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Self-tuning Weighted Measurement Fusion Wiener Signal Filter

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Self-tuning Weighted Measurement Fusion Wiener Signal Filter

第二十九届中国控制会议

作者： gao yuan,deng zili department of automation,heilongjiang university,harbin 150080,p.r.china

For the multisensor single channel autoregressive moving average（ArMA）signals with unknown model parameters and noise variances,using the recursive instrumental variable（rIV）and the correlated method,the strong consistent information fusion estimators of model parameters and noise variances are presented,and then substituting them into the optimal weighted measurement fusion Wiener signal filter,a self-tuning weighted measurement fusion Wiener signal filter is ***,applying the dynamic error system analysis（DESA）method,it is rigorously proved that the self-tuning fused Wiener filter converges to the optimal fused Wiener filter in a realization,so that it has asymptotically global optimality.A simulation example shows its effectiveness.

关键词： Self-tuning Weighted Measurement Fusion Filter Correlation Method Information Fusion Identifier Unknown Model parameters 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

The Immense Impact of reverse Edges on Large Hierarchical Networks

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Engineering 2024年第5期36卷 240-249页

作者： Haosen Cao Bin-Bin Hu Xiaoyu Mo Duxin Chen Jianxi gao Ye yuan Guanrong Chen Tamás Vicsek Xiaohong Guan Hai-Tao Zhang MOE Engineering research Center of Autonomous Intelligent Unmanned Systems State Key Laboratory of Intelligent Manufacturing Equipment and TechnologySchool of Artificial Intelligence and AutomationHuazhong University of Science and TechnologyWuhan 430074China School of Mechanical and Aerospace Engineering Nanyang Technological UniversitySingapore 639798Singapore Jiangsu Key Laboratory of Networked Collective Intelligence School of MathematicsSoutheast UniversityNanjing 210096China department of Computer Science Rensselaer Polytechnic InstituteTroyNY 12180USA department of Electronic Engineering City University of Hong KongHong Kong 999077China department of Biological physics Eötvös UniversityBudapest 1117Hungary MOE Key Laboratory for Intelligent Networks and Network Security School of Automation Science and EngineeringXi’an Jiaotong UniversityXi’an 710049China

Hierarchical networks are frequently encountered in animal groups,gene networks,and artificial engineering systems such as multiple robots,unmanned vehicle systems,smart grids,wind farm networks,and so *** structure of a large directed hierarchical network is often strongly influenced by reverse edges from lower-to higher-level nodes,such as lagging birds’howl in a flock or the opinions of lowerlevel individuals feeding back to higher-level ones in a social *** study reveals that,for most large-scale real hierarchical networks,the majority of the reverse edges do not affect the synchronization process of the entire network;the synchronization process is influenced only by a small part of these reverse edges along specific *** surprisingly,a single effective reverse edge can slow down the synchronization of a huge hierarchical network by over 60%.The effect of such edges depends not on the network size but only on the average in-degree of the involved *** overwhelming majority of active reverse edges turn out to have some kind of“bunching”effect on the information flows of hierarchical networks,which slows down synchronization *** finding refines the current understanding of the role of reverse edges in many natural,social,and engineering hierarchical networks,which might be beneficial for precisely tuning the synchronization rhythms of these *** study also proposes an effective way to attack a hierarchical network by adding a malicious reverse edge to it and provides some guidance for protecting a network by screening out the specific small proportion of vulnerable nodes.

关键词： Synchronizability Large hierarchical networks reverse edges Information flows Complex networks

New results in Cooperative Adaptive Optimal Output regulation

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Journal of Systems Science & Complexity 2024年第1期37卷 253-272页

作者： DONG Yuchen gao Weinan JIANG Zhong-ping State Key Laboratory of Synthetical automation for process Industries Northeastern UniversityShenyang 110819China department of Electrical and Computer Engineering Tandon School of EngineeringNew York UniversityBrooklynNY 11201USA

This paper investigates the cooperative adaptive optimal output regulation problem of continuous-time linear multi-agent *** the multi-agent system dynamics are uncertain,solving regulator equations and the corresponding algebraic riccati equations is challenging,especially for high-order *** this paper,a novel method is proposed to approximate the solution of regulator equations,i.e.,gradient descent *** is worth noting that this method obtains gradients through online data rather than model information.A data-driven distributed adaptive suboptimal controller is developed by adaptive dynamic programming,so that each follower can achieve asymptotic tracking and disturbance ***,the effectiveness of the proposed control method is validated by simulations.

关键词： Adaptive dynamic programming cooperative output regulation gradient descent method multi-agent systems.

Information Fusion Steady-State White Noise Deconvolution Estimators with Time-Delayed Measurements

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Information Fusion Steady-State White Noise Deconvolution Es...

第二十七届中国控制会议

作者： Sun Xiaojun,deng zili department of automation,university of heilongjiang,harbin 150080,p.r.china

White noise deconvolution or input white noise estimation problem has important application backgrounds in oil seismic exploration,communication and signal *** the modern time series analysis method,based on the autoregressive moving average(ArMA) innovation model,under the linear minimum variance optimal fusion rules,three optimal weighted fusion white noise deconvolution estimators are presented for the multisensor systems with time-delayed measurements and correlated *** can handle the input white noise fused filtering,prediction and smoothing problems,and are applicable for the multisensor systems with colored measurement *** are locally optimal,and globally *** accuracy of the fusers is higher than that of each local white noise *** order to compute the optimal weights,the formula of computing the local estimation error cross-covariances is given.A Monte Carlo simulation example for the system with 3 sensors and the Bernoulli-Gaussian input white noise shows their effectiveness and performances.

关键词： Multisensor Information Fusion White Noise Estimator Deconvolution Time-delayed Measurements Modern Time Series Analysis Method

Wind disturbance compensated path-following control for fixed-wing UAVs in arbitrarily strong winds

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Chinese Journal of Aeronautics 2024年第2期37卷 431-445页

作者： Hao LU Lan gao Yunda YAN Mingzhe HOU Chenliang WANG Hangzhou Innovation Institute Beihang UniversityHangzhou 310051China School of Information Science and Technology Hangzhou Normal UniversityHangzhou 311121China department of Computer Science University College LondonLondon WC1E 6BTUnited Kingdom Center for Control Theory and Guidance Technology Harbin Institute of TechnologyHarbin 150001China School of automation Science and Electrical Engineering Beihang UniversityBeijing 100191China

Wind is the primary challenge for low-speed fixed-wing unmanned aerial vehicles to follow a predefined flight *** cope with various wind conditions,this paper proposes a wind disturbance compensated path following control strategy where the wind disturbance estimate is incorporated with the nominal guiding vector field to provide the desired airspeed direction for the *** the control input vector for the outer-loop kinematic subsystem needs to satisfy a magnitude constraint,a scaling mechanism is introduced to tune the proportions of the compensation and nominal ***,an optimization problem is formulated to pursue a maximum wind compensation in strong winds,which can be solved analytically to yield two scaling factors.A cascaded inner-loop tracking controller is also designed to fulfill the outer-loop wind disturbance compensated guiding vector ***-fidelity simulation results under sensor noises and realistic winds demonstrate that the proposed path following algorithm is less sensitive to sensor noises,achieves promising accuracy in normal winds,and mitigates the deviation from a desired path in wild winds.

关键词： path following Guiding vector field Wind disturbance Disturbance rejection Fixed wings

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

Self-tuning Weighted Measurement Fusion Wiener Filter and Its Convergence

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Self-tuning Weighted Measurement Fusion Wiener Filter and It...

2009中国控制与决策会议

作者： yuan gao,Weiling Wang,zili deng department of automation,heilongjiang university,harbin 150080,china

For the multisensor system with identical measurement matrix and correlated measurement noises,by correlated method,the online estimators of the noise statistics are *** on modern time series analysis method,a self-tuning weighted measurement fusion Wiener filter is presented,which avoids Lyapunov and riccati equations,reduces the computational burden and is suitable for real time *** dynamic error system analysis (DESA) method,it is rigorously proved that the proposed self-tuning Wiener filter converges to the optimal Wiener filter in a realization or with probability one,*** has asymptotical global optimality.A simulation example for a target tracking systems with 3 sensors shows its effectiveness.

关键词： Weighted Measurement Fusion Self-tuning Wiener Filter Convergence Dynamic Error System Analysis(DESA) Method Modem Time Series Analysis Method

Information Fusion Steady-state White Noise Deconvolution Estimators

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Information Fusion Steady-state White Noise Deconvolution Es...

第二十七届中国控制会议

作者： Sun Xiaojun,Wang Shigang,deng zili department of automation,university of heilongjiang,harbin 150080,p.r.china

White noise deconvolution or input white noise estimation problem has important application backgrounds in oil seismic exploration,communication and signal *** the modern time series analysis method,based on the autoregressive moving average（ArMA） innovation model and the optimal fusion rules in linear minimum variance sense,the new information fusion white noise deconvolution estimators are presented for the general multisensor systems with different local dynamic models and correlated noises,*** can handle the input white noise fused filtering,prediction and smoothing problems,and are applicable for the systems with colored measurement *** is locally optimal and globally *** accuracy of the fuser is higher than that of each local white noise *** order to compute the optimal weights,the formula of computing the local estimation error cross-covariances is given.A Monte Carlo simulation example for the system with Bernoulli-Gaussian input white noise shows their effectiveness and performances.

关键词： Information fusion Different local model White noise estimator Deconvolution Weighted fusion