(359g) Safeness Index-Based Economic Model Predictive Control of Stochastic Nonlinear Systems

Process operational safety plays an important role in designing control systems for chemical processes since failure to ensure process safety often leads to disastrous incidents potentially causing human and capital loss [1]. Recently, a new class of economic model predictive control systems (EMPC) was developed to simultaneously ensure process operational safety and economic optimality based on constraints expressed in terms of a function called Safeness-Index [2] which characterizes the relative safeness of different points in the state-space. At this point, the approach in [2] can handle sufficiently-small disturbances but its applicability to nonlinear chemical processes with stochastically-modeled disturbances of unbounded variation remains an open issue.

Motivated by this, in this work, we develop a process Safeness Index-based economic model predictive control method 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 [3]. 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.

[1] Sanders R E. Chemical process safety: learning from case histories. Butterworth-Heinemann, 2015.

[2] Albalawi F, Durand H, Christofides P D. Process operational safety using model predictive control based on a process Safeness Index. Computers & Chemical Engineering, 2017, 104: 76-88.

[3] Wu Z, Zhang J, Zhang Z, et al. Economic Model Predictive Control of Stochastic Nonlinear Systems. AIChE Journal, 2018. In press