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