Fuzzy Neural Networks Adaptive Control of Micro Gas Turbine with Prediction Model

This paper proposes a control method for nonlinear models realized in the form of implicit rule-based fuzzy neural networks (FNN). The design of the model dwells on fuzzy sets and neural networks. The rotation speed control scheme of a single shaft gas turbine used in power generation is discussed. A fuzzy neural controller based on the prediction model is designed and the simulation is conducted by Matlab/Simulink. It is shown that by tuning the fuzzy neural network controller (FNNC), the performance of the system can be achieved in a wide range of operating conditions compared to the fuzzy logic controller and fuzzy PID controller (F-PID). It indicates that the controller has satisfactory adaptive ability and robustness. The controller improves the control effectiveness of gas turbine system