto and researcher in Systec - Institute of Systems and Robotics  (ISR). He received the first degree from the University of Porto, and the M.Sc. in Control Systems as well as the Ph.D.  degrees from Imperial College London, U.K. He started his carrier by joining the Department of Mathematics of University of Minho, Portugal, He taught in the Department of Operational Research at LSE - The London School of Economics and was a Research Assistant in the Centre for Process Systems Engineering at Imperial College London. He later returned to University of Minho, where he became associated professor, served as Director of the first degree in Applied Mathematics (2003-05) and Head of the Department (2006-07). In 2009, he moved to the present position at University of Porto and joined ISR, where he now coordinates the Systec –Control thematic line. He has been teaching in the areas of Mathematics, Signal Processing, Systems and Control, as well as Automation and Robotics. During 2015/16 , he is spending the sabbatical year as a Visiting Scholar in the Department of Electrical and Computer Engineering at Texas A&M. His research interests are in optimization and control theory, having a specific interest in nonlinear problems, optimal control, and model predictive control.

Personal webpage: http://www.fe.up.pt/~faf