A Process Control Design Case Stud 16.422 Model-Based Predictive Control (MPC)of a refinery plant Multi-input multi-output automatic controllers Optimize the process based on maximizing production and minimizing utility cost Higher levels of automation-human less in the loop · Three variable types CVs-Controlled Variables-process variables to be kept at setpoints or within constraints(20-30 variables) MVs- Manipulated Variables- Variables(typically valves )that are adjusted to achieve CVs while optimizing(6-8 variables) DVs- Disturbance variables- Variables that can measured but not controlled, e.g., ambient air temp. (2-3 variables Humans have difficulty monitoring, diagnosing, controlling these advanced systems16.422 A Process Control Design Case Study • Model-Based Predictive Control (MPC) of a refinery plant • Multi-input & multi-output automatic controllers – Optimize the process based on maximizing production and minimizing utility cost. – Higher levels of automation – human less in the loop • Three variable types – CVs - Controlled Variables – process variables to be kept at setpoints or within constraints (20-30 variables). – MVs - Manipulated Variables – Variables (typically valves) that are adjusted to achieve CVs while optimizing (6-8 variables). – DVs - Disturbance Variables - Variables that can measured but not controlled, e.g., ambient air temp. (2-3 variables) • Humans have difficulty monitoring, diagnosing, controlling these advanced systems