【摘要】 提出了一种基于遗传算法的神经网络自适应控制方法．该方法是针对ＢＰ算法训练神经网络控制系统时收敛速度慢、动态特性不够理想等不足，用改进的遗传算法来优化神经网络辨识器与控制器的参数，以提高控制系统的性能．仿真实验表明该控制器对于非线性、时变、滞后等对象都具有很好的控制精度、鲁棒性和动态特性更多还原

【Abstract】 This paper presents a kind of adaptive neural network(NN) control method based on genetic algorithms(GA). In order to overcome the defects such as slow convergent speed and unsatisfied dynamic character when backpropagation(BP) is used to train the NN control system, the method using a modified GA to train parameters of NN is proposed to improve the performance of the control system. Simulation shows that the controller has fine accuracy, robustness and dynamic character when it is used to control nonlinear, time variable and time delayed systems.更多还原