Adaptive Particle Swarm-Based Fuzzy Clustering Algorithm in the Application of Steam Drum Pulverized Coal Fired Boiler

The Pulverized Coal Fired Boiler is a control object with time-varying parameters, large delay and multivariate tight-coupling. This paper, aiming at improving the actualities of excessive parameters and suboptimal data clustering effect in the Steam Drum Pulverized Coal Boiler running, proposes a new algorithm Fuzzy Clustering Algorithm (APFM) to fulfill the efficiency optimization of the boiler combustion. Based on the Adaptive Particle Swarm Optimization Algorithm (APSO), this new algorithm overcomes the disadvantages of FCM algorithm such as the sensitivity to initial value and the easy involvement in partial optimum, and enhances the abilities of APSO algorithm such as global search and escape from partial optimum. Finally, the feasibility and effectiveness of this clustering method is demonstrated through the simulation experiment.