本文对具有不确定控制对象提出了一种基于再励学习的神经网络模糊控制器.文中给出了这种自学习控制器的结构,并对算法进行了详细的讨论.仿真结果表明文中提出的控制方法对非线性、不确定控制对象不仅可以进行有效的控制,而且具有良好的鲁棒性. In this paper, a neural network fuzzy controller based on re-energization learning is proposed for uncertain control objects. The structure of this self-learning controller is given and the algorithm is discussed in detail. The simulation results show that the proposed controller The control method not only can effectively control nonlinear and uncertain control objects, but also has good robustness.