Adaptive sliding mode observer for non-linear stochastic systems with uncertainties
Adaptive sliding mode observer for non-linear stochastic systems with uncertainties
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DOI：
10.1504/ijmic.2009.028870
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发表时间：
2009-10
期刊：
影响因子：
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通讯作者：
F. Qiao;Ya Zhang;Q. Zhu;Hua Zhang
中科院分区：
文献类型：
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作者：
F. Qiao;Ya Zhang;Q. Zhu;Hua Zhang
本文提出了一种新的自适应滑模观测器（ASMO），用于重构具有结构不确定性、参数摄动和外部扰动的非线性随机系统的状态。该方法采用滑模技术来保证观测的鲁棒性，并采用自适应律来更新滑模增益。从理论上证明了所提观测器的估计误差是均方指数收敛于有限界的。利用MatLab在计算机上对受不确定性干扰和噪声污染的洛伦兹混沌吸引子进行了状态重建仿真研究，仿真结果验证了所提出的观测策略的有效性。
It is presented, in this paper, a novel adaptive sliding mode observer (ASMO) for reconstructing the states of non-linear stochastic systems with structure uncertainties, parameter perturbations and external disturbances which is presented in the Ito differential equations. The proposed ASMO uses sliding mode technique to guarantee the robustness of observation, and an adaptive law is employed to update the sliding mode gain. The estimation error of the proposed observer is theoretically proved to be mean square exponentially convergent to a limited bound. Simulation study is made on computer with MatLab for reconstructing the states of Lorenz chaotic attractor disturbed with uncertainties and polluted with noises, and the simulation results verify the effectiveness of the proposed observation strategy.