Intelligent modeling and control of a conveyor belt grain dryer using a simplified type 2 neuro-fuzzy controller

• Main Authors: Lutfy, Omar F., Selamat, Hazlina, Mohd. Noor, S. B.
• Format: Article
• Published: Taylor and Francis Inc. 2015
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/55995/; http://dx.doi.org/10.1080/07373937.2015.1021007

In this article, a nonlinear autoregressive with exogenous input (NARX) network was utilized to model a conveyor belt grain dryer using a set of input–output data collected during an experiment to dry paddy grains. The resulting NARX model has achieved a remarkable modeling accuracy compared to other previously reported modeling techniques. To control the considered dryer, a simplified type 2 adaptive neuro-fuzzy inference system (ANFIS) controller was proposed. The effectiveness of this controller was demonstrated by several performance tests conducted by computer simulations. Moreover, a comparative study with other related controllers further confirmed the superiority of the proposed dryer controller