Online model based optimization and control of a reactor system with heterogeneous catalyst

Global competition will require the next generation of manufacturing plants to meet tough capital and operating cost constraints. Industry must rely increasingly on fundamental models to interpret and direct plant operation. New statistical and control algorithms will guide data conditioning and control action to optimize plant operation. A synergistic combination of control and expert system techniques will not only manage the process but also learn online. They will actively interact with the minimal number of plant personnel to avoid upsets and maintain optimal plant operation. Automation and wide scale optimization will prevail. A typical chemical reactor system is shown