Article
Engineering, Mechanical
Antonio Leanza, Giacomo Mantriota, Giulio Reina
Summary: Accurate knowledge of vehicle dynamics response is crucial for improving handling performance and ensuring safe driving. However, due to cost and technological limitations, not all quantities of interest can be directly measured. Model-based estimation methods, such as Kalman Filtering (KF), have been developed to map the relationship between uncertain quantities and measurable variables. This paper compares models of varying fidelity and KF-based estimators to guide the construction of a model-based observer. Nonlinear estimation algorithms, including the Unscented Kalman Filter (UKF) and Cubature Kalman Filter (CKF), are contrasted with the standard Extended Kalman Filter (EKF) using experimental data from a public dataset.
VEHICLE SYSTEM DYNAMICS
(2023)
Article
Engineering, Aerospace
Kevin R. Ford, Anton J. Haug
Summary: This article introduces a new filter that combines a modified version of the EPC with a multiple-model algorithm to achieve superior performance against a wider range of ASCM trajectories than the EPC EKF.
IEEE TRANSACTIONS ON AEROSPACE AND ELECTRONIC SYSTEMS
(2021)
Article
Mechanics
Elvis Villano, Basilio Lenzo, Aleksandr Sakhnevych
Summary: A novel method for estimating vehicle sideslip angle is proposed in this paper, utilizing a combination of kinematic and dynamic approaches with cross-feedback, and validated on experimental data obtained from different race tracks. The method shows promising results in improving both sideslip angle estimation accuracy and vehicle longitudinal velocity estimation compared to current state-of-the-art techniques.
Article
Automation & Control Systems
Pan Wang, Xiaobin Fan, Xinbo Chen, Juean Yi, Shuwen He
Summary: In this study, a four-wheel motor driven electric vehicle is taken as the research object to study the estimation problem of the sideslip angle in the vehicle's nonlinear state. An Unscented Kalman Filter (UKF) estimation method is proposed to reduce observation error and improve the practicability of the estimation system. The effectiveness of the algorithm is verified by comparing with the Extended Kalman Filter (EKF) algorithm and conducting real vehicle road tests.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2023)
Article
Automation & Control Systems
Emir Hrustic, Rayen Ben Abdallah, Jordi Vila-Valls, Damien Vivet, Gael Pages, Eric Chaumette
Summary: This paper discusses the use of linearly constrained KF for robust nonlinear filtering under mismatched process and measurement models, introducing a new linearly constrained extended KF (LCEKF) for mitigating parametric modeling errors. The performance improvement of the new LCEKF for robust vehicle navigation is demonstrated through numerical results.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Chemistry, Analytical
Antonio Leanza, Giulio Reina, Jose-Luis Blanco-Claraco
Summary: The study proposed a novel approach to model vehicle dynamics directly as a graphical model, which can accurately estimate and monitor sideslip angle, with a flexible mathematical framework and greater potential for future extensions.
Article
Computer Science, Information Systems
Dongchan Kim, Gihoon Kim, Seungwon Choi, Kunsoo Huh
Summary: The proposed integration scheme combines a deep neural network and a kinematics-based model in an unscented Kalman filter for sideslip angle estimation. The deep neural network includes two modules, both utilizing recurrent neural networks to analyze sequential sensor data and reduce noise and bias to match the model for the unscented Kalman filter. The algorithm was verified through simulation and experiment, showing the effectiveness of the approach.
Article
Chemistry, Multidisciplinary
Yafei Li, Yiyong Yang, Xiangyu Wang, Yongtao Zhao, Chengbiao Wang
Summary: This study proposes a state observer based on the EKF method to estimate the vehicle sideslip angle using steering torque instead of steering angle. Transfer functions between the sideslip angle-steering torque and sideslip angle-steering angle are established, and the analysis shows that the steering torque signal reacts more rapidly and directly due to hydraulic pressure. Finally, the proposed method is validated through a simulation hardware-in-the-loop bench test, showing accurate reflection of the sideslip angle with good reliability and effectiveness.
APPLIED SCIENCES-BASEL
(2023)
Article
Automation & Control Systems
Dasol Jeong, Geonhee Ko, Seibum B. Choi
Summary: This paper proposes a constrained lateral dynamics model of articulated vehicles and an algorithm for estimating sideslip angle and cornering stiffness. The articulated vehicle is modeled using the bicycle model, linear tire model, and modified Dug-off model, with the estimation of normal force on each axle based on the longitudinal load transfer model. Accurate sideslip angle and cornering stiffness are crucial for vehicle control safety and autonomous driving performance. The dual linear time-varying Kalman filter is used to simultaneously estimate the sideslip angle and cornering stiffness, with the observability matrix ensuring the convergence of the estimation algorithm. The estimation performance is verified through simulation and experimental validation.
Article
Engineering, Geological
Xingyu Li, Chaodong Zhang, Yue Zheng, Ning Zhang
Summary: This study proposes a novel constrained unscented Kalman filter (UKF) method for updating structural parameters and identifying unknown external excitations in strongly nonlinear structures. The unknown excitation is estimated by a recursive nonlinear least-square algorithm, while a specially developed Matlab-OpenSees recursion platform is used to implement the algorithm. The applicability of the method is verified through investigations on a steel frame and a reinforced concrete bridge.
SOIL DYNAMICS AND EARTHQUAKE ENGINEERING
(2022)
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
Engineering, Aerospace
Xiaohua Li, Bo Lu, Wasiq Ali, Jun Su, Haiyan Jin
Summary: The paper introduces a probabilistic multiple hypothesis tracker (PMHT) algorithm based on batch recursive extended Rauch-Tung-Striebel smoother (RTSS) to effectively handle the nonlinearity in passive Doppler and bearing measurements in multiple-target tracking.
INTERNATIONAL JOURNAL OF AEROSPACE ENGINEERING
(2021)
Article
Engineering, Marine
Fei Deng, Carlos Levi, Hongdong Yin, Menglan Duan
Summary: The study proposes an optimized UKF algorithm to improve the estimation precision of hydrodynamic coefficients for an AUV, in combination with three KF algorithms for verification. The research enhances the adaptability and prediction performance of the identification approach and demonstrates the superior accuracy of OUKF compared to EKF and UKF in the presence of ARMA noisy model.
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
Construction & Building Technology
Andrea Calabrese, Salvatore Strano, Mario Terzo
STRUCTURAL CONTROL & HEALTH MONITORING
(2018)
Article
Automation & Control Systems
Gianluca Palli, Salvatore Strano, Mario Terzo
CONTROL ENGINEERING PRACTICE
(2018)
Article
Automation & Control Systems
Vincenzo Niola, Salvatore Strano, Mario Terzo
JOURNAL OF DYNAMIC SYSTEMS MEASUREMENT AND CONTROL-TRANSACTIONS OF THE ASME
(2018)
Article
Engineering, Mechanical
Salvatore Strano, Mario Terzo
MECHANICAL SYSTEMS AND SIGNAL PROCESSING
(2018)
Article
Engineering, Civil
A. Calabrese, M. Spizzuoco, S. Strano, M. Terzo
ENGINEERING STRUCTURES
(2019)
Article
Engineering, Electrical & Electronic
Daniel Garcia-Pozuelo, Oluremi Olatunbosun, Salvatore Strano, Mario Terzo
SENSORS AND ACTUATORS A-PHYSICAL
(2019)
Article
Engineering, Civil
Ingrid E. Madera Sierra, Daniele Losanno, Salvatore Strano, Johannio Marulanda, Peter Thomson
ENGINEERING STRUCTURES
(2019)
Article
Engineering, Mechanical
Daniel Garcia-Pozuelo, Oluremi Ayotunde Olatunbosun, Luigi Romano, Salvatore Strano, Mario Terzo, Ari J. Tuononen, Yi Xiong
VEHICLE SYSTEM DYNAMICS
(2019)
Review
Thermodynamics
Salvatore Strano, Mario Terzo
ADVANCES IN MECHANICAL ENGINEERING
(2019)
Article
Engineering, Mechanical
Luigi Romano, Aleksandr Sakhnevych, Salvatore Strano, Francesco Timpone
VEHICLE SYSTEM DYNAMICS
(2020)
Article
Engineering, Civil
A. Calabrese, D. Losanno, M. Spizzuoco, S. Strano, M. Terzo
ENGINEERING STRUCTURES
(2019)
Article
Mechanics
Luigi Romano, Aleksandr Sakhnevych, Salvatore Strano, Francesco Timpone
Article
Computer Science, Interdisciplinary Applications
Vincenzo Niola, Gianluca Palli, Salvatore Strano, Mario Terzo
COMPUTERS & STRUCTURES
(2019)
Article
Engineering, Electrical & Electronic
Giovanni Breglio, Andrea Irace, Lorenzo Pugliese, Michele Riccio, Michele Russo, Salvatore Strano, Mario Terzo
Article
Automation & Control Systems
Subhashis Nandy
Summary: This research focuses on the design and stability analysis of nonlinear controllers for an electrically driven marine cycloidal propeller, along with estimating various parameters using the Extended Kalman Filter. The controller is defined using an efficient physics-based model and is able to accurately process multiple control signals. The robustness of the controller is assessed using Monte Carlo simulation, and its performance is evaluated through validation investigations.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Lucas C. Borin, Guilherme Hollweg, Caio R. D. Osorio, Fernanda M. Carnielutti, Ricardo C. L. F. Oliveira, Vinicius F. Montagner
Summary: This work presents a new automated test-driven design procedure for robust and optimized current controllers applied to LCL-filtered grid-tied inverters. The design of control gains is guided by high-fidelity simulations and particle swarm optimization algorithm, considering various normal and abnormal operating conditions. The proposed design ensures superior performance compared with other current control designs.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Wei He, Xiang Wang, Mohammad Masoud Namazi, Wangping Zhou, Josep M. Guerrero
Summary: The main objective of this paper is to develop a reduced-order adaptive state observer for a large class of DC-DC converters with constant power load, in order to estimate their unavailable states and unknown parameter and achieve an output feedback control scheme. The observer is designed using a generalized parameter estimation based observer technique and dynamic regressor extension and mixing method. The comparison study shows that the observer has the advantage of verifying the observability of the systems for exponential convergence without any extra excitation condition.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Te Zhang, Bo Zhu, Lei Zhang, Qingrui Zhang, Tianjiang Hu
Summary: This paper introduces a control technique called time-varying uncertainty and disturbance estimator (TV-UDE) which extends the classic UDE approach to handle more complicated issues. By combining TV-UDE with a nominal dynamic output-feedback controller, robust control for uncertain second-order attitude control systems without velocity measurements is achieved. Numerical simulations and physical experiments on a 2-DOF AERO attitude helicopter platform demonstrate the effectiveness of the proposed design in reducing steady-state errors and avoiding issues caused by high-gain estimation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kanishke Gamagedara, Taeyoung Lee, Murray Snyder
Summary: This paper presents the developments of flight hardware and software for a multirotor unmanned aerial vehicle capable of autonomously taking off and landing on a moving vessel in ocean environments. The flight hardware consists of a general-purpose computing module connected to a low-cost inertial measurement unit, real-time kinematics GPS, motor speed controller, and a camera through a custom-made printed circuit board. The flight software is developed in C++ with multi-threading to execute control, estimation, and communication tasks simultaneously. The proposed flight system is verified through autonomous flight experiments on a research vessel in Chesapeake Bay, utilizing real-time kinematics GPS for relative positioning and vision-based autonomous flight for shipboard launch and landing.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yun Zhu, Kangkang Zhang, Yucai Zhu, Pengfei Jiang, Jinming Zhou
Summary: In this study, a three-term Dynamic Matrix Control (DMC) algorithm using quadratic programming is developed and compared with the traditional two-term DMC algorithm. Simulation studies and real-life tests show that the three-term DMC algorithm outperforms the two-term DMC algorithm in control effectiveness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Jayu Kim, Taehoon Lee, Cheol-Joong Kim, Kyongsu Yi
Summary: This paper presents a data-based model predictive control method for a semi-active suspension system. The method utilizes a continuous damping controller and a stiffness controller to improve ride comfort and reduce vehicle pitch motion. Gaussian process regression is also used to compensate for model parameter uncertainties. The algorithm has been verified through computer simulations and vehicle tests, demonstrating its effectiveness and robustness.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Kunpeng Zhang, Jikang Gao, Zongqi Xu, Hui Yang, Ming Jiang, Rui Liu
Summary: A improved dynamic programming model is proposed in this paper for joint operation optimization of virtual coupling of heavy-haul trains. By simultaneously optimizing the headway and energy savings, as well as performing locomotive engineering advisory analysis, significant improvements in train performance can be achieved.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Demian Garcia-Violini, Yerai Pena-Sanchez, Nicolas Faedo, Fernando Bianchi, John V. Ringwood
Summary: This study presents a model invalidation methodology for wave energy converters (WECs) that can effectively handle dynamic uncertainty and external noise. The results indicate that neglecting dynamic uncertainty can lead to overestimation of performance, highlighting the importance of accurate dynamic description for estimating control performance.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Shengyang Lu, Yue Jiang, Xiaojun Xu, Hanxiang Qian, Weijie Zhang
Summary: This paper proposes an adaptive heading tracking control strategy based on wheelbase changes for unmanned ground vehicles (UGVs) with variable configuration. The strategy adjusts the wheelbase according to different working conditions to optimize driving performance. The impact of changing wheelbase on sideslip angle and heading angle is analyzed, and a robust-active disturbance rejection control method is developed to achieve desired front-wheel steering angle. A torque distribution method based on tire load rate and real-time load is applied to enhance longitudinal stability.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Domenico Dona, Basilio Lenzo, Paolo Boscariol, Giulio Rosati
Summary: This paper proposes a new method for designing minimum energy trajectories for servo-actuated systems and demonstrates its accuracy and effectiveness through numerical comparisons and experimental validation.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Haolin Wang, Luyao Zhang, Yao Mao, Qiliang Bao
Summary: This paper proposes a method of transforming the core element of ADRC, ESO, into a novel fuzzy self-tuning observer structure to improve the stability of LOS in the electro-optical tracking system. It effectively solves the conflict between disturbance rejection ability and noise attenuation ability in traditional ESO.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Alejandro Toro-Ossaba, Juan C. Tejada, Santiago Rua, Juan David Nunez, Alejandro Pena
Summary: This work presents the development of a myoelectric Model Reference Adaptive Controller (MRAC) with an Adaptive Kalman Filter for controlling a cable driven soft elbow exoskeleton. The proposed MRAC controller is effective in both passive and active control modes, showing good adaptability and control capabilities.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Mehrad Jaloli, Marzia Cescon
Summary: This study presents an advanced multi-agent reinforcement learning (RL) strategy for personalized glucose regulation, which is shown to improve glucose regulation and reduce the risk of severe hyperglycemia compared to traditional therapy.
CONTROL ENGINEERING PRACTICE
(2024)
Article
Automation & Control Systems
Yingming Tian, Kenan Du, Jianfeng Qu, Li Feng, Yi Chai
Summary: This paper investigates the control strategy for PMSM with position sensor fault in railway. A learning observer-based control strategy is proposed, which achieves high-precision estimation of electromotive force and accelerates speed response.
CONTROL ENGINEERING PRACTICE
(2024)