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  • Open Access

    ARTICLE

    A New Estimation of Nonlinear Contact Forces of Railway Vehicle

    Khakoo Mal1,2, Imtiaz Hussain Kalwar3, Khurram Shaikh2, Tayab Din Memon2,4, Bhawani Shankar Chowdhry1, Kashif Nisar5,*, Manoj Gupta6

    Intelligent Automation & Soft Computing, Vol.28, No.3, pp. 823-841, 2021, DOI:10.32604/iasc.2021.016990

    Abstract

    The core part of any study of rolling stock behavior is the wheel-track interaction patch because the forces produced at the wheel-track interface govern the dynamic behavior of the whole railway vehicle. It is significant to know the nature of the contact force to design more effective vehicle dynamics control systems and condition monitoring systems. However, it is hard to find the status of this adhesion force due to its complexity, highly non-linear nature, and also affected with an unpredictable operation environment. The purpose of this paper is to develop a model-based estimation technique using the Extended Kalman Filter (EKF)… More >

  • Open Access

    ARTICLE

    Kernel Entropy Based Extended Kalman Filter for GPS Navigation Processing

    Dah-Jing Jwo*, Jui-Tao Lee

    CMC-Computers, Materials & Continua, Vol.68, No.1, pp. 857-876, 2021, DOI:10.32604/cmc.2021.016894

    Abstract This paper investigates the kernel entropy based extended Kalman filter (EKF) as the navigation processor for the Global Navigation Satellite Systems (GNSS), such as the Global Positioning System (GPS). The algorithm is effective for dealing with non-Gaussian errors or heavy-tailed (or impulsive) interference errors, such as the multipath. The kernel minimum error entropy (MEE) and maximum correntropy criterion (MCC) based filtering for satellite navigation system is involved for dealing with non-Gaussian errors or heavy-tailed interference errors or outliers of the GPS. The standard EKF method is derived based on minimization of mean square error (MSE) and is optimal only under… More >

  • Open Access

    ARTICLE

    Minimum Error Entropy Based EKF for GPS Code Tracking Loop

    Dah-Jing Jwo1,*, Jen-Hsien Lai2

    CMC-Computers, Materials & Continua, Vol.67, No.3, pp. 2883-2898, 2021, DOI:10.32604/cmc.2021.015102

    Abstract This paper investigates the minimum error entropy based extended Kalman filter (MEEKF) for multipath parameter estimation of the Global Positioning System (GPS). The extended Kalman filter (EKF) is designed to give a preliminary estimation of the state. The scheme is designed by introducing an additional term, which is tuned according to the higher order moment of the estimation error. The minimum error entropy criterion is introduced for updating the entropy of the innovation at each time step. According to the stochastic information gradient method, an optimal filer gain matrix is obtained. The mean square error criterion is limited to the… More >

  • Open Access

    ARTICLE

    Estimation Performance for the Cubature Particle Filter under Nonlinear/Non-Gaussian Environments

    Dah-Jing Jwo1,*, Chien-Hao Tseng2

    CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 1555-1575, 2021, DOI:10.32604/cmc.2021.014875

    Abstract This paper evaluates the state estimation performance for processing nonlinear/non-Gaussian systems using the cubature particle filter (CPF), which is an estimation algorithm that combines the cubature Kalman filter (CKF) and the particle filter (PF). The CPF is essentially a realization of PF where the third-degree cubature rule based on numerical integration method is adopted to approximate the proposal distribution. It is beneficial where the CKF is used to generate the importance density function in the PF framework for effectively resolving the nonlinear/non-Gaussian problems. Based on the spherical-radial transformation to generate an even number of equally weighted cubature points, the CKF… More >

  • Open Access

    ARTICLE

    Estimation of Quaternion Motion for GPS-Based Attitude Determination Using the Extended Kalman Filter

    Dah-Jing Jwo*

    CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2105-2126, 2021, DOI:10.32604/cmc.2020.014241

    Abstract In this paper, the Global Positioning System (GPS) interferometer provides the preliminarily computed quaternions, which are then employed as the measurement of the extended Kalman filter (EKF) for the attitude determination system. The estimated quaternion elements from the EKF output with noticeably improved precision can be converted to the Euler angles for navigation applications. The aim of the study is twofold. Firstly, the GPS-based computed quaternion vector is utilized to avoid the singularity problem. Secondly, the quaternion estimator based on the EKF is adopted to improve the estimation accuracy. Determination of the unknown baseline vector between the antennas sits at… More >

  • Open Access

    ARTICLE

    The Design of a TLD and Fuzzy-PID Controller Based on the Autonomous Tracking System for Quadrotor Drones

    Pi-Yun Chen, Guan-Yu Chen*

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 489-500, 2020, DOI:10.32604/iasc.2020.013925

    Abstract The objective of this paper is to design a new Quadrotor Autonomous Following System, and the main three contents are as follows: Object tracking, quadrotor attitude determination and the controller. The image tracking portion performs object detection and keeps tracking by way of the Tracking-Learning-Detection (TLD), and gets the information of the target motion estimation positions. The attitude determination of the Quadrotor has adopted the Inertial Navigation System and sensors of the accelerometer, gyroscope and electronic compass, etc. for retrieving the information. The Kalman filter is also utilized for estimating the current values in order to reduce external interference, improve… More >

  • Open Access

    ARTICLE

    Prediction and Abnormality Assertion on Emu Brake Pad Based on Multivariate Integrated Random Walk

    Hongsheng Su1,2,∗, Shuangshuang Wang1, Dengfei Wang2

    Computer Systems Science and Engineering, Vol.33, No.5, pp. 351-360, 2018, DOI:10.32604/csse.2018.33.351

    Abstract To better solve the issue with abnormal failure of electric motor unit (EMU) brake pad resulted from various random factors in the ever-changing operating environment, in this paper, a new evaluation method of performance prediction and abnormity decision is proposed based on the Multivariate integrated random walk (MIRW) model. In this method, the state space model of the EMU brake pad performance degradation is firstly established. And then based on the observed data, the brake pad performance degradation trend is extracted by the fixed interval forward - backward smoothing algorithm. Based on it, the future degradation state can be predicted… More >

  • Open Access

    ARTICLE

    Complementary Kalman Filter as a Baseline Vector Estimator for GPS-Based Attitude Determination

    Dah-Jing Jwo1, *

    CMC-Computers, Materials & Continua, Vol.65, No.2, pp. 993-1014, 2020, DOI:10.32604/cmc.2020.011592

    Abstract The Global Positioning System (GPS) offers the interferometer for attitude determination by processing the carrier phase observables. By using carrier phase observables, the relative positioning is obtained in centimeter level. GPS interferometry has been firstly used in precise static relative positioning, and thereafter in kinematic positioning. The carrier phase differential GPS based on interferometer principles can solve for the antenna baseline vector, defined as the vector between the antenna designated master and one of the slave antennas, connected to a rigid body. Determining the unknown baseline vectors between the antennas sits at the heart of GPS-based attitude determination. The conventional… More >

  • Open Access

    ARTICLE

    The SLAM Algorithm for Multiple Robots Based on Parameter Estimation

    MengYuan Chen1,2

    Intelligent Automation & Soft Computing, Vol.24, No.3, pp. 593-602, 2018, DOI:10.31209/2018.100000026

    Abstract With the increasing number of feature points of a map, the dimension of systematic observation is added gradually, which leads to the deviation of the volume points from the desired trajectory and significant errors on the state estimation. An Iterative Squared-Root Cubature Kalman Filter (ISR-CKF) algorithm proposed is aimed at improving the SR-CKF algorithm on the simultaneous localization and mapping (SLAM). By introducing the method of iterative updating, the sample points are re-determined by the estimated value and the square root factor, which keeps the distortion small in the highly nonlinear environment and improves the precision further. A robust tracking… More >

  • Open Access

    ARTICLE

    Robust Remaining Useful Life Estimation Based on an Improved Unscented Kalman Filtering Method

    Shenkun Zhao, Chao Jiang*, Zhe Zhang, Xiangyun Long

    CMES-Computer Modeling in Engineering & Sciences, Vol.123, No.3, pp. 1151-1173, 2020, DOI:10.32604/cmes.2020.08867

    Abstract In the Prognostics and Health Management (PHM), remaining useful life (RUL) is very important and utilized to ensure the reliability and safety of the operation of complex mechanical systems. Recently, unscented Kalman filtering (UKF) has been applied widely in the RUL estimation. For a degradation system, the relationship between its monitored measurements and its degradation states is assumed to be nonlinear in the conventional UKF. However, in some special degradation systems, their monitored measurements have a linear relation with their degradation states. For these special problems, it may bring estimation errors to use the UKF method directly. Besides, many uncertain… More >

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