Optimization of control system for Nitrifying Process in two nitro chlorobenzene production

The nitrifying process (NP) is an important step in two nitro chlorobenzene production. This paper presents an intelligent optimization control system (IOCS) to implement the modeling, optimization, and control of the NP by improved back-propagation neural networks, c-means clustering, genetic and chaos approaches. The results of actual runs demonstrate the validity of the system.