Education
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2010 |
PhD |
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2004 |
MASc |
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2002 |
BEng |
Experience
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2016 - ... |
Assistant Professor |
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2015 - 16 |
Visiting Researcher |
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2012 - 15 |
Postdoctoral Fellow |
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2010 - 12 |
Postdoctoral Fellow |
Research Interests
Physics-based Approaches for Process Systems Engineering
As the complexity of physical processes under study increased in the last decades, research in the field of PSE, and in particular process control, sought to develop new strategies, and generally speaking, more evolved model-based frameworks, to achieve systems analysis and design to meet (dynamic) performance and robustness objectives. One route toward this general objective was to develop detailed conservation laws for mass, momentum, energy, and entropy balances, with suitable constitutive relationships. As a result, a paradox emerged from a systems science standpoint. These detailed models were often of limited applicability in Process Systems Engineering because of their complexity. This led some researchers to consider physical models with known particular structures in order to facilitate analysis and design while retaining a maximum of modeling details and accuracy. Analysis and control design for systems described using potential-based representations, in particular Port-Hamiltonian Systems (PHS), emerged as a viable modeling, simulation and control framework for finite and infinite dimensional systems and both deterministic and stochastic systems. This approach is now central to nonlinear control theory. Stability analysis, feedback control design, and observer design are greatly simplified for dynamical systems or interconnected systems modeled or re-expressed as PHS. Analysis carried on PHS models are not limited to control theory, as exemplified by applications from the field of physics-based numerical integration, where conservation principles are enforced to improve known numerical methods. Applications of PSE methods to irreversible systems, for example reacting systems and systems generating entropy, pose additional challenges. The objective of this project is to develop a framework for the modeling, analysis, optimal design, and control design of nonlinear physical systems subjected to irreversible evolution constraints from the field of Process Systems Engineering (PSE). The proposed research seeks to consider interconnected dynamical systems following general conservation laws. In the proposed research, these dynamical systems may be described by ordinary differential equations (finite dimensional systems), partial differential equations (infinite dimensional systems), stochastic differential equations, and/or algebraic differential equations. As an extension of previous studies on chemical process systems in the context of nonlinear feedback control design, the central tool to be considered in the achievement of this objective is to extend methods developed for mechanical systems to chemical systems to solve problems from the field of PSE. Expected developments would seek to cover, in a unified way, the key relevant subfields of PSE: Modeling and identification; Design and otpimization; Process control and on-line estimation; Scheduling and fault-tolerant design; and Numerical methods.
Fall
CHEE 321: Chemical Reaction Engineering
Winter
Publications for Nicolas Hudon please visit google scholar