Process Analytics, Optimization and Control

Queen's control researchers are a group of international reputation which boast a depth and breadth that is unique in Canada. Current research activities in areas such as applied statistics, process control, control theory, systems analysis and system modeling have identified the Queen's control community internationally as an independent and innovative group, with a perfect blend of technical and practical skills. The group's approach to control research, driven by both industrial applications and technical innovation, has been collaborative and interdisciplinary. Our main focus has been on the analysis, design and implementation of supervisory control strategies that assembles many different technologies in an attempt to yield significant advancement over current practice while providing tangible benefits for industry.

1) High performance process control

High performance process control is a class of controller design techniques whose objective is to ensure a given degree of performance that remains, as much as possible, invariant to the choice of operating point. High performance process control techniques are very important for the efficient implementation of plant wide strategies in which the regulation of a given process may be required over wide ranges of operating policies. Our recent research in this area has been focused on the applications of these techniques to the design of high performance process control schemes in chemical processes.

2) Control, Optimization and Supervision

Chemical and petrochemical plants are highly integrated environments where thousands of operations can take place simultaneously. The control, optimization and supervision of such environments are extremely complex and require considerable machinery to handle. In fact, it remains difficult, if not impossible, to address such problems in a systematic manner. Our research proposes to use emerging technologies that can be useful to the problems faced in integrated processes including; hybrid systems control, real-time optimization, process monitoring, controller performance assessment and multivariate statistics.

Meet Emmanuel Ogbe, a PhD candidate researching optimization:

PhD Candidate Emmanuel Ogbe from Queen's Engineering on Vimeo.




Research Interests

Martin Guay

Dupuis 406
(613) 533-2788

Nonlinear process control, Economic optimization control, Adaptive Control of Nonlinear Systems, Analysis of Biological Systems, Control and Estimation of Systems Described by PDEs

Thomas J. Harris

(613) 533-6771

Process control, Process monitoring, Controller performance assessment, Statistical methods in chemical engineering

Nicolas Hudon

Assistant Professor
Dupuis Hall 304
(613) 533-2787

Chemical process modeling, control and optimization; Decentralized nonlinear control; Physically-based methods in nonlinear stabilizing control

Xiang Li
Associate Professor
Dupuis Hall 403
(613) 533-6582

Process design and operation, supply chain management, planning and scheduling, model predictive control, energy and water networks, global optimization, optimization under uncertainty

Kim B. McAuley

Gordon 425
(613) 533-6000 ext 77562

Mathematical modeling, Applied statistics, Process control, Polymer reaction engineering, Nylon polymerization, Polymer gel dosimetry

P. James McLellan

Dupuis 316
(613) 533-2785

Functional data analysis, Statistical methods for chemical process modeling, Process control, Fault detection, Real-time optimization