An Improved Adaptive Algorithm for INS/GPS System

2013 ◽  
Vol 397-400 ◽  
pp. 1606-1610 ◽  
Author(s):  
Li Dong Wang ◽  
Ying Zhao ◽  
Ni Zhang
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Initial Conditions ◽  
Forgetting Factor ◽  
Kalman Filter Algorithm ◽  
Simulation Results ◽  
The Stability ◽  
Gps System

In INS/GPS system, the changing of initial conditions and the quality of the data can affect the convergence of the conventional Kalman filter algorithm. Sage-Husa adaptive filter algorithm is adopted in the INS/GPS system in this paper. The effecting of the forgetting factor to the improved Sage-Husa adaptive filter algorithm is studied and the simulation results show that when the forgetting factor taken near 0.97, the adaptive filtering result is best, the stability of the system is guaranteed and the convergent speed of error can be reduced.

The Design of a Wavelet-Based Neural Network Adaptive Filter

2013 ◽  
Vol 860-863 ◽  
pp. 2791-2795
Author(s):  
Qian Xiao ◽  
Yu Shan Jiang ◽  
Ru Zheng Cui
Keyword(s):  
Neural Network ◽  
Wavelet Transform ◽  
Real Time ◽  
Adaptive Filter ◽  
Adaptive Algorithm ◽  
Distributed Storage ◽  
Hopfield Neural Network ◽  
Lms Algorithm ◽  
The Neural Network ◽  
Simulation Results

Aiming at the large calculation workload of adaptive algorithm in adaptive filter based on wavelet transform, affecting the filtering speed, a wavelet-based neural network adaptive filter is constructed in this paper. Since the neural network has the ability of distributed storage and fast self-evolution, use Hopfield neural network to implement adaptive filter LMS algorithm in this filter so as to improve the speed of operation. The simulation results prove that, the new filter can achieve rapid real-time denoising.

A Variable Step Size LMS Adaptive Filtering Algorithm and Simulations Based on Computational Verb Theory

2013 ◽  
Vol 756-759 ◽  
pp. 3972-3976 ◽  
Author(s):  
Li Hui Sun ◽  
Bao Yu Zheng
Keyword(s):  
Adaptive Filtering ◽  
Adaptive Algorithm ◽  
Linear Functional ◽  
Functional Relationship ◽  
Lms Algorithm ◽  
Variable Step Size ◽  
Step Size ◽  
Filtering Algorithm ◽  
Variable Step ◽  
Simulation Results

Based on traditional LMS algorithm, variable step LMS algorithm and the analysis for improved algorithm, a new variable step adaptive algorithm based on computational verb theory is put forward. A kind of sectorial linear functional relationship is established between step parameters and the error. The simulation results show that the algorithm has the advantage of slow change which is closely to zero. And overcome the defects of some variable step size LMS algorithm in adaptive steady state value is too large.

Speed Regulation Strategies of PMSM Based on Adaptive ADRC

2012 ◽  
Vol 466-467 ◽  
pp. 546-550 ◽  
Author(s):  
Wen Gu ◽  
Jiu He Wang ◽  
Xiao Bin Mu ◽  
Sheng Sheng Xu
Keyword(s):  
Permanent Magnet ◽  
Control Strategy ◽  
Adaptive Algorithm ◽  
Permanent Magnet Synchronous Motor ◽  
Regulation System ◽  
Speed Regulation ◽  
Adaptive Parameters ◽  
Regulation Strategies ◽  
Simulation Results ◽  
The Stability

To the speed-regulation system of permanent magnet synchronous motor (PMSM), this paper presents a active disturbances rejection controller (ADRC) based on the adaptive theory. First, the inertia information will be obtained by identification. Then, ADRC is designed by combining an adaptive algorithm. The controller can realize the adaptive parameters adjustment according to the inertia information, which is called adaptive ADRC. Simulation results have confirmed this control strategy can effectively improve the stability and robustness of PMSM.

scholarly journals Affine Projection Algorithm Using Regressive Estimated Error

2011 ◽  
Vol 2011 ◽  
pp. 1-5 ◽  
Author(s):  
Shu Zhang ◽  
Yongfeng Zhi
Keyword(s):  
Convergence Rate ◽  
Adaptive Filtering ◽  
Projection Algorithm ◽  
Error Signal ◽  
Affine Projection ◽  
Affine Projection Algorithm ◽  
Fast Convergence Rate ◽  
Simulation Results ◽  
The Stability ◽  
Estimated Error

An affine projection algorithm using regressive estimated error (APA-REE) is presented in this paper. By redefining the iterated error of the affine projection algorithm (APA), a new algorithm is obtained, and it improves the adaptive filtering convergence rate. We analyze the iterated error signal and the stability for the APA-REE algorithm. The steady-state weights of the APA-REE algorithm are proved to be unbiased and consist. The simulation results show that the proposed algorithm has a fast convergence rate compared with the APA algorithm.

scholarly journals Experimental and simulated milling stability tests

Mechanik ◽  
2017 ◽  
Vol 90 (11) ◽  
pp. 965-967
Author(s):  
Piotr Andrzej Bąk ◽  
Krzysztof Jemielniak
Keyword(s):  
Numerical Simulation ◽  
Stability Analysis ◽  
Time Domain ◽  
Cutting Parameters ◽  
Milling Machine ◽  
Machined Surface ◽  
Simulation Results ◽  
The Stability ◽  
The Time Domain

Self-excited vibrations significantly reduce the milling productivity, deteriorate the quality of machined surface and tool life. One of the ways to avoid these vibrations is to modify the cutting parameters based on the stability analysis results. A method of numerical simulation of self-excited vibrations in the time domain can be used for this purpose. A comparison of numerical simulation results with those from experiments conducted using a milling machine is presented. The results confirm the correctness of applied modeling.

scholarly journals An Improved Strong Tracking Kalman Filter Algorithm for the Initial Alignment of the Shearer

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-12 ◽  
Author(s):  
Yuming Chen ◽  
Wei Li ◽  
Gaifang Xin ◽  
Hai Yang ◽  
Ting Xia
Keyword(s):  
Kalman Filter ◽  
Adaptive Filtering ◽  
Alignment Algorithm ◽  
Forgetting Factor ◽  
Initial Alignment ◽  
Simulation And Experiment ◽  
Noise Covariance ◽  
Kalman Filter Algorithm ◽  
Fading Factor ◽  
Sequential Filter

The strap-down inertial navigation system (SINS) is a commonly used sensor for autonomous underground navigation, which can be used for shearer positioning under a coal mine. During the process of initial alignment, inaccurate or time-varying noise covariance matrices will significantly degrade the accuracy of the initial alignment of the shearer. To overcome the performance degradation of the existing initial alignment algorithm under complex underground environment, a novel adaptive filtering algorithm is proposed by the integration of the strong tracking Kalman filter and the sequential filter for the initial alignment of the shearer with complex underground environment. Compared with the traditional multiple fading factor strong tracking Kalman filter (MSTKF) method, the proposed MSTSKF algorithm integrates the advantage of strong tracking Kalman filter and sequential filter, and multiple fading factor and forgetting factor for east and north velocity measurement are designed in the algorithm, respectively, which can effectively weaken the coupling relationship between the different states and increase strong robustness against process uncertainties. The simulation and experiment results show that the proposed MSTSKF method has better initial alignment accuracy and robustness than existing strong tracking Kalman filter algorithm.

scholarly journals Some New Trajectory Patterns and Periodic Behaviors of Unstable Second-Order Digital Filter with Two's Complement Arithmetic

2003 ◽  
Vol 13 (08) ◽  
pp. 2361-2368 ◽  
Author(s):  
Wing-Kuen Ling ◽  
Kwong-Shum Tam
Keyword(s):  
Periodic Orbit ◽  
Digital Filter ◽  
State Vector ◽  
Initial Conditions ◽  
Second Order ◽  
The State ◽  
Simulation Results ◽  
The Stability ◽  
Straight Lines

This Letter shows some counter-intuitive simulation results that for some filter parameters in the extended boundaries of the stability triangle, the state vector will converge to a periodic orbit after some iterations, no matter what the initial conditions. Also, a new pattern, which looks like a rotated letter "X", is found. The center of the rotated letter is located at the origin and the slopes of the "straight lines" of the rotated letter are equal to the values of the pole locations.

Improved Current Statistic Model and Adaptive Filtering

2005 ◽  
Author(s):  
Hongtao Hu ◽  
Zhongliang Jing
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Statistical Model ◽  
Adaptive Filtering ◽  
Adaptive Algorithm ◽  
Tracking Algorithm ◽  
Unscented Transformation ◽  
Maneuvering Targets ◽  
Statistic Model ◽  
Simulation Results

Current statistical model needs to pre-define the value of maximum accelerations of maneuvering targets. So it may be difficult to meet all maneuvering conditions. In this paper a novel adaptive algorithm for tracking maneuvering targets is proposed. The algorithm is implemented with fuzzy-controlled current statistic model adaptive filtering and unscented transformation. The Monte Carlo simulation results show that this method outperforms the conventional tracking algorithm based on current statistical model.

Shimmy model for electric vehicle with independent suspensions

2017 ◽  
Vol 232 (3) ◽  
pp. 330-340 ◽  
Author(s):  
Tian Mi ◽  
Gabor Stepan ◽  
Denes Takacs ◽  
Nan Chen
Keyword(s):  
Electric Vehicle ◽  
Degrees Of Freedom ◽  
Initial Conditions ◽  
Structural Parameters ◽  
Contact Point ◽  
Dynamic Responses ◽  
Simulation Results ◽  
The Stability ◽  
Linearized Model ◽  
Wheel Shimmy

A 5-degrees-of-freedom shimmy model is established to analyse the dynamic responses of an electric vehicle with independent suspensions. Tyre elasticity is considered by means of Pacejka’s magic formula. Under the nonslip assumption for the leading contact point, tyre–road constraint equations are derived. Numerical simulation is conducted with different structural parameters and initial conditions to observe the shimmy phenomenon. Simulation results indicate that Hopf bifurcation occurs at a certain vehicle forward speed. Moreover, suspension structural parameters, such as caster angle, affect wheel shimmy. The linearized model of the system presents the stability boundaries, which agree with the simulation results. The results of this study not only provide a theoretical reference for shimmy attenuation, but also validate the effectiveness of the provided model, which can be used in further dynamic analysis of vehicle shimmy.

Research on the White Noise Suppression by Adaptive Filtering of Genetic Algorithm

2012 ◽  
Vol 155-156 ◽  
pp. 989-994 ◽  
Author(s):  
Xiao Rong Tong
Keyword(s):  
Genetic Algorithm ◽  
White Noise ◽  
Adaptive Filtering ◽  
Adaptive Filter ◽  
Noise Suppression ◽  
Signal Transmission ◽  
Weight Vector ◽  
Mean Filter ◽  
The Mean ◽  
Simulation Results

Signal transmission is often subject to the disturbance of white noise. Owing to the spectrum of white noise can be found in the real number field, it is often difficult to filter out with the traditional filter. This article describes the methods of white noise suppression using adaptive filter and mean filter. First, using the genetic algorithm to optimize the weight vector of the adaptive filter, and then using the method of the mean filter to further filter, Simulation results show that the filter can effectively suppress white noise.

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