|
基于驻留时间的切换复杂网络的降阶估计
|
Abstract:
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。
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.
[1] | Boccaletti, S., Latora, V., Moreno, Y., Chavez, M. and Hwang, D. (2006) Complex Networks: Structure and Dynamics. Physics Reports—Review Section of Physics Litters, 424, 175-308. https://doi.org/10.1016/j.physrep.2005.10.009 |
[2] | Chen, D., Yang, N., Hu, J. and Du, J. (2019) Resilient Set-Membership State Estimation for Uncertain Complex Networks with Sensor Saturation under Round-Robin Protocol. International Journal of Control Automation and Systems, 17, 3035-3046. https://doi.org/10.1007/s12555-018-0780-8 |
[3] | Chen, Y., Wang, Z., Wang, L. and Sheng, W. (2020) Mixed/State Estimation for Discrete-Time Switched Complex Networks with Random Coupling Strengths through Redundant Chan-nels. IEEE Transactions on Neural Networks and Learning Systems, 31, 4130-4142. https://doi.org/10.1109/TNNLS.2019.2952249 |
[4] | Shen, B., Wang, Z., Wang, D. and Li, Q. (2020) State-Saturated Recursive Filter Design for Stochastic Time-Varying Nonlinear Complex Networks Under-Deception Attacks. IEEE Transactions on Neural Networks and Learning Systems, 31, 3788-3800. https://doi.org/10.1109/TNNLS.2019.2946290 |
[5] | Peng, S. (1999) Robust Kalman Filtering for Continuous-Time Systems with Discrete-Time Measurements. IMA Journal of Mathematical Control and Information, 16, 221-232. https://doi.org/10.1093/imamci/16.3.221 |
[6] | Geromel, J. and Oliveira, M. (2001) H2 and H∞ Robust Filtering for Convex Bounded Uncertain Systems. IEEE Transactions on Automatic Control, 46, 100-107. https://doi.org/10.1109/9.898699 |
[7] | Liu, Y., Shen, B. and Shu, H. (2020) Finite-Time Resilient State Estimation for Discrete-Time Delayed Neural Networks under Dynamic Event-Triggered Mechanism. IEEE Transactions on Neural Networks, 121, 356-365.
https://doi.org/10.1016/j.neunet.2019.09.006 |
[8] | Yang, F., Han, Q. and Liu, Y. (2019) Distributed State Estima-tion over a Filtering Network with Time-Varying and Switching Topology and Partial Information Exchange. IEEE Transactions on Systems Man Cybernetics-Systems, 49, 870-882. https://doi.org/10.1109/TCYB.2017.2789212 |
[9] | He, S. and Liu, F. (2010) Robust Peak-to-Peak Filtering for Markov Jump Systems. Signal Processing, 90, 513-522.
https://doi.org/10.1016/j.sigpro.2009.07.018 |
[10] | 乔伟豪, 朱凤增, 彭力. 基于自适应事件触发的时滞系统分布式——滤波[J]. 控制与决策, 2022, 37(4): 1074- 1080. |
[11] | Li, Z., Chang, X., Mathiyalagan, K. and Xiong, J. (2017) Robust Energy-to-Peak Filtering for Discrete-Time Nonlinear Systems with Measurement Quantization. Signal Processing, 13, 102-109. https://doi.org/10.1016/j.sigpro.2017.03.029 |
[12] | Zhu, F., Liu, X., Wen, J., Xie, L., and Peng, L. (2020) Distributed Robust Filtering for Wireless Sensor Networks with Markov Switching Topologies and De-ception Attacks. Sensors, 20, 1984. https://doi.org/10.3390/s20071948 |
[13] | Boutayeb, M. and Darouach, M. (2000) A Reduced-Order Observer for Non-Linear Discrete-Time Systems. Systems & Control Letters, 39, 141-151. https://doi.org/10.1016/S0167-6911(99)00102-4 |
[14] | Su, X., Wen, Y., Shi, P. and Lam, H.K. (2019) Event-Triggered Fuzzy Filtering for Nonlinear Dynamic Systems via Reduced-Order Approach. IEEE Transactions on Fuzzy Systems, 27, 1215-1225.
https://doi.org/10.1109/TFUZZ.2018.2874015 |
[15] | Liu, Y. and Arumugam, A. (2020) Event-Triggered Non-Fragile Finite-Time Guar-Anteed Cost Control for Uncertain Switched Nonlinear Networked Systems. Nonlinear Analysis: Hybrid Systems, 36, Article ID: 100884.
https://doi.org/10.1016/j.nahs.2020.100884 |
[16] | Zhang, D., Yu, L., Song, H. and Wang, Q. (2013) Distributed Filtering for Sensor Networks with Switching Topology. International Journal of Systems Science, 44, 2104-2118. https://doi.org/10.1080/00207721.2012.684903 |
[17] | Wang, L. and Wang, Q. (2011) Synchronization in Complex Networks with Switching Topology. Physics Letters A, 375, 3070-3074. https://doi.org/10.1016/j.physleta.2011.06.054 |
[18] | Chi, Z. (2011) Design of Dimension Reduction Observer for Nonlinear Systems. Harbin Normal University, Harbin. |