An operator's model for control and optimization of industrial processes

An operator's model is developed based on a polynomial fuzzy neural network architecture for control and optimization of industrial processes. Industrial processes possess complex dynamics which are accentuated under abnormal operating conditions. The operator plays a vital role in bringing the plant states back to a normal mode. In a typical industrial enterprise, knowledge of a specific process lies at three levels; skilled operator, process engineer, and design engineer. The model presented captures the operator's and engineer's corrective actions which are based on their experience and their knowledge of the system's behavioral patterns. The model is tested on a pH neutralization process and simulation results are presented.