In order to overcome the difficulties of temperature controlling, model establishment and poor universality, a decomposing furnace temperature control method is proposed using fuzzy rules extraction based on fuzzy C clustering with belief and improved Wang-Mendel(BFCM-iWM). More specifically, fuzzy C clustering with belief(BFCM) is adopted to extract the sample belief from the running data of decomposing furnace. Then based on this, improved Wang-Mendel(iWM) is utilized to extract fuzzy control rules to reduce the influence of noise and bad point data on rule extraction. The controller, which takes the temperature deviation and deviation change rate as the input quantity and takes the coal feeding increment as the output quantity, is constructed to achieve the temperature control. The simulation results show that the proposed method performs better in robustness, accuracy and temperature controlling.