CMAC neural network and single neuron PID composite control in the application of temperature control

Abstract

The principle of CMAC (Cerebella Model Articulation Controller) and single neuron PID are studied in this article. The CMAC neural network and single neuron pm composite control algorithm is proposed which is applied in the temperature control. The simulation of each controller is tracked. Its anti-interference ability has also been studied and a further study has been proposed by changing the parameters. Simulation results show that the composite control has better results and a certain anti-interference ability. This fully reflects the advantages of the neural network CMAC and single neuron PID composite control that the output error is small, real-time and strong robust.