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

• Main Authors: Zhe Wu, Helen Durand, Panagiotis D. Christofides
• Format: Article
• Language: English
• Published: MDPI AG 2018-05-01
• Series: Mathematics
• Subjects: process operational safety; economic model predictive control; Safeness Index; nonlinear systems; chemical processes; probabilistic uncertainty
• Online Access: http://www.mdpi.com/2227-7390/6/5/69

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.