Decentralized Control of Nonlinear Interconnected Chemical Processes

Dr. Nicolas Hudon, INMA, Universite Catholique de Louvain, Belgium


16 March 2015 at 11:30

Location: JHE 342

In this talk, we consider the problem of designing decentralized feedback controllers for interconnected chemical processes.  In many engineering fields, decentralized and distributed control algorithms have emerged to solve synchronization and coordination problems as cheap and reliable network devices are now available.  However, some characteristics of chemical processes limit the direct application of those algorithms in chemical engineering.  In this research we exploit nonlinear dissipative systems theory to develop a general framework for the analysis and decentralized feedback control design of interconnected chemical processes. 

The main objective of the proposed approach is to design decentralized feedback controllers such that plant-wide stability is guaranteed and such that performance objectives are met for some interconnection structure.  At a plant-wide level, extensions of classical results on the stability of large-scale interconnected systems lead to input-output constraints for each subsystems, encoded as supply rates from input to output interconnecting ports. Then, for each subsystem, a parameterized nonlinear feedback controller is designed using nonlinear dissipative inequalities to ensure that the aforementioned constraints are met in closed-loop. 

The key advantage of using parameterized controller is the possibility to balance local and global objectives.  We develop extensions of the approach for uncertain systems and systems evolving on different time-scales.  As dissipative systems theory offers a physically-motivated perspective to control theory, we also discuss a recently-developed approach to model and represent chemical systems which is based on non-equilibrium thermodynamics, taking into account the first and second laws in the dynamical modeling of chemical systems. 

Impacts of this approach on analysis and design in the context of decentralized feedback control design are discussed. 

Finally, we discuss some current investigations and potential extensions of this research to address the problems of robustness, adaptation, and optimality of the proposed design methodology.

 


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