Breadcrumb
- Home
- Publications
- Proceedings
- 2014 AIChE Annual Meeting
- Computing and Systems Technology Division
- Economics and Process Control
- (721g) Safe Economic Model Predictive Control
To integrate EMPC with safety considerations (i.e., handle safety through feedback control), a novel control and monitoring methodology is proposed. First, the safeness of a region of operation with respect to a possible failure (i.e., determine if stability of the process can be maintained for any point in the region of operation if a failure occurs) is characterized. Second, a statistical analysis is used to evaluate the probability of a possible failure. To this end, it is important to point out that it might be best with respect to the process economics to operate a process in specific region of operation. However, this region of operation must also be acceptable with respect to the process safety. Even if it is safe to operate in this region, the reliability of process components decreases and the probability of failure increases with time in general [6], and the safeness of this region of operation may decrease with time. Thus, the probability of a potential failure is computed with time. If the probability of a failure exceeds a threshold and the process cannot be safely operated in the region of operation if a failure occurs, the region of operation is shifted to a safer region of operation regardless of the fact that the process economics performance may decrease in this region of operation. To transition between regions of operation, appropriate constraints are added to the EMPC optimization problem. Through a rigorous stability analysis, recursive feasibility and closed-loop stability are analyzed. The proposed control and monitoring technique, which effectively integrates process control, process economics, and safety considerations, is demonstrated with a chemical process example.
[1] Leveson NG, Stephanopoulos G. A system-theoretic, control-inspired view and approach to process safety. AIChE Journal. 2013;60:2-14.
[2] Angeli D, Amrit R, Rawlings JB. On average performance and stability of economic model predictive control. IEEE Transactions on Automatic Control. 2012;57:1615-1626.
[3] Huang R, Harinath E, Biegler LT. Lyapunov stability of economically oriented NMPC for cyclic processes. Journal of Process Control. 2011;21:501-509.
[4] Heidarinejad M, Liu J, Christofides PD. Economic model predictive control of nonlinear process systems using Lyapunov techniques. AIChE Journal. 2012;58:855-870.
[5] Lao L, Ellis M, Christofides PD. Smart Manufacturing: Handling preventive actuator maintenance and economics using model predictive control. AIChE Journal. 2014;60:2179-2196.
[6] Barlow RE, Proschan F. Mathematical Theory of Reliability. Philadelphia, PI: Society for Industrial and Applied Mathematics, 1996.