Article
Automation & Control Systems
Li Li, Mingyang Fan, Yuanqing Xia, Cui Zhu
Summary: This paper focuses on distributed fusion estimation for a multi-sensor nonlinear stochastic system, proposing an event-trigger mechanism and unscented Kalman filters for fusion estimation. It establishes boundedness conditions for fusion estimation error covariance through a recursive algorithm and trigger threshold. An ideal compromise between communication rate and estimation performance is achieved.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Engineering, Electrical & Electronic
Feng Tian, Jianqiang Wang, Keqiang Li
Summary: This article proposes a strong tracking event-triggered unscented Kalman filter (STETUKF) that utilizes vehicle-to-vehicle communication to estimate the preceding vehicle state. By adjusting the event-triggered threshold, an ideal compromise can be achieved between the transmission rate and estimation accuracy.
IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY
(2023)
Review
Automation & Control Systems
Leandro P. F. Rodriguez, Jhovany A. Tupaz, Mabel C. Sanchez
Summary: The study introduces a sensor network design strategy using the Unscented Kalman Filter, addressing the tradeoff between cost and estimation precision. A novel procedure is proposed to calculate an upper bound for estimation error, resulting in an efficient sensor network design with global precision.
JOURNAL OF PROCESS CONTROL
(2021)
Article
Chemistry, Analytical
Ojonugwa Adukwu, Darci Odloak, Amir Muhammed Saad, Fuad Kassab Junior
Summary: The focus of this work is to extend nonlinear state estimation methods to gas-lifted systems. The study compared the performance of the extended Kalman filter (EKF), unscented Kalman filter (UKF), and particle filter (PF) in estimating the nonlinear states. It was found that UKF provided slightly better estimates than EKF, while PF performed the worst. The gas-lifted system exhibited casing heading instability, and the results showed that either EKF or UKF could be used for nonlinear state estimation, with UKF being preferred if computational cost is not considered.
Article
Automation & Control Systems
Chen Qian, Qingwei Chen, Yifei Wu, Jian Guo, Yang Gao
Summary: A novel M-estimation based sparse grid quadrature filter (MSGQF) is proposed to improve the robust performance of the nonlinear system. The MSGQF outperforms other filters when abnormal measurement values appear, providing significant performance improvement in the robustness of the nonlinear system.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2021)
Article
Biochemical Research Methods
Amir H. Abolmasoumi, Mohammad Mohammadian, Lamine Mili
Summary: This paper proposes a revised version of the GM-UKF for state estimation in GRNs with different deviations from assumptions. The GM-UKF outperforms other methods for all outlier types, while the H-8-UKF is appropriate for changes in noise powers.
IEEE-ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS
(2023)
Article
Engineering, Mechanical
Tianhao Yu, Zhiheng Wang, Jingfeng Wang
Summary: In this study, a novel iterative augmented unscented Kalman filter (IAUKF) is developed for simultaneous state-parameter-input estimation, overcoming the limitations of existing methods with improved computational efficiency.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2023)
Article
Chemistry, Physical
Chu Xu, Timothy Cleary, Daiwei Wang, Guoxing Li, Christopher Rahn, Donghai Wang, Rajesh Rajamani, Hosam K. Fathy
Summary: This article examines the problem of Lithium-Sulfur (Li-S) battery state estimation, using a physics-based model and mass conservation to simplify the estimation problem. The unscented Kalman filter achieves better low-plateau estimation accuracy when a reduced-order model is used, according to the observability analysis.
JOURNAL OF POWER SOURCES
(2021)
Article
Engineering, Aerospace
Marzieh Ghani, Nima Assadian, Renuganth Varatharajoo
Summary: This paper presents a novel approach to simultaneously estimate the attitude and deformation of a flexible satellite using only sun sensor and magnetometer measurements. The results show that the algorithm successfully estimates the deformation without the need for conventional sensors.
ADVANCES IN SPACE RESEARCH
(2022)
Article
Automation & Control Systems
Xiaoyuan Zheng, Hao Zhang, Zhuping Wang, Changzhu Zhang
Summary: This article investigates the problem of nonlinear system states estimation with multisensor stochastic scheduling. The unscented transformation (UT) technique is applied to solve the non-Gaussian property induced by the nonlinear transformation, and stochastic event-triggered mechanisms (SETMs) are proposed to reduce network transmission burden. The modified unscented Kalman filter is introduced under SETMs, with sufficient conditions provided to guarantee stabillities of error covariance and estimation error. Extensive examples, performance evaluation, and comparison with existing methods demonstrate the superiority of the proposed methods.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2022)
Article
Acoustics
Keyvan Karim Afshar, Ali Javadi
Summary: This paper presents an effective control method for stabilizing and tracking the trajectory of an electromagnetic levitation system using feedback linearization controller and Linear Quadratic Regulator (LQR), along with the utilization of a nonlinear observer and nonlinear Kalman filter to estimate the unmeasured states and system parameter. Simulation results demonstrate that the proposed method is efficient in stabilizing the levitated object and attenuating disturbance and uncertainty in the system.
JOURNAL OF SOUND AND VIBRATION
(2021)
Article
Computer Science, Information Systems
Dah-Jing Jwo, Chien-Hao Tseng
Summary: This paper evaluates the state estimation performance of processing nonlinear/non-Gaussian systems using the cubature particle filter (CPF), which combines the cubature Kalman filter (CKF) and the particle filter (PF). The CPF algorithm effectively resolves nonlinear/non-Gaussian problems by using the CKF to generate the importance density function. The CPF can achieve a maximum a posteriori probability estimate of the nonlinear system, improving estimation accuracy compared to other particle filter and Kalman filter based approaches.
CMC-COMPUTERS MATERIALS & CONTINUA
(2021)
Article
Engineering, Mechanical
Milad Roohi, Kalil Erazo, David Rosowsky, Eric M. Hernandez
Summary: This paper introduces a model-based observer for state estimation in nonlinear hysteretic structural systems, designed to be physically realizable as a nonlinear structural model and offer good performance in real-world applications.
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Engineering, Aerospace
Jingshuai Huang, Zhihui Li, Da Liu, Quanshun Yang, Jianwen Zhu
Summary: An adaptive method for state estimation is proposed in this paper to track a maneuvering hypersonic glide target with model uncertainties. The method models unknown aerodynamic accelerations as the Singer model with a small maneuver frequency. When the real motion mode deviates from the default model, the maneuver frequency is adaptively enlarged to reduce the model error. The proposed method shows stronger robustness and higher estimation accuracy than conventional methods in the presence of model uncertainties, with significantly less computation burden than the multiple-model method.
AEROSPACE SCIENCE AND TECHNOLOGY
(2023)
Article
Automation & Control Systems
Yan Wang, Chen Lv, Yongjun Yan, Pai Peng, Faan Wang, Liwei Xu, Guodong Yin
Summary: This article proposes an integrated scheme for estimating tire-road friction coefficient (TRFC) by combining a strong tracking unscented Kalman filter and an interactive multiple model unscented Kalman filter. Real-time experiments on a mass-produced vehicle demonstrate the feasibility and effectiveness of the proposed method. The results show that the proposed approach has better estimation accuracy than the existing ones under various driving scenarios.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2022)
Article
Engineering, Aerospace
Gaoge Hu, Shesheng Gao, Yongmin Zhong, Bingbing Gao, Aleksandar Subic
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
(2016)
Article
Engineering, Aerospace
Gaoge Hu, Shesheng Gao, Yongmin Zhong, Bingbing Gao, Aleksandar Subic
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART G-JOURNAL OF AEROSPACE ENGINEERING
(2016)
Article
Engineering, Aerospace
Yang Meng, Shesheng Gao, Yongmin Zhong, Gaoge Hu, Aleksandar Subic
Article
Statistics & Probability
Bingbing Gao, Shesheng Gao, Yongmin Zhong, Chengfan Gu
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
(2017)
Article
Biotechnology & Applied Microbiology
Xin Li, Yongmin Zhong, Julian Smith, Chengfan Gu
Article
Computer Science, Artificial Intelligence
Jinao Zhang, Yongmin Zhong, Julian Smith, Chengfan Gu
NEURAL COMPUTING & APPLICATIONS
(2019)
Article
Chemistry, Analytical
Jaehyun Shin, Yongmin Zhong, Denny Oetomo, Chengfan Gu
Article
Chemistry, Analytical
Bingbing Gao, Gaoge Hu, Shesheng Gao, Yongmin Zhong, Chengfan Gu
Article
Chemistry, Analytical
Zhaohui Gao, Dejun Mu, Yongmin Zhong, Chengfan Gu
Article
Chemistry, Analytical
Wenhui Wei, Shesheng Gao, Yongmin Zhong, Chengfan Gu, Gaoge Hu
Article
Chemistry, Analytical
Zhaohui Gao, Dejun Mu, Yongmin Zhong, Chengfan Gu
Article
Chemistry, Analytical
Bingbing Gao, Gaoge Hu, Xinhe Zhu, Yongmin Zhong
Article
Chemistry, Analytical
Tianyao Shen, Bijan Shirinzadeh, Yongmin Zhong, Julian Smith, Joshua Pinskier, Mohammadali Ghafarian
Article
Chemistry, Analytical
Taran Batty, Armin Ehrampoosh, Bijan Shirinzadeh, Yongmin Zhong, Julian Smith
Summary: This paper discusses a method to mitigate system communication time delays in robotic minimally invasive surgery, providing more accurate haptic feedback through environment estimation and force prediction. Experimental results show that the Hunt-Crossley force model performs better in providing accurate haptic feedback.
Article
Engineering, Mechanical
Yanhui Mao, Yongmin Zhong, Yi Gao, Yuelong Wang
Summary: This study introduces discrete wavelet transform to extract well drilling signals and effectively eliminate vibration and rotary noises through a hard threshold method, obtaining useful gravity attitude signals.