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: |
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Author:冯絮影 |
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Description: 支持向量机以其模型结构简单、较好的推广能力和全局最优解等特点已经被用来进行智能
控制的研究，主要包括采用支持向量机回归的非线性时间序列的建模与预测、系统辨识等建模方
面的研究以及优化控制、学习控制和预测控制等方面的研究以及采用支持向量机的故障诊断的研
究。由于现有SVMR基于二次规划的优化方法不适合控制过程的在线训练，因此出现了对SVMR
在线训练算法的研究。分析了国内外这些研究内容的最新研究进展，旨在探讨归纳支持向量机在控
制领域研究的主要成果和存在的问题，以便为进一步的研究提供一定的支持与帮助-Abstract:The support vector machines,which characterizes a simple model structure,good generalization,global optimal
solution etc.,has been applied in the intelligent control.The current research includes SVMR modeling and prediction of
nonlinear times serial,system identification,optimal control,learning control,predict control etc.,and SVM-based fault
diagnosis.Since SVMR based on the quadratic programming unfits for the online training of control,the current research
includes the online training of SVMR.The latest development of those contents in the domestic and overseas research were
analyzed,and the main achievements and problems in SVMR control were summed up in order to provide some support and
help for the further research.
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Size: 533504 |
Author:alice |
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Description: 近似熵是系统复杂性测度很有效的一种方法，在医学、机械设备故障的诊断等方面得到广泛应用。近似熵复杂性测度具有计算简便，对时间序列长度等条件要求相对较低等优点，因而更具有实用价值，是水文非线性系统领域中的新型工具。-Approximate entropy is a measure of system complexity, a very effective way, in medicine, the diagnosis of mechanical equipment failures, etc. are widely used. Approximate entropy complexity measure with simple calculation, the length of time series such as conditions require relatively low, etc., and therefore more practical value, is in the field of nonlinear hydrological system new tools. Platform: |
Size: 166912 |
Author:feiyun |
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Description: 近似熵是系统复杂性测度很有效的一种方法，在医学、机械设备故障的诊断等方面得到广泛应用。近似熵复杂性测度具有计算简便，对时间序列长度等条件要求相对较低等优点，因而更具有实用价值，是水文非线性系统领域中的新型工具。-Approximate entropy is a measure of system complexity, a very effective way, in medicine, the diagnosis of mechanical equipment failures, etc. are widely used. Approximate entropy complexity measure with simple calculation, the length of time series such as conditions require relatively low, etc., and therefore more practical value, is in the field of nonlinear hydrological system new tools. Platform: |
Size: 166912 |
Author:feiyun |
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Description: 基于小波及非线性预测的轴承故障诊断方法Based on Wavelet and nonlinear prediction of fault diagnosis method of rolling bearings-Based on Wavelet and nonlinear prediction of fault diagnosis method of rolling bearings Platform: |
Size: 1235968 |
Author:f1155 |
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Description: 提出基于核函数主元分析的机械故障诊断方法, 它保留主元分析的优点并具有处理非线性的能力。该方法通过核函数映射将非线性问题转换成高维的线性特征空间, 然后对高维空间中的映射数据作主元分析,提取其非线性特征, 对机械故障模式进行识别。并与主元分析方法进行对比分析, 实验结果表明核函数主元分析法非常有效。-Proposed mechanical fault diagnosis method based on Kernel Principal Component Analysis, it retains the advantages of principal component analysis and has the ability to handle nonlinear. The kernel function mapping the nonlinear problem is converted into a high-dimensional linear feature space, the primary element analysis and mapping data in high-dimensional space, extract the nonlinear characteristics of mechanical failure mode identification. Comparative analysis and principal component analysis method, the experimental results show that Kernel Principal Component Analysis method is very effective. Platform: |
Size: 312320 |
Author:张力 |
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Description: 韩清凯等著《故障转子系统的非线性振动分析与诊断方法》附录A.2碰摩转子系统计算仿真程序-Hanqing Kai waiting for the " fault rotor system of nonlinear vibration analysis and diagnosis method in Appendix A.2 Rub Rotor System simulation program Platform: |
Size: 3072 |
Author:帝王 |
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Description: 文章对非线性系统进行了故障诊断，并做了容错控制，并用仿真实例很好滴证明了！-This paper discusses the fault diagnosis of nonlinear systems and fault-tolerant control, good drop by simulation examples prove! Platform: |
Size: 154624 |
Author:爪瓦 |
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Description: 齿轮箱故障诊断中振动信号是非线性、非平稳的，所以在分析振动信号之前需要对信号进行平稳化处理，该段是EMD分解的程序。-Gearbox Fault Diagnosis vibration signal is nonlinear, non-stationary, so before analyzing vibration signals the need for a smooth signal processing, the segment is the EMD program. Platform: |
Size: 8192 |
Author:胡永红 |
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Description: Rafael Martinez-Guerra, Juan Luis Mata-Machuca (auth.)-Fault Detection and Diagnosis in Nonlinear Systems_ A Differential and Algebraic Viewpoint-Springer International Platform: |
Size: 4352000 |
Author:dotmcontrol |
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。-RBF network can approximate any nonlinear function, can handle regular system are difficult to resolve, with good generalization ability, and fast convergence rate, it has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis. Platform: |
Size: 14336 |
Author:qjl |
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Description: 遗传算法是一种新的优化方法，在计算科学、模式识别和智能故障诊断中得到了广泛的应用。它是用来解决复杂的非线性和多维空间的优化问题，近年来也得到了更广泛的应用。-Genetic algorithm is a new optimization method, extensively used in computational science, pattern recognition and intelligent fault diagnosis. It is used in solving the complex nonlinear and multidimensional space optimization problem, in recent years has also been a more broad application. Platform: |
Size: 2048 |
Author:xiaocao |
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Description: 基于核函数的非线性维数约简方法有基于核函数的主成分分(KPCA),本算法主要应用于过程监测、故障诊断等领域。-Kernel function based nonlinear dimensionality reduction method is based on kernel function (KPCA), which is mainly used in process monitoring, fault diagnosis and so on. Platform: |
Size: 1024 |
Author:ZhangTK |
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.) Platform: |
Size: 5120 |
Author:gahuan
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Description: RBF网络能够逼近任意的非线性函数，可以处理系统内的难以解析的规律性，具有良好的泛化能力，并有很快的学习收敛速度，已成功应用于非线性函数逼近、时间序列分析、数据分类、模式识别、信息处理、图像处理、系统建模、控制和故障诊断等。(RBF network can approximate any nonlinear function, regularity can handle within the system to parse, has good generalization ability and learning, fast convergence speed, and has been successfully applied to nonlinear function approximation, time series analysis, data classification, pattern recognition, information processing, image processing, system modeling, control and fault diagnosis.) Platform: |
Size: 47104 |
Author:哼哼1214
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