Soft Computing Techniques for Process Control Applications

Technological innovations in soft computing techniques have brought automation capabilities to new levelsof applications. Process control is an important application of any industry for controlling the complexsystem parameters, which can greatly benefit from such advancements. Conventional control theory isbased on mathematical models that describe the dynamic behaviour of process control systems. Due to lackin comprehensibility, conventional controllers are often inferior to the intelligent controllers. Softcomputing techniques provide an ability to make decisions and learning from the reliable data or expert’sexperience. Moreover, soft computing techniques can cope up with a variety of environmental and stabilityrelated uncertainties. This paper explores the different areas of soft computing techniques viz. Fuzzy logic,genetic algorithms and hybridization of two and abridged the results of different process control casestudies. It is inferred from the results that the soft computing controllers provide better control on errorsthan conventional controllers. Further, hybrid fuzzy genetic algorithm controllers have successfullyoptimized the errors than standalone soft computing and conventional techniques.