摘要：AbstractProcess 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 which 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, 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.
关键词：KeywordsProcess operational safetyEconomic model predictive controlSafeness IndexNonlinear systemsChemical processesProbabilistic uncertainty
