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A NEW DE-NOISING METHOD BASED ON 3-BAND WAVELET AND NONPARAMETRIC adaptive estimation

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Journal of Electronics(China) 2007年第3期24卷 358-362页

作者： Li Li Peng Yuhua Yang Mingqiang Xue Peijun School of Inform. Sci. and Eng. Shandong Univ. Jinan 250100 China School of Math. Shandong Univ. Jinan 250100 China

Wavelet de-noising has been well known as an important method of signal de-noising. Recently,most of the research efforts about wavelet de-noising focus on how to select the threshold,where Donoho method is applied widely. Compared with traditional 2-band wavelet,3-band wavelet has advantages in many aspects. According to this theory,an adaptive signal de-noising method in 3-band wavelet domain based on nonparametric adaptive estimation is proposed. The experimental results show that in 3-band wavelet domain,the proposed method represents better characteristics than Donoho method in protecting detail and improving the signal-to-noise ratio of reconstruction signal.

关键词： Nonparametric adaptive estimation 3-band wavelet Signal de-noising

adaptive Parameter estimation and Velocity Control of UAV Systems

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Adaptive Parameter Estimation and Velocity Control of UAV Sy...

estimation of IIR Systems with Binary-Valued Observations

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作者： Hang Gui Ruisheng Sun Jieqing Chen Nanjing University of Science and Technology

This paper presents an adaptive velocity control method for small UAV systems. In the design, an adaptive parameter estimation with prescribed performance is introduced to online estimate the model parameters of UAVs. The velocity control parameters are adaptively updated in terms of the variations of the flight dynamics to improve the UAV flight performance. We identify the UAV’s model through an adaptive estimator and then adaptively tune the controller parameters, which will overcome the variations of model parameters and extern disturbances. Finally,the simulation results verify that the adaptive velocity control system has better control performance than the conventional PID velocity control system.

关键词： UAV velocity control adaptive control adaptive estimation prescribed performance estimation

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Chinese Annals of Mathematics,Series B 2023年第5期44卷 687-702页

作者： Ruifen DAI Lei GUO Data Science Institute Shandong UniversityJinan 250100China Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceChinese Academy of SciencesBeijing 100190China

estimation and control problems with binary-valued observations exist widely in practical ***,most of the related works are devoted to finite impulse response(FIR for short)systems,and the theoretical problem of infinite impulse response(IIR for short)systems has been less *** study the estimation problems of IIR systems with binary-valued observations,the authors introduce a projected recursive estimation algorithm and analyse its global convergence properties,by using the stochastic Lyapunov function methods and the limit theory on double array *** is shown that the estimation algorithm has similar convergence results as those for FIR systems under a weakest possible non-persistent excitation ***,the upper bound for the accumulated regret of adaptive prediction is also established without resorting to any excitation condition.

关键词： Binary-valued observations Infinite impulse response adaptive estimation Double array martingales adaptive prediction

Joint state and parameter estimation in particle filtering and stochastic optimization

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控制理论与应用（英文版） 2008年第2期6卷 215-220页

作者： Xiaojun YANG Keyi XING Kunlin SHI Quan PAN The State Key Laboratory for Manufacturing System Engineering System Engineering Institute Xi＇an Jiaotong University Xi＇an Shaanxi 710049 China Xi＇an Institute of Electromechanical Information Technology Xi＇an Shaanxi 710065 China School of Automation Northwestern polytechnical University Xi＇an Shaanxi 710072 China

In this paper, an adaptive estimation algorithm is proposed for non-linear dynamic systems with unknown static parameters based on combination of particle filtering and Simultaneous Perturbation Stochastic Approxi- mation （SPSA） technique. The estimations of parameters are obtained by maximum-likelihood estimation and sampling within particle filtering framework, and the SPSA is used for stochastic optimization and to approximate the gradient of the cost function. The proposed algorithm achieves combined estimation of dynamic state and static parameters of nonlinear systems. Simulation result demonstrates the feasibilitv and efficiency of the proposed algorithm

关键词： Parameter estimation Particle filtering Sequential Monte Carlo Simultaneous perturbation stochastic approximation adaptive estimation

ON ASYMPTOTICALLY EFFICIENT estimation FOR A SEMIPARAMETRIC REGRESSION MODEL

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Acta Mathematicae Applicatae Sinica 1997年第3期13卷 302-313页

作者：熊健梁华 Department of Mathematics Xiangtan Techer's College Xiangtan China Institute of Systems Science the Chinese Academy of Sciences Beijing China

Consider the model Y=Xτβ+g(T)+ε. Here g is a smooth but unknown function, β is a k×1 parameter vector to be estimated and ε, is an random error with mean 0 and variance σ2. The asymptotically efficient estimator of β is constructed on the basis of the model Yi=Xτiβ+g(Ti)+εi, i=1,…,n, when the density functions of (X,T) and ε are known or ***, an asymptotically normal estimator of σ2 is given.

关键词： Asymptotically efficient estimation adaptive estimation semiparametric regression model

Design and comparison of minimal symmetric model-subset for maneuvering target tracking

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Journal of Systems Engineering and Electronics 2010年第2期21卷 268-272页

作者： Fuming Sun Xu E Hongyu Ma School of Electronic and Informational Engineering Liaoning University of Technology Jinzhou 121001 E R. China

Model-set is utilized in state estimation for maneuver- ing target tracking. Two minimal symmetric model-subsets are designed and investigated by moment matching method, which include hypersphere-symmetric model-subset and axis-symmetric model-subset, if system mode is a random variable and obeys certain probability distribution. They can be used as the fun- damental model-subset for multiple models estimation with fixed structure, variable structure and moving bank. The model-groups constructed by above designed subsets are given, which give the practical guidance for use of model-set in multiple models ap- proach with a variable structure. Simulation results show that the performances of two minimal model-set significantly outperform the corresponding model-sets with fixed spacing.

关键词： adaptive estimation multiple models target tracking variable structure.

adaptive feedback control for nonlinear triangular systems subject to uncertain asymmetric dead-zone input

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Control Theory and Technology 2023年第4期21卷 530-540页

作者： Minghui Feng Yanjie Chang Zhiyu Duan Xianfu Zhang School of Control Science and Engineering Shandong UniversityJinan250061ShandongChina

In this paper,an adaptive control strategy is proposed to investigate the issue of uncertain dead-zone input for nonlinear triangular systems with unknown *** considered system has no precise priori knowledge about the dead-zone feature and growth rate of ***,a dynamic gain is introduced to deal with the unknown growth rate,and the dead-zone characteristic is processed by the adaptive estimation approach without constructing the dead-zone ***,by virtue of hyperbolic functions and sign functions,a new adaptive state feedback controller is proposed to guarantee the global boundedness of all signals in the closed-loop ***,the uncertain dead-zone input problem for nonlinear upper-triangular systems is solved by the similar control ***,two simulation examples are given to verify the effectiveness of the control scheme.

关键词： Dead-zone input Dynamic gain adaptive estimation Global boundedness

Leader-follower formation control without leader's velocity information

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Science China(Information Sciences) 2014年第9期57卷 230-241页

作者： SHEN DongBin SUN ZhenDong SUN WeiJie College of Automation Science and Engineering South China University of Technology Key Laboratory of Systems & Control Academy of Mathematics and Systems ScienceChinese Academy of Sciences

In this paper,we consider the mobile robots formation control problem without direct measurement of the leader robot’s linear *** decentralized nonlinear algorithms are proposed,respectively,based on adaptive dynamic feedback and immersion&invariance estimation based second order sliding mode control *** main idea is to solve formation problem by estimating the leader robots’s linear velocity,while maintaining the given predefined separation distance and bearing angle between the leader robot and the follower *** stability of the closed-loop system is proven by means of the Lyapunov *** proposed controllers are smooth,continuous and robust against unknown bounded uncertainties such as sensor inaccuracy between the outputs of sensors and the true values in collision free *** examples and physical vehicles experiments are presented to verify the effectiveness of the proposed design approaches,and the proposed designed methodologies are carefully compared to illustrate the pros and cons of the approaches.

关键词： nonholonomic mobile robots leader-follower formation adaptive dynamic feedback adaptive estimation immersion & invariance

adaptive Statistical Spatial Downscaling of Precipitation Supported by High-Resolution Atmospheric Simulation Data for Mountainous Areas of Nepal

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Journal of Meteorological Research 2023年第4期37卷 508-520页

作者： Hua YANG Kun YANG Jun QIN Baohong DING Yaozhi JIANG Yingying CHEN Xu ZHOU Yan WANG Shankar SHARMA National Tibetan Plateau Data Center State Key Laboratory of Tibetan Plateau Earth SystemEnvironment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101 University of Chinese Academy of Sciences Beijing 100049 Ministry of Education Key Laboratory for Earth System Modeling Department of Earth System ScienceInstitute for Global Change StudiesTsinghua UniversityBeijing 100084 State Key Laboratory of Resources and Environmental Information System Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101 Key Laboratory of Land Surface Pattern and Simulation Institute of Geographic Sciences and Natural Resources ResearchChinese Academy of SciencesBeijing 100101

In complex terrain regions, it is very challenging to obtain high accuracy and resolution precipitation data that are required in land hydrological studies. In this study, an adaptive precipitation downscaling method is proposed based on the statistical downscaling model MicroMet. A key input parameter in the MicroMet is the precipitation adjustment factor(PAF) that shows the elevation dependence of precipitation. Its value is estimated conventionally based on station observations and suffers sparse stations in high altitudes. This study proposes to estimate the PAF value and its spatial variability with precipitation data from high-resolution atmospheric simulations and tests the idea in Nepal of South Himalayas, where rainfall stations are relatively dense. The result shows that MicroMet performs the best with the PAF value estimated from the simulation data at the scale of approximately 1.5 degrees. Not only the value at this scale is qualitatively consistent with early knowledge obtained from intensive observations, but also the downscaling performance with this value is better than or comparable to that with the PAF estimated from dense station data. Finally, it is shown that the PAF estimation, although critical, cannot replace the importance of increasing input station density for downscaling.

关键词： precipitation statistical downscaling precipitation adjustment factor adaptive estimation high resolution dynamical downscaling