To approach an effective vibration control, the emphasis of the research is an adaptive control method for vehicle suspension system. Because of the features of the passive suspension's structure, the system can o...
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ISBN:
(纸本)9781424426928
To approach an effective vibration control, the emphasis of the research is an adaptive control method for vehicle suspension system. Because of the features of the passive suspension's structure, the system can only store or exhaust the body vibration energy. So the conception of active and semi-active suspension has been advanced, which give a new way to improve the vibration performance of suspension system. The Least Means Squares (LMS) adaptive filtering algorithm is used in active suspension system. With adjusting the weight of the adaptive filter, the minimum quadratic performance index is obtained. For the vibration control of two-DOF vehicle suspension model, the simulation results show that the body's vertical vibration control based on the adaptive filtering algorithm is prominent under the excitation of road signal.
By studyingthe shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between mu and the error signal by reviewing the existing algorithm and...
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ISBN:
(纸本)9781479939039
By studyingthe shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between mu and the error signal by reviewing the existing algorithm and presents a novel variable step size LMS adaptive filtering algorithm by improving Sigmoid function based on translation transformation. The selective of parameters and the performance of convergence are discussed. Theoretical analysis and simulation results show that the proposed variable step size LMS algorithm has better performance. Comparing with some existing algorithms, the algorithm improves their convergence performance.
By studyingthe shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between μ and the error signal by reviewing the existing algorithm and...
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ISBN:
(纸本)9781479939046
By studyingthe shortage of the traditional fixed step size least mean square (LMS) algorithm. This paper builds a nonlinear function relationship between μ and the error signal by reviewing the existing algorithm and presents a novel variable step size LMS adaptive filtering algorithm by improving Sigmoid function based on translation transformation. The selective of parameters and the performance of convergence are discussed. Theoretical analysis and simulation results show that the proposed variable step size LMS algorithm has better performance. Comparing with some existing algorithms, the algorithm improves their convergence performance.
The real-timely estimation of the SOC (state of charge) is the key technology in Li-ion battery management system. In this paper, to overcome the error of the SOC estimation of Extended Kalman filter (EKF), a new esti...
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ISBN:
(纸本)9783037858615
The real-timely estimation of the SOC (state of charge) is the key technology in Li-ion battery management system. In this paper, to overcome the error of the SOC estimation of Extended Kalman filter (EKF), a new estimation method based on modified-strong tracking filter (MSTF) is applied to SOC estimation of Li-ion battery, based on the second-order RC equivalent circuit model. Experiments are made to compare the new filter with the EKE and Coulomb counting approach (Ah). The simulation results demonstrate that the new filter algorithm MSTF used in this paper has higher filtering accuracy under the same conditions.
When infrared focal plane array imaging system detects targets, especially small targets, there is the problem of low gray resolution. In this paper, an adaptive scene-based gray super-resolution technique is proposed...
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ISBN:
(纸本)9780819497765
When infrared focal plane array imaging system detects targets, especially small targets, there is the problem of low gray resolution. In this paper, an adaptive scene-based gray super-resolution technique is proposed, aiming to solve the problem. The paper gives a detailed description on the method of image gray super-resolution by adjusting the signal sample range in infrared focal plane array (IRFPA) imaging system. The method contains the following three parts: extracting the effective gray range from the scene, and obtaining the basis of super-resolution adjustment;providing the adjusting parameters after filter-predicting the basis of adjustment, combining with the adaptive LMS-based filteringalgorithm;and completing gray super-resolution by controlling the parameters in super-resolution circuit. Finally, the total solution is experiment validated. The experiment in infrared focal plane array imaging system has proven the feasibility and effectiveness of this method, and the improvement of super-resolution. Then test set shows the MRTD can be increased more than one time.
The urban traffic usually has the characteristics of time-variation and nonlinearity, real-time and accurate traffic flow forecasting has become an important component of the Intelligent Transportation System(ITS). Th...
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The urban traffic usually has the characteristics of time-variation and nonlinearity, real-time and accurate traffic flow forecasting has become an important component of the Intelligent Transportation System(ITS). The paper gives a brief introduction of the basic theory of Kalman filter, and establishes the traffic flow forecasting model on the basis of the adaptive Kalman filter, while the traditional Kalman filtering model has the shortcomings of lower forecasting accuracy and easily running into filtering divergence. The Sage&Husa adaptive filtering algorithm will appropriately estimate and correct the unknown or uncertain noise covariance, so as to improve the dynamic characteristics of the model. The simulation results demonstrate that the adaptive Kalman filtering forecasting model has stronger tracking capability and higher forecasting precision, which is applicable to the traffic flow forecasting.
In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array da...
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ISBN:
(纸本)9781467321976;9781467321969
In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array data, and multipath propagation is usually encountered due to various reflections, where the incident signals are caused to be coherent (i.e., fully correlated). In this paper, we propose a new computationally efficient subspace-based adaptivealgorithm for 2-D DOA tracking of multiple coherent incident signals by using two parallel uniform linear arrays (ULAs). In the proposed algorithm, the computationally expensive eigendecomposition and the pair-matching of estimated 2-D DOAs are avoided, and the association of estimated 2-D DOAs at two successive time instants is accomplished by employing the Luenberger observer and dynamic model of direction trajectories. The effectiveness of the proposed algorithm are verified through numerical examples.
In this article, we proposed a robust adaptivealgorithm for PN code acquisition and beamforming in direct sequence spread spectrum (DSSS) system with antenna arrays. Two adaptive filters are employed in the DSSS syst...
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ISBN:
(纸本)9781629931357
In this article, we proposed a robust adaptivealgorithm for PN code acquisition and beamforming in direct sequence spread spectrum (DSSS) system with antenna arrays. Two adaptive filters are employed in the DSSS system, one is a spatial filter acting as a beamformer and the other is a temporal filter acting as a PN code-delay estimator. The cost function of LMS adaptivealgorithm is given by constraining both the spatial filter weight and the temporal filter weight. A robust and fast adaptivealgorithm with two different iterative step size is presented in the following. Computer simulations show that the proposed algorithm becomes more robust and faster, especially in DSSS system with a large spread spectrum gain.
An amended LMS Newton algorithm is proposed which create the nonlinear functional relation of the step factor mu and the error signal e(n). And the next we discuss the factors in the amended algorithm and the performa...
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ISBN:
(纸本)9783037852866
An amended LMS Newton algorithm is proposed which create the nonlinear functional relation of the step factor mu and the error signal e(n). And the next we discuss the factors in the amended algorithm and the performance in the different IF environment. The algorithm is simple and easy to be implemented, Theoretical analysis and computer simulation show that the properties of the algorithm such as convergence speed, and steady state error ate better than those of SVSLMS algorithm.
In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array da...
详细信息
In some practical applications, the two-dimensional (2-D) direction-of-arrivals (DOAs) of incident signals should be estimated adaptively or the time-varying 2-D DOAs should be tracked promptly from the noisy array data, and multipath propagation is usually encountered due to various reflections, where the incident signals are caused to be coherent (i.e., fully correlated). In this paper, we propose a new computationally efficient subspace-based adaptivealgorithm for 2-D DOA tracking of multiple coherent incident signals by using two parallel uniform linear arrays (ULAs). In the proposed algorithm, the computationally expensive eigendecomposition and the pair-matching of estimated 2-D DOAs are avoided, and the association of estimated 2-D DOAs at two successive time instants is accomplished by employing the Luenberger observer and dynamic model of direction trajectories. The effectiveness of the proposed algorithm are verified through numerical examples.
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