Abstract: By integrating the advantages of genetic algorithm (GA),neural network and fuzzy control,a fuzzy neural network controller based on improved GA is proposed for sintering process which is a highly nonlinear system with complexity and multiple parameters,and the controller is used to control the burning through point(BTP) in sintering process.Structural parameters of the fuzzy neural network are firstly optimized off-line by GA,and then are adjusted on-line by using the local searching and adaptabilities of BP algorithms.To solve the problems of premature and slow convergence in traditional GAs,the GA is improved from several aspects such as crossover and mutation operators and fitness function selection.Elitist strategy is used to improve the global searching efficiency and convergence rate.The simulation results show that response of the proposed controller is more effective than that of the traditional fuzzy neural network controllers(FNNCs).The algorithm obtains a better effect in practical system and provides a new approach for solving the burning through point control problem.