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中文摘要：
在这篇论文，适应可变结构神经控制为不明确的多输入多产量(MIMO ) 的一个班被介绍有州的变化时间的延期的非线性的系统并且未知非线性死了地区。未知变化时间的延期不确定性被补偿在设计使用适当 Lyapunov-Krasovskii functionals。没有必然作为增加的贡献构造死了地区的逆，途径在死了的乐队外面移开线性功能的假设。由利用不可分类型的 Lyapunov 函数并且为剩余和最佳的近似错误以及死了地区的骚乱的上面的界限介绍一个适应赔偿术语，靠近环的控制系统被证明到最终一致地半全球性被围住。另外，一个修改适应控制算法被给以便避免高周波的啁啾现象。模拟结果表明途径的有效性。
英文摘要：
In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output （MIMO） nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.
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