Abstract
The main objective in operating a chemical plant is to improve profit while assuring products meet required specifications and plant operation satisfies environmental and operational constraints. A subobjective that directly affects profit is to improve the control performance of key economic variables in the plant, particularly the production rate and quality. An optimal control-based approach is proposed to determine a set of dominant measurements and manipulated variables and to structure them to improve control of the production rate and product quality. After the dominant variables are identified, a decentralized control structure is designed to control these variables. Then, a model predictive controller (MPC) is built on top of the decentralized control structure. The approach is applied to the Tennessee Eastman Process to demonstrate its effectiveness.
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