Application Of Fuzzy Neural Network In Coordinated Control System

The coordinated control system is the core of the power plant unit and plays an important role in the safe and efficient operation of the power plant.However,with the expansion of the power grid capacity and the rapid development of new energy sources,the power grid's ability to regulate peaks and pressures of large power generating units and The more and more stringent requirements of power grid load command response make it difficult to achieve satisfactory control requirements for conventional PID control.Therefore,the optimization study of the coordinated control system has certain practical significance for improving the economic efficiency of the power plant.Unit coordinated control system is a multi-variable,strongly coupled nonlinear system.This paper studies three-input three-output control system.The traditional PID control has many problems and cannot meet people's control requirements.This paper analyzes the advantages and disadvantages of fuzzy control and neural network control and analyzes the dynamic characteristics of the coordinated control object,and proposes that the fuzzy neural network control is applied to the unit control system.It mainly completes four aspects of research work:1.Set up a unit-unit nonlinear dynamic model.Combining with the actual situation in the field,the model is simplified and the mechanism analysis is carried out to obtain a unit model nonlinear model.Then use the data identification and parameter estimation to obtain the unit parameters of the unit and verify the correctness of the model.The simulation results show the reliability of the model.2.Establish a coordinated control simulation system.According to the on-site SAMA diagram,a simulation model of the coordinated control system was established and a simulation loop was formed with the unit model to prepare for the optimization of the coordinated control.3,Fuzzy control and neural network theory research,application of fuzzy neural network intelligent algorithm design RBF fuzzy neural network self-adjusting parameter controller,the controller combines the advantages of fuzzy control system and neural network control.4.The fuzzy neural network controller is applied to the coordinated control system,through simulation experiments,and compared with the traditional PID control widely used in engineering,and also compared with the adaptive fuzzy neural network(ANFIS)control.The results show that: The RBF fuzzy neural network control method in this paper hassignificantly improved the quality of the coordinated control.The optimized coordinated control system has a good level of control,good load response,low main steam pressure and main steam temperature fluctuations.The system modeling and control optimization methods proposed in this paper not only have theoretical research value,but also have engineering application significance,and have played a reference role in the modeling and optimization work of the power plant coordinated control system.