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SELF-TUNING MEASUREMENT FUSION KALMAN FILTER WITH CORRELATED MEASUREMENT NOISES

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Journal of Electronics(China) 2009年第5期26卷 614-622页

作者： Gao Yuan ran chenjian deng zili Department of Automation Heilongjiang University Harbin 150080 China

For the multisensor system with correlated measurement noises and unknown noise statistics, based on the solution of the matrix equations for correlation function, the on-line estimators of the noise variances and cross-covariances is obtained. Further, a self-tuning weighted measurement fusion Kalman filter is presented, based on the Riccati equation. By the Dynamic Error System Analysis (DESA) method, it rigorously proved that the presented self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion steady-state Kalman filter in a realization or with probability one, so that it has asymptotic global optimality. A simulation example for a target tracking system with 3-sensor shows that the presented self-tuning measurement fusion Kalman fuser converges to the optimal steady-state measurement fusion Kalman fuser.

关键词： Correlation function method Multisensor measurement fusion Self-tuning Kalman filter Convergence in a realization

Self-tuning weighted measurement fusion Kalman filter and its convergence

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控制理论与应用（英文版） 2010年第4期8卷 435-440页

作者： chenjian ran,zili deng (Department of Automation,Heilongjiang University,Harbin Heilongjiang 150080,China) Department of Automation Heilongjiang University Harbin Heilongjiang China

For multisensor systems,when the model parameters and the noise variances are unknown,the consistent fused estimators of the model parameters and noise variances are obtained,based on the system identification algorithm,correlation method and least squares fusion *** these consistent estimators into the optimal weighted measurement fusion Kalman filter,a self-tuning weighted measurement fusion Kalman filter is *** the dynamic error system analysis （DESA） method,the convergence of the self-tuning weighted measurement fusion Kalman filter is proved,i.e.,the self-tuning Kalman filter converges to the corresponding optimal Kalman filter in a ***,the self-tuning weighted measurement fusion Kalman filter has asymptotic global *** simulation example for a 4-sensor target tracking system verifies its effectiveness.

关键词： Multisensor weighted measurement fusion Fused parameter estimator Fused noise variance estimator Self-tuning fusion Kalman filter Asymptotic global optimality Convergence

Self-tuning Measurement Fusion Kalman Filter for Multisensor Systems with Companion Form and Common Disturbance Noise

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Self-tuning Measurement Fusion Kalman Filter for Multisensor...

第二十九届中国控制会议

作者： ran chenjian,deng zili Department of Automation,Heilongjiang University,Harbin 150080,P.R.China

For the multisensor systems with companion form and common disturbance noise,when the model parameters and noise variances are all unknown,using recursive extended least squares（RELS）algorithm,the local and fused estimators of part model parameters are *** then,the information fusion noise variance estimators and other parameters estimators are presented by using correlation method and the Gevers-Wouters algorithm with a dead *** have strong ***,a self-tuning weighted measurement fusion Kalman filter based on a self-tuning Riccati equation is *** the the dynamic error system analysis（DESA）method,it is rigorously proved that the self-tuning weighted measurement fusion Kalman filter converges to the optimal weighted measurement fusion Kalman filter in a realization,so that it has asymptotic global *** self-tuning filter can be applied to the signal processing to obtain the self-tuning measurement fusion signal filters.A simulation example of a self-tuning fused filter for ARMA signal with 3-sensor signal shows its effectiveness.

关键词： Multisensor Information Fusion Filter Measurement Fusion Common Noises Self-tuning Fusion Filter Parameter Identification

Descriptor Wiener state fuser

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Descriptor Wiener state fuser

2009中国控制与决策会议

作者： chenjian ran~1,zili deng~2 1.Department of Automation,Heilongjiang University,Harbin 150080 2.Department of Automation,Heilongjiang University,Harbin 150080

＜正＞By the modem time series analysis method,based on the autoregressive moving average（ARMA） innovation model and white noise estimation theory,a new local descriptor Wiener state estimators are presented,and using the optimal fusion rule weighted by diagonal matrices,a distributed decoupled descriptor Wiener state fuser is presented for the linear discrete stochastic descriptor systems with *** realizes a decoupled fusion estimation for state *** descriptor Wiener state fuser is obtained by weighting the local Wiener state *** order to compute the optimal weights,the formulas of computing the cross-covariances among local estimation errors are *** can handle the fused filtering,smoothing,and prediction problems in a unified *** accuracy is higher than that of each local estimator.A Monte Carlo simulation example shows its effectiveness.

关键词： Multisensor information fusion Weighted fusion Decoupled fusion Descriptor system Wiener state fuser White noise estimator Modern time series analysis method and ARMA innovation model

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2009中国控制与决策会议

作者： chenjian ran~1,zili deng~2 1.Department of Automation,Heilongjiang University,Harbin 150080 2.Department of Automation,Heilongjiang University,Harbin 150080

＜正＞For the multisensor linear discrete time-invariant systems with correlated measurement noises and with different measurement matrices,based on the weighted least squares（WLS） method,applying the orthogonal transformation, two weighted measurement fusion Kalman filters are *** the information filter,it is proved that they are functionally equivalent to the centralized fusion Kalman filter,*** corresponding two weighted measurement fusion Kalman filters are numerically identical to the centralized fusion Kalman filter,so that they have the global optimality. Compared with the centralized fusion Kalman filter,they can obviously reduce the computational *** numerical simulation examples in the tracking systems verify their functional equivalence and compare their computational load.

关键词： Multisensor information fusion Kalman filter Measurement fusion Correlated measurement noises Global optimality and Orthogonal transformation

Reduced dimension weighted measurement fusion Kalman filtering algorithm

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Reduced dimension weighted measurement fusion Kalman filteri...

2009中国控制与决策会议

作者： chenjian ran ~1,zili deng~2 1.Department of Automation,Heilongjiang University,Harbin 150080 2.Department of Automation,Heilongjiang University,Harbin 150080

＜正＞For the multisensor linear discrete time-invariant systems with correlated measurement noises and with dif ferent measurement matrices,based on the linear unbiased minimum variance criterion,a weighted measurement fusion Kalman filtering algorithm is *** is identical to that obtained by the Weighted Least Squares（WLS） method, and is numerically identical to the centralized fusion Kalman filtering algorithm,so that it has the global *** optimal weights are given by the Lagrange multiplier method,but its computation burden is *** order to reduce the computational burden,a reduced dimension weighted measurement fusion Kalman filtering algorithm is derived,which avoids the Lagrange multiplier method,and can significantly reduced the computational *** comparison of computational count between two algorithms is given.A simulation example shows effectiveness and correctness of the proposed algorithm.

关键词： Weighted measurement fusion Linear unbiased minimum variance(LUMV) criterion Lagrange multiplier method and Reduced dimension algorithm

Performance Analysis of an Efficient Integration System of Coal-Fired Power Plant,Solar Thermal Energy and CO_(2)Capture

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Journal of Thermal Science 2024年第4期33卷 1509-1522页

作者： WANG Yuhao WANG Ruilin LIU Lanhua XING chenjian GUO Yafei YANG Qingshan YING Jiaheng SUN Jian LI Wenjia LIU Yuanyuan ZHAO Chuanwen School of Energy and Mechanical Engineering Nanjing Normal UniversityNanjing210023China China Huadian Group Co.LTD.Shanghai Branch Shanghai200120China Key Laboratory of Efficient Utilization of Low and Medium Grade Energy(Tianjin University) Ministry of Education of ChinaTianjin300350China Huadian Zhengzhou Mechanical Design Institute Company Limited Zhengzhou450046China

Coal-fired power plant is a major contributor to greenhouse gas *** post-combustion capture is a promising method for CO_(2)emission reduction but the high thermal demand is *** address this issue,solar thermal energy and CO_(2)capture are jointly integrated into the coal-fired power plant in this *** solar thermal energy is employed to meet the heat requirement of the CO_(2)capture process,thereby avoiding the electricity loss caused by self-driven CO_(2)***,the heat released from the carbonation reaction of MgO adsorbent is integrated into the steam rankine *** partially substituting the extracted steam for feedwater heating,the electricity output of the power plant is further *** to the results from the developed model,the system could achieve a CO_(2)capture rate of 86.5%and an electricity output enhancement of 9.8%compared to the reference system,which consists of a self-driven CO_(2)capture coal-fired power plant and PV generation *** operational strategy is also optimized and the amount of CO_(2)emission reduction on a typical day is increased by 11.06%.This work shows a way to combine fossil fuels and renewable energy for low carbon emissions and efficient power generation.

关键词： CO_(2)capture parabolic trough collector solar aided coal-fired electricity generation

Convergence analysis of self-tuning Riccati equation for systems with correlation noises

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Frontiers of Electrical and Electronic Engineering in China 2009年第4期4卷 409-416页

作者： chenjian ran Guili TAO Jinfang LIU zili deng Department of Automation Heilongjiang UniversityHarbin 150080China Department of Computer Heilongjiang Institute of Science and TechnologyHarbin 150080China Department of Computer and Information Engineering Harbin Deqiang Business CollegeHarbin 150080China

For linear discrete time-invariant stochastic system with correlated noises,and with unknown state transition matrix and unknown noise statistics,substituting the online consistent estimators of the state transition matrix and noise statistics into steady-state optimal Riccati equation,a new self-tuning Riccati equation is presented.A dynamic variance error system analysis(DVESA)method is presented,which transforms the convergence problem of self-tuning Riccati equation into the stability problem of a time-varying Lyapunov *** decision criterions of the stability for the Lyapunov equation are *** the DVESA method and Kalman filtering stability theory,it proves that with probability 1,the solution of self-tuning Riccati equation converges to the solution of the steady-state optimal Riccati equation or time-varying optimal Riccati *** proposed method can be applied to design a new selftuning information fusion Kalman filter and will provide the theoretical basis for solving the convergence problem of self-tuning filters.A numerical simulation example shows the effectiveness of the proposed method.

关键词： Kalman filter Riccati equation Lyapunov equation self-tuning filter convergence stability dynamic variance error system analysis(DVESA)method

技术溢出视角下服务贸易自由化对服务业出口服务质量的作用机制

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商业经济研究 2024年第7期 165-170页

作者：张谌建中国社会科学院北京100084

服务贸易正逐步成为世界各国引领创新与推动合作的重要力量,同时各国之间的服务贸易关系日益深化,使得服务贸易展现出强大韧性,为巩固全球产业链做出了显著贡献。目前我国服务贸易规模迅速扩大,国际地位不断提升,服务贸易成为拉动我国... 详细信息

服务贸易正逐步成为世界各国引领创新与推动合作的重要力量,同时各国之间的服务贸易关系日益深化,使得服务贸易展现出强大韧性,为巩固全球产业链做出了显著贡献。目前我国服务贸易规模迅速扩大,国际地位不断提升,服务贸易成为拉动我国经济增长和贸易扩张的新趋势和新动力。然而,与我国服务业出口规模形成鲜明对比的是,服务业出口服务质量仍处于较低水平,传统服务贸易占比尚居于高位。而推进服务贸易自由化有利于促进国内外企业合作,促使服务业先进技术由外到内溢流,从而使我国服务类企业进一步激发创新活力,提升出口服务质量。基于此,本文实证分析技术溢出视角下服务贸易自由化对服务业出口服务质量的作用机制,同时提出针对性建议,旨在引导我国提升服务贸易自由化程度,促进技术溢出,实现我国服务业出口服务质量提升。研究结果显示:服务贸易自由化能够显著促进服务业出口服务质量提升。研发投入、教育水平、基础设施建设、金融发展水平以及知识产权保护力度均能显著提高服务业出口服务质量。技术溢出在服务贸易自由化与服务业出口服务质量之间起显著中介作用。

关键词：服务贸易贸易自由化服务业出口出口服务质量技术溢出