Real-time Optimization for Distributed Model Predictive Control

Abstract:

Distributed Model Predictive Control aims to control massively complex networks of coupled subsystems in a scalable fashion. The paradigm functions by solving many small MPC optimization problems in parallel at each of the subsystems before exchanging information and repeating the process. The ability to reliably solve these small-scale problems in real-time is a critical piece of the distributed MPC puzzle, and is the focus of this talk.

I will discuss some of our recent work that brings the benefits of model predictive control to small-scale, high-speed systems and that can dramatically reduce online MPC loop execution to microsecond timescales. We show how our new real-time MPC schemes provide constraint satisfaction and stability, while optimizing for performance, at speeds several orders of magnitude faster than state-of-the-art. No single real-time optimization method will be able to tackle the broad range of possible problem classes, and so we present three techniques suitable for fast-sampled systems in the range of nano-, micro- and milli-seconds respectively. The controller synthesis methodologies are unique in that they take the available online computational resources as input and produce a controller that will execute within these bounds while satisfying constraints and stabilizing the system.

I will motivate our work on real-time MPC with several applications, including wave power systems, camera networks, racing cars and smart power grids. Industrial examples will be presented throughout, which serve to highlight theoretical advancements and the extensive software tools that help to bring the developed theory to bear in practical scenarios.

Slides

Video

Biography:Manfred Morari was appointed head of the Department of Information Technology and Electrical Engineering at ETH Zurich in 2009. He was head of the Automatic Control Laboratory from 1994 to 2008. Before that he was the McCollum-Corcoran Professor of Chemical Engineering and Executive Officer for Control and Dynamical Systems at the California Institute of Technology. He obtained the diploma from ETH Zurich and the Ph.D. from the University of Minnesota, both in chemical engineering. His interests are in hybrid systems and the control of biomedical systems. In recognition of his research contributions he received numerous awards, among them the Donald P. Eckman Award and the John R. Ragazzini Award of the Automatic Control Council, the Allan P. Colburn Award and the Professional Progress Award of the AIChE, the Curtis W. McGraw Research Award of the ASEE, Doctor Honoris Causa from Babes-Bolyai University, Fellow of IEEE, the IEEE Control Systems Field Award, and was elected to the National Academy of Engineering (U.S.). Manfred Morari has held appointments with Exxon and ICI plc and serves on the technical advisory boards of several major corporations.