Description: The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller(FCMAC) is proposed to control this cable compensation system. In FCMAC ,without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective. -The cable compensation system is an experiment system that performs simulations of partial or microgravity environments on earth. It is a highly nonlinear and complex system.In this paper, a network based on the theory of the Fuzzy Cerebellum Model Articulation Controller (FCMAC) is proposed to control this cable compensation system. In FCMAC, without appropriate learning rate, the control system based on FCMAC will become unstable or its convergence speed will become slow.In order to guarantee the convergence of tracking error, we present a new kind of optimization based on adaptive GA for selecting learning rate.Furthermore, this approach is evaluated and its performance is discussed.The simulation results shows that performance of the FCMAC based the proposed method is stable and more effective. Platform: |
Size: 69632 |
Author:Alice |
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Description: 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain algorithm, which can be used for target tracking, multi-target tracking, and video tracking and positioning. solve nonlinear problems of capacity than Kalman filtering, EKF, UKF much better, and I treasure the good stuff, now up with the share could not bear children, she sets the wolf, we hope that support each other and work together to promote. Platform: |
Size: 14336 |
Author:zhang |
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Description: 基本粒子滤波器的实现,对非线性非高斯目标可进行有效跟踪!-elementary particle filter to the realization of non-Gaussian nonlinear objectives can be effectively tracking! Platform: |
Size: 1024 |
Author:wyb |
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Description: 在目标被动式跟踪中广泛应用的伪量测变换估计器(PLE)具有良好的误差收敛性。然而由于等价噪声和状态的相关性,该估计器的估计是有偏的。提出的强跟踪滤波器(STF)通过强制白化残差具有自适应地校正估计偏差和迅速跟踪状态变化的能力。STF已经在非线性系统时滞估计、故障诊断与容错控制方面取得了很好的效果。-Passive target tracking is widely used in the pseudo-measurement transform estimator (PLE) has a good error convergence. However, due to the equivalent noise and the relevance of state, the estimator is a biased estimate of. Raised strong tracking filter (STF) has adopted mandatory bleaching residuals adaptively estimated bias correction and rapid tracking of the status change. STF has been estimated in the time-delay nonlinear systems, fault diagnosis and fault-tolerant control has been achieved very good results. Platform: |
Size: 7168 |
Author:冯絮影 |
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Description: 在对目标进行跟踪时，由于目标的运动方程和观测方程的非线性性，使得滤波时采用传统的卡尔曼滤波器时存在较大误差，不敏卡尔曼滤波器很好的避免了这一点。-Tracking of targets, because the objectives and observation equations of motion of nonlinear equations, and makes filtering when using the traditional Kalman filter when there is a big error, not a very good filter敏卡尔曼avoid this . Platform: |
Size: 2048 |
Author:liqiangqiang |
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Description: This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and-This paper studies the problem of tracking a ballistic object inthe reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and thetheoretical Cramer-Rao lower bounds (CRLB) of estimationerror are derived. The estimation performance (error mean and Platform: |
Size: 2048 |
Author:zhangsheng |
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Description: This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and-This paper studies the problem of tracking a ballistic object inthe reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and thetheoretical Cramer-Rao lower bounds (CRLB) of estimationerror are derived. The estimation performance (error mean and Platform: |
Size: 2048 |
Author:zhangsheng |
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Description: This paper studies the problem of tracking a ballistic object in
the reentry phase by processing radar measurements. A suitable
(highly nonlinear) model of target motion is developed and the
theoretical Cramer—Rao lower bounds (CRLB) of estimation
error are derived. The estimation performance (error mean and-This paper studies the problem of tracking a ballistic object inthe reentry phase by processing radar measurements. A suitable (highly nonlinear) model of target motion is developed and thetheoretical Cramer-Rao lower bounds (CRLB) of estimationerror are derived. The estimation performance (error mean and Platform: |
Size: 1024 |
Author:zhangsheng |
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Description: Abstract—Stable direct and indirect decentralized adaptive radial basis
neural network controllers are presented for a class of interconnected
nonlinear systems. The feedback and adaptation mechanisms for each
subsystem depend only upon local measurements to provide asymptotic
tracking of a reference trajectory. Due to the functional approximation
capabilities of radial basis neural networks, the dynamics for each
subsystem are not required to be linear in a set of unknown coeffi cients
as is typically required in decentralized adaptive schemes. In addition,
each subsystem is able to adaptively compensate for disturbances and
interconnections with unknown bounds. Platform: |
Size: 151552 |
Author:centema |
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Description: "A Tutorial on Particle Filters for Online Nonlinear Non-Gaussian Bayesian Tracking"
This is a paper about tracking by particle filter.
This is very useful. Platform: |
Size: 330752 |
Author:Wolf |
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Description: the attached file consists of matlab code for implementation of sequential importance sampling particle filter given in IEEE paper entitled as "A TUTORIAL ON PARTICLE FILTERS FOR ONLINE NONLINEAR NON GUASSIAN BAYESIAN TRACKING" Platform: |
Size: 1024 |
Author:babi |
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Description: 在机动目标跟踪中，机动目标模型是机动目标跟踪的基本要素之一，一般希望机动目标模型能准确表征目标机动时的各种运动状态。比较常用的模型有匀速运动(CV)模型、匀加速运动(CA) 模型、时间相关模型（Singer）和机动目标“当前”统计模型。上述模型均采用机动频率表征目标的机动情况。在应用当中，通常采用固定的机动频率，这就表示机动目标的机动时间是一定的，而实际上机动目标的机动时间是不断变化的，也就是说机动频率是不断变化的，采用固定机动频率必然会带来误差。采样周期在0.5—2S时，机动频率越小跟踪精度越高[1]，但机动频率仍然是固定值。本文提出的基于神经网络的机动频率自适应调整方法可以使机动频率随机动而变化，从而提高状态估计的准确性，提高跟踪精度。本文将小波神经网络用于机动目标跟踪中机动频率的自适应调整，该算法对机动目标“当前”统计模型中的机动频率进行实时修改, 从而自适应的改变机动频率,使跟踪算法与目标的真实状态更接近。该算法采用小波神经网络的离线训练，实时性好。-The maneuver of the maneuvering target is uncertain. The maneuvering frequency is constantly changeable, but traditionally it is beforehand determined as a constant based on the target state estimation in the state model of the maneuvering target. The maneuver of the maneuvering target makes the kinematics equation of the target model mismatch with the practical motion model and the tracking error will be increased. Based on the advantages of the self-learning, the rapid convergence rate and the nonlinear approximation ability of the wavelet neural network, it was put forward to be used in the field of target tracking in the paper. The new residual is used as the input of the wavelet neural network, the output of the network is used to adjust adaptively the maneuvering frequency of the CS model. The algorithm is more close to the real state of the target. The simulation results showed that tracking error can be reduced and the tracking accuracy can be improved. Platform: |
Size: 4096 |
Author:李隆基 |
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Description: This thesis aimed to eliminate tracking
error of traveling a circular profile on the CNC machine tools. Friction is one of the
most significant source of nonlinear disturbance for the motion control which caused
by the relative motion of different contact surface at the low velocity. The nonlinear
component of friction such as static friction (stiction) and the Coulomb friction should
be overcome so that the tracking error will be eliminated. When the X-Y tables are
tracking a circular profile, quadrant glitches appear at ninety degrees intervals, i.e. the
motion of one axis has a zero velocity crossing and reverses direction.-This thesis is aimed to eliminate tracking
error of traveling a circular profile on the CNC machine tools. Friction is one of the
most significant source of nonlinear disturbance for the motion control which caused
by the relative motion of different contact surface at the low velocity. The nonlinear
component of friction such as static friction (stiction) and the Coulomb friction should
be overcome so that the tracking error will be eliminated. When the X-Y tables are
tracking a circular profile, quadrant glitches appear at ninety degrees intervals, i.e. the
motion of one axis has a zero velocity crossing and reverses direction. Platform: |
Size: 685056 |
Author:tatos |
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Description: 粒子滤波matlab程序，可用于机动目标跟踪，适用于非线性系统-Particle filter matlab program can be used for maneuvering target tracking for nonlinear systems Platform: |
Size: 4096 |
Author:chenchao |
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Description: 关于非线性跟踪微分器的源程序，有需要的朋友可以看一看-About nonlinear tracking differentiator source, a friend in need can take a look Platform: |
Size: 1024 |
Author:hukai |
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Search - nonlinear tracking