ARTIFICIAL NEURAL NETWORKS - PRINCIPLE AND APPLICATION TO MODEL-BASEDCONTROL OF DRYING SYSTEMS - A REVIEW

This paper reviews the developments in the model based control of dryi ng systems using Artificial Neural Networks (ANNs). Survey of current research works reveals the growing interest in the application of ANN in modeling and control of non-linear, dynamic and time-variant system s. Over 115 articles published in this area are reviewed. All landmark papers are systematically classified in chronological order, in three distinct categories; namely, conventional feedback controllers, model based controllers using conventional methods and model based controll ers using ANN for drying process. The principles of ANN are presented in detail. The problems and issues of the drying system and the featur es of various ANN models are dealt with upto-date. ANN based controlle rs lead to smoother controller outputs, which would increase actuator life. The paper concludes with suggestions for improving the existing modeling techniques as applied to predicting the performance character istics of dryers. The hybridization techniques, namely, neural with fu zzy logic and genetic algorithms, presented, provide, directions for p ursuing further research for the implementation of appropriate control strategies. The authors opine that the information presented here wou ld be highly beneficial for pursuing research in modeling and control of drying process using ANN.