Pushing predictive controllers, which require the solution of an optimization problem at each sampling interval, into the millisecond range opens up both new possibilities, as well as new challenges for control. Computational limits placed on standard convex solvers invalidate basic assumptions made when proving the stability, or invariance of constrained control laws and as a result cannot be used in fast, real-time implementations with confidence.
This talk will present two optimization methods that can be proven to stabilize a system and enforce constraints, even for extremely short computational times or in the presence of time jitter. We'll report on two fast 'code-generation' toolboxes: FiOrdOs, for first-order, and FORCES, for second order methods and demonstrate their capabilities through application examples.
Colin Jones is an Assistant Professor in the Automatic Control Laboratory at the Ecole Polytechnique Federale de Lausanne (EPFL) in Switzerland. He was a Senior Researcher at the Automatic Control Lab at ETH Zurich until 2010 and obtained a PhD 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 a BASc and MASc in Electrical Engineering and Mathematics. Colin has worked in a variety of industrial roles, ranging from control of heating, ventilation and air conditioning to ballistic missile interception. He was co-founder of Apex Optimization; a custom optimization house that focuses on human resource scheduling. His current research interests are in the areas of high-speed predictive control and optimization, as well as green energy generation, distribution and management.