中文摘要：

这份报纸与多重未知州的变化时间的延期为不明确的纯反馈的非线性的系统的一个类处理适应神经控制的问题并且未知死了地区。基于 Razumikhin 功能的方法， backstepping 技术和神经网络 parameterization 的新奇联合，一个适应神经控制计划为如此的系统被开发。所有靠近环的信号被显示出到最终一致地 semiglobally 被围住，并且追踪的错误留在起源的一位小邻居。最后，一个模拟例子被给表明建议控制计划的有效性。

英文摘要：

This paper addresses the problem of adaptive neural control for a class of uncertain pure-feedback nonlinear systems with multiple unknown state time-varying delays and unknown dead-zone. Based on a novel combination of the Razumikhin functional method, the backstepping technique and the neural network parameterization, an adaptive neural control scheme is developed for such systems. All closed-loop signals are shown to be semiglobally uniformly ultimately bounded, and the tracking error remains in a small neighborhood of the origin. Finally, a simulation example is given to demonstrate the effectiveness of the proposed control schemes.