用于非线性动力系统控制问题的自组织神经网络自适应方法

本文提出一种用自组织自学习适应思想解决非线性动力系统控制问题的新方法。在每个小区域感受野，可以把非线性系统近似展开为线性，由神经元执行控制。各神经元的凝视点，感受野和功能由自组织自学习自适应方法进行调节。大量仿真结果验证了本方法的正确性和实用性。

Self-Organizing Neural Network Adaptive Method for Control Problems of Nonlinear Dynamic Systems

In this paper a new self-organizing, learning and adaptive method to solve the control problems of nonlinear dynamic systems is proposed. In each small regions (receptive fields), a nonlinear system can be expressed as a linear one and controlled by neurons. The gazing points, receptive fields and control functions of each neurons are regulated in self-organizing learning and adapting way. Several computer simulation examples verify the correctness and feasibility of this method.