Safeness Index-Based Economic Model Predictive Control of Stochastic Nonlinear Systems

Zhe Wu, Helen Durand and Panagiotis D. Christofides
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Zhe Wu: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095-1592, USA
Helen Durand: Department of Chemical Engineering and Materials Science, Wayne State University, Detroit, MI 48202, USA
Panagiotis D. Christofides: Department of Chemical and Biomolecular Engineering, University of California, Los Angeles, CA 90095-1592, USA

Mathematics, 2018, vol. 6, issue 5, 1-19

Abstract: Process operational safety plays an important role in designing control systems for chemical processes. Motivated by this, in this work, we develop a process Safeness Index-based economic model predictive control system for a broad class of stochastic nonlinear systems with input constraints. A stochastic Lyapunov-based controller is first utilized to characterize a region of the state-space surrounding the origin, starting from which the origin is rendered asymptotically stable in probability. Using this stability region characterization and a process Safeness Index function that characterizes the region in state-space in which it is safe to operate the process, an economic model predictive control system is then developed using Lyapunov-based constraints to ensure economic optimality, as well as process operational safety and closed-loop stability in probability. A chemical process example is used to demonstrate the applicability and effectiveness of the proposed approach.

Keywords: process operational safety; economic model predictive control; Safeness Index; nonlinear systems; chemical processes; probabilistic uncertainty (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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