Document Type

Conference Proceeding

Abstract

Lyapunov-based economic model predictive control (LEMPC) is an optimization-based control design that computes economically-optimal control actions for a process while maintaining the closed-loop state within a bounded region of state-space; however, it may be difficult to design in practice without closed-loop simulations, as it requires an auxiliary stabilizing controller, Lyapunov function, and a number of sets to be developed to ensure closed-loop stability. Practical application of this method could benefit from methods which make it more likely that, without simulations to identify aspects of the control design that would provide stability, controller parameters can be selected that would maintain stability. In this work, we propose a method to seek to enhance tractability of LEMPC by providing initial suggestions for reducing the likelihood that ad hoc selection of a value for one of its parameters would be problematic for closed-loop stability.

Disciplines

Controls and Control Theory | Process Control and Systems

Comments

© American Automatic Control Council (AACC) 2020. Peer Reviewed Conference Proceeding, 2020 American Control Conference (ACC), July 1-3, 2020, Denver, CO, USA. Originally published at https://doi.org/10.23919/ACC45564.2020.9147880. Financial support from the National Science Foundation CBET-1839675 and Wayne State College of Engineering start-up funding is gratefully acknowledged. 

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