Research on the Intelligent Control Strategy Based on Improved FNNC for Hydraulic Turbine Generating Units

It is difficult to gain better control performance using general control strategy to control complicated non-linear hydraulic turbine generating units system. In the study, a new control technique, which efficiently get optimal control parameters for fuzzy neural network controller through the training of neural network and genetic algorithms, was proposed and then applied to control turbine generating unit system. In the designed control system, RBF neural network is employed to identify and predict the relation between input and output of hydroelectric generating units system and controller reasoning networks have been predigested. In training, fuzzy reasoning parameters can be given through genetic algorithms when error is bigger and can be trained on-line through neural network when error is less. The improved genetic algorithms have quick training speed and give whole optimized parameters for fuzzy neural network controller. Simulation experiment results show that the designed improved controller has better control effect in controlling hydraulic turbine generating units system.