Neural Adaptive Sliding Mode Control for a Class of Nonlinear Neutral Delay Systems

Neural Adaptive Sliding Mode Control for a Class of Nonlinear Neutral Delay Systems
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一类非线性中性时滞系统的神经自适应滑模控制

DOI:
10.1115/1.2977462
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发表时间:
2008-11
影响因子:
1.7
通讯作者:
Ho, Daniel W. C.
Ho, Daniel W. C.
中科院分区:
计算机科学4区
文献类型:
--
作者:
Wang, Xingyu;Lam, James;Niu, Yugang;Ho, Daniel W. C.

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研究了一类具有未知非线性不确定性且可能不满足范数有界条件的中立型时滞系统的滑模控制问题。针对不确定中立型时滞系统,提出了一种基于神经网络逼近的滑模控制方案。利用线性矩阵不等式(LMI)方法,给出了闭环系统稳定且状态渐近收敛到零的充分条件。当LMI可行时,滑动面和滑模控制律的设计都可以通过凸优化得到。结果表明,状态轨迹被驱动到指定的滑动面,该滑动面取决于当前状态和延迟状态。最后给出了仿真结果,验证了该方法的有效性。
This paper is concerned with the problem of sliding mode control (SMC) for a class of neutral delay systems with unknown nonlinear uncertainties that may not satisfy the norm-bounded condition. A SMC scheme based on neural-network approximation is proposed for the uncertain neutral delay system. By means of linear matrix inequality (LMI) approach, a sufficient condition is given such that the resultant closed-loop system is guaranteed to be stable, and the states asymptotically converge to zero. When the LMI is feasible, the designs of both the sliding surface and the sliding mode control law can be easily obtained via convex optimization. It is shown that the state trajectories are driven toward the specified sliding surface that depends on the current states as well as the delayed states. Finally, a simulation result is given to illustrate the effectiveness of the proposed method.
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发表时间: 2002-08
期刊: IEEE Trans. Autom. Control.
影响因子: --
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