Temperature control with a neural fuzzy inference network

We propose a neural fuzzy inference network (NFIN) suitable for adaptive temperature control of a water bath system. The rules in the NFIN are created and adapted as online learning proceeds via simultaneous structure and parameter identification. The NFIN has been applied to a practical water bath temperature control system. The performance of the NFIN is compared to that of the PID controller and fuzzy logic controller (FLC) on the water bath temperature control system. The three control schemes are compared through experimental studies. It is found that the proposed NFIN control scheme has the best control performance among the three control schemes.