(681a) Safe Economic Model Predictive Control of Nonlinear Systems

Economic model predictive control (EMPC) is a feedback control method which allows addressing process control tasks integrated with dynamic economic optimization of the process [1]. EMPC may continuously operate a chemical process in a time-varying fashion (off steady-state) to dynamically optimize process economic performance beyond what can be achieved via steady-state operation, and it also incorporates constraints to guarantee closed-loop stability within a well-characterized region of the operating state-space. On the other hand, process operational safety is of significant importance in the chemical process industries because unsafe process operation often results in very negative consequences [2]. Recently, a feedback control approach attempting to address stabilization and operational safety via Control Lyapunov-Barrier Functions (CLBFs) [3] has been investigated in the sense that the closed-loop state converges to the steady-state from a well-characterized set of initial conditions while avoiding an unsafe region the in state-space [4]. However, economic optimality is not addressed within this approach.

Motivated by the above, this work focuses on the design of a new class of economic model predictive control (EMPC) systems for nonlinear systems that address simultaneously the tasks of economic optimality, safety and closed-loop stability. Specifically, the EMPC is developed by incorporating an economics-based cost function and Control Lyapunov-Barrier Function (CLBF)-based constraints that ensure that the closed-loop state does not enter unsafe sets and remains within a well-characterized set in the system state-space while optimizing process economics. The new class of CLBF-EMPC systems is demonstrated using a nonlinear chemical process example.

[1] Ellis M, Durand H, Christofides P D. A tutorial review of economic model predictive control methods. Journal of Process Control. 2014, 24:1156-1178.

[2] Leveson NG, Stephanopoulos G. A system-theoretic, control-inspired view and approach to process safety. AIChE Journal. 2014, 60:2-14.

[3] Romdlony M Z, Jayawardhana B. Stabilization with guaranteed safety using control Lyapunov–barrier function. Automatica, 2016, 66: 39-47.

[4] Wu Z, Albalawi F, Zhang Z, Zhang J, Durand H, and Christofides P D. Control Lyapunov-Barrier Function-Based Model Predictive Control of Nonlinear Systems. Proceedings of the American Control Conference, 2018, in press, Milwaukee, Wisconsin.