Neuro-Predictive Control of an Infrared Dryer with a Feedforward-Feedback Approach Academic Article uri icon


  • © 2014 Chinese Automatic Control Society and Wiley Publishing Asia Pty Ltd. In this research, a hybrid control system is proposed to address the temperature control of an infrared dryer. The control system includes a feedback-predictive controller and a neural network steady state control law. The feedback-predictive controller outputs the amplified value of the predicted error as the transient control command. The predictive model was employed to suppress the undesirable effect of the dead-time of the system. A multilayer perceptron was designed and tested based on a control equilibrium point and steady state control to be used as a feedforward controller. The stability of the control system in a continuous domain was proved with no limit on the amplification gain of the predictive-feedback controller. In other words, there is no concern about losing stability with accelerating convergence towards the reference. The entire control system was constructed in Simulink and compiled to a C code and applied on the experimental setup. Experimental results are outstanding in comparison with the results of an interactively tuned IMC-based PID controller.

author list (cited authors)

  • Mohammadzaheri, M., Chen, L., Mirsepahi, A., Ghanbari, M., & Tafreshi, R.

publication date

  • January 1, 2015 11:11 AM