Abstract

The field of fast-MPC, or the use of embedded optimization for high speed control, is a rapidly growing field in academia and increasingly in industry. Achieving the required extremely high speed optimization, often within micro-seconds, on low-end embedded platforms calls for a wide range of heuristic procedures for both the control design, as well as in the implementation of the optimization algorithms themselves. This semi-heuristic process leads to complex control laws that can be very effective, but that are also extremely difficult to tune and design. This talk will introduce a framework for the non-conservative analysis of many of the heuristics used in these controllers via a convex sum-of-squares approach. We will then build on this framework to develop a formal optimal synthesis procedure for very high-speed embedded optimization-based control laws.

Bio:

Colin Jones is an Assistant Professor in the Automatic Control Laboratory at the EPFL in Switzerland. He was a Senior Researcher at the Automatic Control Lab at ETH Zurich until 2010 and obtained a Ph.D. in 2005 from the University of Cambridge for his work on polyhedral computational methods for constrained control. Prior to that, he was at the University of British Columbia in Canada, where he took his bachelor and master degrees in Electrical Engineering and Mathematics. His current research interests are in the areas of high-speed predictive control and optimization, as well as green energy generation, distribution and management.