摘要
本文提出了以神经网络为模型的一类离散非线性系统的有效可行的自适应控制算法。该控制算法不仅能解决此类非线性系统的跟踪控制问题,而且降低了通常的以神经网络为模型的自适应控制算法的模型构造的复杂性。
For a class of discrete-time nonlinear systems, an adaptive control scheme using multi-layered neural networks is presented. It can not only solve the tracking problem but also simplify the neural networks model. It is also shown that the closed-loop system is uniformly ultimately bounded and the parameters of the neural networks are convergent.
出处
《模式识别与人工智能》
EI
CSCD
北大核心
1998年第3期335-340,共6页
Pattern Recognition and Artificial Intelligence
关键词
神经网络
非线性系统
自适应控制
Neural Networks, Nonlinear System, Adaptive Control
