Distributed moving horizon estimation under constraints of quantized measurements and packet dropouts
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摘要:
针对网络约束问题,对带丢包和量化的网络化系统分布式状态估计进行了研究。用一组满足Bernouli分布的随机变量来描述丢包现象,采用预测补偿机制进行丢包补偿。将数据量化引入的误差描述为观测方程中的参数不确定性,通过求解固定时域内的min-max问题,得到局部估计器。对局部估计器的稳定性进行研究,给出了误差范数平方的期望收敛的充分条件。推导了局部估计器误差协方差上界的递推公式,在此基础上,应用协方差交叉(CI)融合算法得到了分布式融合估计器。仿真结果表明,所提算法能够有效减小数据丢包和量化对状态估计的影响。
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关键词:
- 分布式滚动时域估计 /
- 预测补偿 /
- 数据量化 /
- 稳定性分析 /
- 协方差交叉(CI)融合
Abstract:Aimed at the problem of network constraint, distributed state estimation for networked systems with packet dropouts and quantized measurements is studied. A group of Bernoulli distributed random variables is employed to describe the phenomenon of packet dropouts, and a prediction compensation mechanism is applied to compensate the packet dropouts. Quantized errors introduced by data quantification are described as parameter uncertainty in the observation equation, and the local estimator is obtained by solving a min-max problem in fixed time domain. The stability of the local estimator is studied, and a sufficient condition for the convergence of the expectation of the square norm of estimation error is obtained. For each local estimator, the recursive formula of the upper bound of the error covariance is derived, based on which a distributed fusion estimator is presented by using the Covariance Intersection (CI) fusion algorithm. The simulation results show that the proposed algorithm can effectively reduce the influence of packet dropouts and quantization on state estimation.
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[1] ZHANG D, SHI P, WANG Q G, et al.Analysis and synthesis of networked control systems:A survey of recent advances and challenges[J].ISA Transactions, 2017, 66:376-392. https://www.sciencedirect.com/science/article/abs/pii/S0019057816304475 [2] LIANG X, XU J J.Control for networked control systems with remote and local controllers over unreliable communication channel[J].Automatica, 2018, 98:86-94. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=9a65e9e5001aab18f91f233f4b890963 [3] GAO C, ZHAO G R, LU J H, et al.Decentralized moving-horizon state estimation for a class of networked spatial-navigation systems with random parametric uncertainties and communication link failures[J].IET Control Theory and Applications, 2015, 9(18):2666-2677. [4] SUN S L, LIN H L, MA J, et al.Multi-sensor distributed fusion estimation with applications in networked systems:A review paper[J].Information Fusion, 2017, 38:122-134. https://www.sciencedirect.com/science/article/abs/pii/S1566253517300362 [5] HU J, WANG Z D, CHEN D Y, et al.Estimation, filtering and fusion for networked systems with network-induced phenomena:New progress and prospects[J].Information Fusion, 2016, 31:65-75. https://www.sciencedirect.com/science/article/abs/pii/S1566253516000087 [6] MONTESTRUQUE L A, ANTSAKLIS P J.Static and dynamic quantization in mode based networked control systems[J].International Journal of Control, 2007, 80(1):87-101. https://www3.nd.edu/~pantsakl/Publications/347-IJC07.pdf [7] SUN S L, XIE L H, XIAO W D, et al.Optimal linear estimation for systems with multiple packet dropouts[J].Automatica, 2008, 44(5):1333-1342. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=3b56ac1a5f3e04e26f9d813daee97c3a [8] SUN S L, TIAN T, LIN H L.Optimal linear estimators for systems with finite-step correlated noises and packet dropout compensations[J].IEEE Transactions on Signal Processing, 2016, 64(21):5672-5681. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=9ce6d462c72f2bff0d0620a822f89199 [9] DING J, SUN S L, MA J, et al.Fusion estimation for multi-sensor networked systems with packet loss compensation[J].Information Fusion, 2019, 45:138-149. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=7feed8b1fd22e98e6f5693537b18a1a9 [10] FU M Y, CARLOS E.State estimation for linear discrete-time systems using quantized measurements[J].Automatica, 2009, 45(12):2937-2945. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=420f7e442739aeeb808f21ed41b4c7f5 [11] CHE W W, WANG J L, YANG G H.Quantised H∞ filtering for networked systems with random sensor packet losses[J].IET Control Theory and Applications, 2010, 4(8):1339-1352. https://www.researchgate.net/publication/224164486_Quantized_H_filter_for_networked_systems_with_random_sensor_packet_losses [12] RAO C V, RAWLINGS J B, LEE J H.Constrained linear state estimation-a moving horizon approach[J].Automatica, 2001, 37(10):1619-1628. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=225d640285c275583d9decd66ec0bb29 [13] 赵海艳.时域约束系统的滚动时域估计方法研究[D].长春: 吉林大学, 2007. http://cdmd.cnki.com.cn/Article/CDMD-10183-2007095975.htmZHAO H Y.Study on moving horizon estimation for time-domain constrained system[D].Changchun: Jilin University, 2007(in Chinese). http://cdmd.cnki.com.cn/Article/CDMD-10183-2007095975.htm [14] LIU A D, YU L, ZHANG W A.Moving horizon estimation for networked systems with multiple packed dropouts[J].Journal of Process Control, 2012, 22(9):1593-1608. https://www.researchgate.net/publication/270753908_Moving_horizon_estimation_for_networked_systems_with_packet_dropouts [15] FARINA M, TRECATE G F, SCATTOLINI R.Distributed moving horizon estimation for linear constrained systems[J].IEEE Transactions on Automatic Control, 2010, 55(11):2462-2475. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=0b7c21a9987f275519457b9098b751cd [16] 谢澜涛, 谢磊, 苏宏业.不确定系统的鲁棒与随机模型预测控制算法比较研究[J].自动化学报, 2017, 43(6):969-992. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zdhxb201706009XIE L T, XIE L, SU H Y.A comparative study on algorithms of robust and stochastic MPC for uncertain systems[J].Acta Automatica Sinica, 2017, 43(6):969-992(in Chinese). http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=zdhxb201706009 [17] ALESSANDRI A, BAGLIETTO M, BATTISTELLI G.Min-max moving-horizon estimation for uncertain discrete-time linear systems[J].SIAM Journal on Control and Optimization, 2012, 50(3):1439-1465. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=4bc75e020e118203af7a5b050bd37ec4 [18] DENG Z L, ZHANG P, QI W J, et al.Sequential covariance intersection fusion Kalman filter[J].Information Sciences, 2012, 189:293-309. doi: 10.1016/j.ins.2011.11.038 [19] FU M Y, XIE L H.The sector bound approach to quantized feedback control[J].IEEE Transactions on Automatic Control, 2005, 50(11):1698-1711. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=5f637d9ccbdf0d44e7930414be8dabbb [20] SAYED A H, NASCIMENTO V H, CIPPARRONE F A M.A regularized robust design criterion for uncertain data[J].SIAM Journal on Matrix Analysis and Applications, 2002, 23(4):1120-1142. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=bd53a96baf2f2b75d2834f07c230fc4d [21] SAYED A H.A framework for state-space estimation with uncertain models[J].IEEE Transactions on Automatic Control, 2001, 46(7):998-1013. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=29a323a034489e42723ec04c19ef2cea [22] LIU A D, YU L, ZHANG W A.Moving horizon estimation for networked systems with quantized measurements and packet dropouts[J].IEEE Transactions on Circuits and Systems I:Regular Papers, 2013, 60(7):1823-1834. http://www.wanfangdata.com.cn/details/detail.do?_type=perio&id=73dec909294a768723bbdc4215729977