My research is on the development of new control theory and mathematical optimization methods for the design of cyber-physical systems, where physical systems affect computations and vice versa in a closed loop - by incorporating computational elements one can design systems with functionalities that are impossible by physical design alone. I am particularly interested in the interplay between the complexity of the algorithms, computing architecture and physical realization, and how these complexities need to be traded off to satisfy given system-wide performance specifications. Central to my work is the use of powerful optimization-based control methods, such as model predictive control (MPC), to handle nonlinearities and uncertainties in a systematic fashion. My particular expertise is in the design of efficient numerical methods and embedded computing architectures for solving advanced optimization, control and estimation problems in real-time. My theoretical research is motivated by and applied to a variety of problems in the design of aerospace, renewable energy and computing systems.
See my Google Scholar page for my most recent publications and preprints.
PHD STUDENTSHIPS AVAILABLE
EPSRC Centre for Doctoral Training in High-performance Embedded and Distributed Systems: If you are interested in doing a PhD under my supervision in the area of model predictive control and optimization of computing systems or cyber-physical systems, please go to the HiPEDS applications page for details on how to apply for a position and studentship. I am particularly looking for an outstanding student interested in a project that is in collaboration with Mathworks, the creators of Matlab and Simulink.
ECC 2016 Tutorial Session on Embedded Optimization: Presentations can be downloaded here.
My talk on co-design of optimization-based controllers, given at MATLAB EXPO 2015, is now available.
2006-present: Department of Aeronautics and Department of Electrical and Electronic Engineering, Imperial College London
- 2014: Sabbatical Visitor, Department of Electrical and Electronic Engineering, University of Melbourne
- 2002-2007: Royal Academy of Engineering Research Fellow, University of Cambridge and Imperial College London
2001-2005: Research Fellow, Wolfson College and Department of Engineering, University of Cambridge
2001-2002: Research Associate, Department of Engineering, University of Cambridge
1997-2001: PhD in Control Engineering, St John's College and Department of Engineering, University of Cambridge
1997: Electromechanical Engineer, Council for Scientific and Industrial Research (CSIR), South Africa
1993-1996: BSc(Eng) in Electrical Engineering, University of Cape Town
et al., 2014, Embedded Online Optimization for Model Predictive Control at Megahertz Rates, IEEE Transactions on Automatic Control, Vol:59, ISSN:0018-9286, Pages:3238-3251
Jerez JL, Constantinides GA, Kerrigan EC, 2015, A Low Complexity Scaling Method for the Lanczos Kernel in Fixed-Point Arithmetic, IEEE Transactions on Computers, Vol:64, ISSN:0018-9340, Pages:303-315
et al., 2013, Predictive control using an FPGA with applicationto aircraft control, IEEE Transactions on Control Systems Technology, Vol:22, ISSN:1558-0865, Pages:1006-1017
Shahzad A, Kerrigan EC, Constantinides GA, 2012, A Stable and Efficient Method for Solving a Convex Quadratic Program with Application to Optimal Control, SIAM Journal on Optimization, Vol:22, ISSN:1052-6234, Pages:1369-1393
Jones BL, Kerrigan EC, 2010, When is the discretization of a spatially distributed system good enough for control?, Automatica, Vol:46, ISSN:0005-1098, Pages:1462-1468
Goulart PJ, Kerrigan EC, Ralph D, 2008, Efficient robust optimization for robust control with constraints, Mathematical Programming, Vol:114, ISSN:0025-5610, Pages:115-147
Goulart, P.J., Kerrigan, E.C., Maciejowski, J.M., 2006, Optimization over state feedback policies for robust control with constraints, Automatica, Vol:42, ISSN:0005-1098, Pages:523-533
Kerrigan EC, 2015, Feedback and Time are Essential for the Optimal Control of Computing Systems, Pages:380-387, ISSN:2405-8963
et al., 2015, Computer Architectures to Close the Loop in Real-time Optimization, 54th IEEE Conference on Decision and Control (CDC), IEEE, Pages:4597-4611
Kerrigan EC, 2014, Co-design of Hardware and Algorithms for Real-time Optimization, 2014 European Control Conference (ECC), IEEE, Pages:2484-2489