Safe Model Predictive Control Formulations Ensuring Process Operational Safety

Speaker: Fahad Albalawi
Affiliation: Ph.D. Candidate - UCLA

Abstract:  Model predictive control (MPC) is an advanced control strategy widely used in the process industries and beyond. Therefore, industry is interested in the developments of MPC formulations that can enhance safety, reliability, and economic profitability of chemical processes. Motivated by these considerations, the first part of this dissertation focuses on the development of methods for integrating process operational safety and process economics within model predictive control system designs. To accomplish these critical control objectives, various economic model predictive control (EMPC) schemes that maintain the process state within a safety region in state-space while optimizing process economics are considered for the first time. The safety region is initially assumed to be a level set of a Lyapunov function which is made forward invariant through appropriate MPC design. However, safety-based constraints may define a safety region that is irregularly shaped, and therefore, the safety region may not be taken to be a level set of a Lyapunov function in general.

Hence, the second part of this thesis proposes an economic model predictive control (EMPC) formulation that utilizes a Safeness Index function (a function that measures the safeness of points in state-space) as a hard constraint to define a safe region of operation termed the safety zone. Such a safety zone is not restricted to be a level set of a Lyapunov function and may be irregularly shaped.  While the two initial safe-EMPC formulations explicitly handle process safety and economics considerations, they are centralized in nature and may lead to control action calculations that exceed the allowable sampling period. To address this potential practical limitation of the centralized safety-based EMPC designs, the third part of this dissertation addresses the development of distributed economic model predictive control architectures with safety-based constraints. Both sequential and iterative distributed control architectures, and the partitioning of inputs between the various optimization problems in the distributed structure based on their impact on process operational safety, are investigated. Chemical process examples will be used throughout the talk to demonstrate the applicability and effectiveness of the proposed control methods.

Biography:  Fahad Albalawi was born in Jeddah, Saudi Arabia. He received the B.S. in Electrical Engineering from Umm Alqura University, Makkah.  He is currently a Ph.D. candidate in Electrical Engineering at the University of California, Los Angeles. His research interests include economic model predictive control, nonlinear systems, dynamic process optimization and process operational safety. Upon graduation, he will join Taif University, Saudi Arabia, as Assistant Professor of Electrical Engineering.

Hosted by Prof. Panagiotis D. Christofides, UCLA Department of Electrical Engineering

Date(s) - May 15, 2017
2:00 pm - 4:00 pm

5513 Boelter Hall
580 Portola Plaza, Los Angeles CA 90095