Temperature modeling and control of DMFC based on FGA-ANFIS technology
基于一种FGA–ANFIS技术的DMFC温度建模和控制

To improve the performance of a direct methanol fuel cell(DMFC),the adaptive neural fuzzy inference (FGA-ANFIS)technology is applied to the modeling and control of a DMFC temperature system.First,an adaptive neural fuzzy inference system(ANFIS)identification model of DMFC stack temperature is developed based on the input-output sampled data,getting around the internal complexity of DMFC stack.Then,taking the well-trained network model as the reference model of the control system of DMFC stack,we use a novel fuzzy genetic algorithm(FGA)for adaptively adjusting the parameters and fuzzy rules of a neural fuzzy controller.Simulation results demonstrate better performance of his neural fuzzy controller in comparison with those of the nonlinear PID and traditional fuzzy algorithm.