基于驻留时间的切换复杂网络的降阶估计
Reduced Order Estimation of Switching Complex Networks Based on Dwell Time
摘要: 研究一类离散时滞非线性切换复杂网络的降阶l2-l∞状态估计问题。通过引入辅助变量，提出了一种新的模型化简方法，该方法用测量输出表示直接观测状态，通过设计降阶估计器估计不可测状态。利用平均驻留时间法和李雅普诺夫稳定性理论，给出了一个既保证估计误差系统指数稳定性又保证估计误差对外生干扰的l2-l∞性能水平的充分条件。降阶估计器增益通过求解一组线性矩阵不等式得到。最后，通过数值仿真验证了理论结果的有效性，并通过对比实验验证了所设计估计器的阶数对估计精度的影响。
Abstract: In this paper, the l2-l∞ reduced-order state estimation problem is investigated for a class of dis-crete time-delayed nonlinear switched complex networks. By introducing an auxiliary variable, a new model reduction method is proposed where the directly observed state can be represented by the measurement output and the unmeasured state is estimated by designing a reduced-order es-timator. With the help of the average dwell time method and the Lyapunov stability theory, a suffi-cient condition is presented to guarantee both the exponential stability of the resulting estimation error system and a prescribed l2-l∞ performance level of the estimation error against exogenous disturbances. The desired reduced-order estimator gains are acquired in terms of the solution to a set of linear matrix inequalities. Finally, a numerical simulation is given to illustrate the usefulness of the proposed theoretical results and some comparative experiments are made to show the im-pact of the order of the designed estimator on the estimation accuracy.
文章引用：张亚平, 张梦瑶. 基于驻留时间的切换复杂网络的降阶估计[J]. 应用数学进展, 2022, 11(12): 8522-8539. https://doi.org/10.12677/AAM.2022.1112900

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