Developing optimal regulation and monitoring strategies to control a continuous petrochemical process

The purpose of this paper is to discuss the development of optimal strategies for regulating and monitoring a continuous petrochemical process using the Algorithmic Statistical Process Control (ASPC) methodology. The Single-Input/Single-Output (SISO) case is discussed, using the polymer viscosity as controlled variable (output), and reactor temperature as manipulated variable (input). Alternative regulation strategies are considered. Robustness properties and stability conditions of the controllers are discussed. The performance and the adequacy of the regulation schemes in a simulation of realistic assignable causes affecting the process are studied. In this context the benefits of implementing an integrated EPC/SPC system (ASPC system) are compared with those of using an EPC system alone.