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Safe Model Predictive Control Formulations Ensuring Process Operational Safety

  • Author(s): Albalawi, Fahad Ali
  • Advisor(s): Christofides, Panagiotis D
  • et al.
Abstract

Model predictive control (MPC) is an advanced control strategy widely used in the process industries and beyond. Therefore, industry is interested in the development of MPC formulations that can enhance safety, reliability, and economic profitability of chemical processes. Motivated by these considerations, 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 assumed in the first part of the dissertation 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 safety-based EMPC formulations explicitly handle process safety and economic 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 EMPC 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 thesis to demonstrate the applicability and effectiveness of the proposed control methods.

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