Reference number : GC-2017-Q1-01817, amendment number : , agreement type : G, recipient legal name : Hudon, Nicolas (Queen’s University), recipient country : CA, recipient province : nan, recipient city : Ontario, recipient postal code : nan, program name english : Discovery Grants Program - Individual, program name french : Programme de subventions à la découverte - individuelles, program purpose english : Due to growing financial and environmental pressures, design and operation of sustainable processes are central challenges to chemical engineering science and practice. Renewable energy production and effluent treatment processes need to be operated in a consistent manner to meet performance and environmental objectives and ensure the viability of Canadian industries. As sustainable processes are highly integrated to reduce material and energy consumption, these processes are complex networks of interconnected sub-processes. Classical control strategies are limited for integrated processes as their inherent complexity renders analysis and control design computationally intractable. 
 
The novelty of this research consists in using physics-based models to extract essential dynamical features driving a given chemical process unit and measure its impact on plant-wide operation. It was demonstrated in previous research that it is possible to improve distributed control design for interconnected chemical sub-processes exchanging mass and energy using structured models. The objective of this research is to generalize this approach to address challenges impeding optimal operation of sustainable process systems. This research will focus on critical problems hindering the operation of sustainable processes. In particular, the proposed framework will measure the propagation of uncertainties and disturbances in interconnected systems. New robust control and on-line estimation methodologies will be developed to mitigate the effects of uncertainties and external disturbances on process performance. This research will have impact on the operation of viable sustainable chemical processes in the Canadian industry. 
 
Through this research, high qualified personnel (HQP) will develop nonlinear controllers and soft-sensors for process applications. This research will yield to significant theoretical results in the fields of distributed nonlinear process control; in particular, for the control of uncertain, time-varying, and interconnected systems. This research will have impacts on nonlinear process control theory and practice. HQP will demonstrate the outcomes of this research program on practical applications. In collaboration with industrial partners involved with sustainable chemical processes operation, the distributed control algorithms resulting from this research program will be implemented on physical processes. HQP trained through this research program will develop theoretical and practical knowledge in process control. The products of this research program will be disseminated through publications and direct industrial applications, ensuring maximal benefits for HQP and industrial partners. The developed model-based control techniques will support the development of a Canadian sustainable chemical industry., program purpose french : Due to growing financial and environmental pressures, design and operation of sustainable processes are central challenges to chemical engineering science and practice. Renewable energy production and effluent treatment processes need to be operated in a consistent manner to meet performance and environmental objectives and ensure the viability of Canadian industries. As sustainable processes are highly integrated to reduce material and energy consumption, these processes are complex networks of interconnected sub-processes. Classical control strategies are limited for integrated processes as their inherent complexity renders analysis and control design computationally intractable. 
 
The novelty of this research consists in using physics-based models to extract essential dynamical features driving a given chemical process unit and measure its impact on plant-wide operation. It was demonstrated in previous research that it is possible to improve distributed control design for interconnected chemical sub-processes exchanging mass and energy using structured models. The objective of this research is to generalize this approach to address challenges impeding optimal operation of sustainable process systems. This research will focus on critical problems hindering the operation of sustainable processes. In particular, the proposed framework will measure the propagation of uncertainties and disturbances in interconnected systems. New robust control and on-line estimation methodologies will be developed to mitigate the effects of uncertainties and external disturbances on process performance. This research will have impact on the operation of viable sustainable chemical processes in the Canadian industry. 
 
Through this research, high qualified personnel (HQP) will develop nonlinear controllers and soft-sensors for process applications. This research will yield to significant theoretical results in the fields of distributed nonlinear process control; in particular, for the control of uncertain, time-varying, and interconnected systems. This research will have impacts on nonlinear process control theory and practice. HQP will demonstrate the outcomes of this research program on practical applications. In collaboration with industrial partners involved with sustainable chemical processes operation, the distributed control algorithms resulting from this research program will be implemented on physical processes. HQP trained through this research program will develop theoretical and practical knowledge in process control. The products of this research program will be disseminated through publications and direct industrial applications, ensuring maximal benefits for HQP and industrial partners. The developed model-based control techniques will support the development of a Canadian sustainable chemical industry., agreement title english : Distributed Control and Estimation of Sustainable Chemical Process Systems, agreement title french : Distributed Control and Estimation of Sustainable Chemical Process Systems, agreement number : RGPIN, agreement value : 110000.0, agreement start date : 2017-05-10, agreement end date : nan, description english : nan, description french : nan, expected results english : nan, expected results french : nan, additional information english : Grant or Award spanning more than one fiscal year. (2017-2018 to 2022-2023), additional information french : Subvention ou bourse octroyée s'appliquant à plus d'un exercice financier. (2017-2018 à 2022-2023), owner organization : nserc-crsng, owner organization title : Natural Sciences and Engineering Research Council of Canada | Conseil de recherches en sciences naturelles et en génie du Canada