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论文类型：期刊论文

发表时间：2006-01-01

发表刊物：3rd International Symposium on Neural Networks (ISNN 2006)

收录刊物：SCIE、EI、CPCI-S

卷号：3972

页面范围：836-841

ISSN号：0302-9743

摘要：A stable adaptive neural network control approach is proposed in this paper for uncertain nonlinear strict-feedback systems based on backstepping. The key assumptions are that the neural network approximation errors satisfy certain bounding conditions. By a special scheme, the controller singularity problem is avoided perfectly. The proposed scheme improves the control performance of systems and extends the application scope of nonlinear systems. The overall neural network control systems guarantee that all the signals of the systems are uniformly ultimately bounded and the tracking error converges to a small neighborhood of zero by suitably choosing the design parameter.