model-free adaptive heating process control

The aim of this paper is to analyze the dynamic behaviour of a Model-Free Adaptive (MFA) heating process control. The MFA controller is designed as three layer neural network with proportional element. The method of backward propagation of errors was used for neural network training. Visualization and training of the artificial neural network was executed by Netlab in Matlab environment. Simulation of the MFA heating process control with outdoor temperature compensation has proved better results than classic PID control. MFA controller can ensure zero control deviation between desired and actual variable of indoor temperature more quickly than PID controller.