A Hybrid Controller of Self-Optimizing Algorithm and ANFIS for Ball Mill Pulverizing System

For ball mill pulverizing system of the thermal power plant, a hybrid controller of self-optimizing algorithm and adaptive neuro-fuzzy inference system(ANFIS) is proposed. In order to keep the ball mill pulverizing system working at the optimum point all along, the self-optimizing algorithm is presented. The self-optimization algorithm can automatically find out the extreme point and adjust the control set values in time. The adaptive neuro-fuzzy inference system, which integrates the advantages of the neural network and the fuzzy control, uses the learning ability of the neural network to optimize the membership functions and fuzzy logic rules of fuzzy control. Such combined framework makes fuzzy control more systematic and less relying on expert knowledge. Simulations results verify that the controller can control the ball mill pulverizing system effectively and has higher control quality.