Article
Automation & Control Systems
Wenzhao Yu, Haixiang Xu, Xin Han, Yahao Chen, Mengfei Zhu
Summary: A new fault-tolerant control method based on the neural modified extended state observer is proposed for dynamic positioning vessel with thruster faults. By accurately estimating total uncertainties and establishing a feedback controller, effective fault-tolerant control is achieved, with simulation results showing superior performance.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Engineering, Marine
Ming-Yang Li, Long-Tao Liu, Wen-Bo Xie, Ji-Tao Li
Summary: This paper proposes a collision avoidance fault-tolerant control scheme for dynamic positioning vessels, considering velocity constraints and thruster faults. It integrates the collision avoidance problem as a security zone constraint using an artificial potential function. An indirect error vector is constructed, incorporating the gradient of potential function and vessel velocity information, to ensure the satisfaction of velocity constraints. The derived controller provides robustness against unknown parameters affections, ocean disturbances, and thruster faults, while maintaining a simple structure and inexpensive online computations for real-time implementation.
Article
Engineering, Marine
Zhifu Li, Ming Wang, Ge Ma, Tao Zou
Summary: This paper proposes a reinforcement learning (RL) fault-tolerant control (FTC) method for trajectory tracking of autonomous underwater vehicles (AUVs) with thruster faults. To handle the thruster fault, unknown disturbance, and model uncertainty, a new integral extended state observer (IESO) is proposed for fault diagnosis observation. Based on the actor-critic structure of RL, a PD-like feedback controller is designed to realize the FTC of AUVs in the face of thruster fault. The proposed method is verified to have good fault tolerance and robustness through simulation and underwater experiments.
Article
Engineering, Marine
Dongdong Mu, Yupei Feng, Guofeng Wang, Yunsheng Fan, Yongsheng Zhao, Xiaojie Sun
Summary: This study investigates the position-constrained ship dynamic positioning output feedback control, taking into account the thruster system dynamics, in order to address the limitations of ship operating area, unknown time-varying disturbances, immeasurable ship speed, unknown dynamics, and input saturation. A barrier Lyapunov function is used to restrict ship position and limit position error. The set total disturbance is estimated using a fixed-time extended state observer, and the thruster system dynamics equations are incorporated into the controller design process. A robust control term is introduced to handle errors in the controller design, and the stability proof demonstrates the effectiveness of the proposed control strategy in achieving desired ship location and maintaining the ship within the operating area.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2023)
Article
Automation & Control Systems
Yongyi Lin, Jialu Du, Jian Li
Summary: This paper presents a novel robust adaptive finite-time fault-tolerant control scheme for dynamic positioning of vessels, addressing thruster faults, unknown model parameters, and environmental disturbances. By incorporating finite-time control technique, neural networks technique, and sliding mode differentiator, the proposed FTC strategy ensures the vessel reaches the desired position and heading in finite time while maintaining the boundedness of all signals in the closed-loop system. Simulation results demonstrate the effectiveness of the proposed FTC scheme.
INTERNATIONAL JOURNAL OF CONTROL AUTOMATION AND SYSTEMS
(2021)
Article
Automation & Control Systems
Haili Chen, Hongxiang Ren, Zongjiang Gao, Feng Yu, Wei Guan, Delong Wang
Summary: This study introduces a novel dynamic positioning scheme for ships, addressing unknown environmental disturbances and thruster faults. The proposed scheme demonstrates higher convergence rate and robustness, integrating finite-time disturbance observer and thruster fault-tolerant control for superior overall performance.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Engineering, Marine
Alireza Hosseinnajad, Mehdi Loueipour
Summary: This paper presents a novel fault tolerant control system for remotely operated vehicles, which considers unknown system dynamics and unknown thruster faults and failures while accounting for magnitude and rate limits of the thrusters. The proposed control system consists of a novel integral sliding mode control (ISMC) and a new state and fault observer. Simulations show the superior performance of the proposed control system in terms of positioning accuracy and fault tolerance.
Article
Computer Science, Artificial Intelligence
Haibin Sun, Jierong Shi, Linlin Hou
Summary: An adaptive event-triggered observer-based output feedback control method is proposed to enhance the anti-disturbance and reliability performance of unmanned surface vehicles in the presence of actuator faults and external disturbances. A Takagi-Sugeno fuzzy system is established considering the unknown disturbances and actuator faults. An adaptive event-triggered mechanism is designed to construct state and disturbance observers based on the output of the event generator. The developed adaptive event-triggered observer-based output feedback dynamic positioning controller ensures asymptotical stability with H-8 performance, as proved by the Lyapunov function method. The advantages of the proposed method are demonstrated through an example.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Engineering, Marine
Alireza Hosseinnajad, Navid Mohajer, Saeid Nahavandi
Summary: This paper proposes a novel Barrier Lyapunov Function (BLF)-based fault tolerant control system for a work-class Remotely-Operated Vehicle (ROV) with thruster saturation and rate limits. The proposed control system is composed of a fixed-time state and fault observer, and a novel BLF-based backstepping controller. Simulations confirm the superior performance of the proposed control system.
Article
Computer Science, Artificial Intelligence
Chujian Zeng, Bo Zhao, Derong Liu
Summary: This paper proposes a neuro-dynamic programming-based fault tolerant control scheme for a class of nonlinear systems, considering the occurrence of both actuator and sensor faults simultaneously. The scheme combines a descriptor observer with an adaptive observer to estimate system states and multiple faults. By employing a critic neural network, the approximate optimal control policy is obtained for the fault-free system. An FTC law is developed to suppress the influence of actuator faults by combining the estimations of actuator faults with the approximate optimal control policy. The stability of the closed-loop nonlinear system is analyzed using the Lyapunov stability theorem.
Article
Engineering, Marine
Xiaofeng Liu, Mingjun Zhang, Xing Liu, Wende Zhao
Summary: This paper proposes a fault-tolerant control method based on FTESO and FTC for multiple-thruster AUVs to address issues such as current disturbances, thruster faults, and modelling uncertainty, effectively reducing energy consumption and improving tracking accuracy.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Bin Guo, Songyi Dian, Tao Zhao, Xingming Wang
Summary: This article investigates the fault-attack control problem for wheeled mobile robot systems. It proposes an event-observer based compensation controller to achieve tracking control performance. The article establishes a dynamic model for the robot system with actuator faults, disturbances, and attacks, and presents an event-based proportional-integral observer (PIO) for state estimation and fault compensation. The article also considers communication efficiency by constructing a dynamic event condition and adaptive trigger scheme.
Article
Automation & Control Systems
Xingxing Hua, Xin Dai, Shaoxin Sun, Yue Sun
Summary: In this paper, a novel fault-tolerant control scheme is proposed for multi-agent systems with various uncertainties. The proposed scheme is capable of estimating incipient faults, dealing with disturbances, and compensating for parameter uncertainties, time delay, and nonlinear terms. Simulation results demonstrate the effectiveness of the proposed technique in practical systems.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Xiaoyang Gao, Yue Long, Tieshan Li, Xin Hu, C. L. Philip Chen, Fuchun Sun
Summary: This article discusses the problem of optimal fuzzy output-feedback tracking control for dynamic positioning of marine vessels in the presence of uncertainties, disturbances, unavailable velocities, and thruster saturations. The proposed control scheme integrates a fuzzy velocity observer, a finite-time disturbance observer, a dynamic auxiliary system, and an optimal control strategy with dynamic surface control. Simulation results demonstrate the effectiveness of the proposed optimal control scheme.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Engineering, Marine
Ziwen Yu, Xinjiang Wei, Huifeng Zhang, Xin Hu, Jian Han
Summary: This study investigates the anti-disturbance control problem for ship dynamic positioning systems with model uncertainties and ocean disturbances under thruster faults. A stochastic disturbance observer (SDO) is established to estimate the ocean disturbance online. An adaptive law is used for evaluating thruster faults, which is obtained from Lyapunov function. A robust control term with adaptive technology is employed to attenuate the model uncertainties. Then, a composite anti-disturbance control (CADC) strategy is proposed by combining disturbance observer-based control (DOBC), adaptive technology, and robust control term, which achieves the desired position and yaw angle of the ship. The simulation example confirms the validity of the controller.
PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART M-JOURNAL OF ENGINEERING FOR THE MARITIME ENVIRONMENT
(2023)
Article
Automation & Control Systems
Ning Tian, Huazhen Fang, Yebin Wang
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2019)
Article
Automation & Control Systems
Quan Ouyang, Jian Chen, Jian Zheng, Huazhen Fang
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2018)
Article
Green & Sustainable Science & Technology
Quan Ouyang, Jian Chen, Jian Zheng, Huazhen Fang
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2018)
Article
Automation & Control Systems
Tao Yang, Di Wu, Huazhen Fang, Wei Ren, Hong Wang, Yiguang Hong, Karl Henrik Johansson
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2019)
Article
Automation & Control Systems
Ning Tian, Huazhen Fang, Jian Chen, Yebin Wang
Summary: This article introduces a new equivalent circuit model for rechargeable batteries by modifying an existing double-capacitor model, incorporating a nonlinear-mapping-based voltage source and serial RC circuit to better represent battery nonlinear phenomena. Two offline parameter estimation approaches, 1.0 and 2.0, are designed for constant-current and variable-current charging/discharging scenarios. The proposed model demonstrates excellent accuracy and predictive capability in extensive experimental evaluation, surpassing the Rint and Thevenin models in accuracy and complexity.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2021)
Article
Automation & Control Systems
Hang Geng, Mulugeta A. Haile, Huazhen Fang
Summary: This article introduces a new method (SSUE) that can simultaneously estimate the internal state and parameter uncertainty of a system to address the challenge of parameter variability in practical dynamic systems. By developing a Bayesian framework and numerical methods, the estimation of parameter uncertainty and the update of the state vector are achieved, while observability analysis is conducted to assess consistency.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2021)
Article
Automation & Control Systems
Ning Tian, Huazhen Fang, Yebin Wang
Summary: The article proposes a real-time charging control framework based on explicit MPC, which shifts constrained optimization offline and expresses charging law as piecewise affine functions, reducing online computational costs and coding difficulty. Extensive numerical simulation and experimental results verify the effectiveness of the proposed eMPC charging control framework and algorithm. This research has the potential to meet the needs for real-time battery management running on embedded hardware.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2021)
Article
Automation & Control Systems
Quan Ouyang, Guotuan Xu, Huazhen Fang, Zhisheng Wang
Summary: This article introduces a integrated battery pack charging system to solve cell imbalance issue and proposes a fast charging control method to optimize the current provided by charger and equalizing currents. The designed strategy demonstrates superior performance through extensive simulation and experimental results.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2021)
Article
Automation & Control Systems
Hamidreza Movahedi, Ning Tian, Huazhen Fang, Rajesh Rajamani
Summary: This article presents a method for estimating the state-of-charge (SoC) of a lithium-ion battery using a nonlinear double-capacitor model. The model incorporates a nonlinear function to capture the voltage hysteresis phenomenon associated with the SoC. A modified Preisach model is used to represent the hysteresis term, and a nonlinear observer is designed using Lyapunov analysis to ensure stability. Experimental data is used to evaluate the observer's performance, and it is found to outperform other filters, such as the extended Kalman filter and the unscented Kalman filter. The key technical contribution of this article is the development of an observer design method for handling hysteresis in nonlinear systems.
IEEE-ASME TRANSACTIONS ON MECHATRONICS
(2022)
Article
Automation & Control Systems
Huazhen Fang, Mulugeta A. Haile, Yebin Wang
Summary: This paper introduces an innovative saturation mechanism to make the Extended Kalman Filter robust against outliers, leading to the development of robust EKF approaches for both continuous- and discrete-time systems. The proposed approaches demonstrate the capability to reject outliers of various magnitudes, types, and durations at significant computational efficiency without requiring additional measurement redundancy.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2022)
Article
Automation & Control Systems
Chuan Yan, Tao Yang, Huazhen Fang
Summary: This article investigates control design for high-order leader-follower multi-agent systems where only the first state of an agent is measured. By developing distributed observers, followers are able to reconstruct the unmeasured or unknown quantities about themselves and the leader, and observer-based tracking control approaches are built on this basis. The proposed approaches' convergence properties are analyzed and their performance is validated through simulation.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2022)
Article
Energy & Fuels
Hao Tu, Scott Moura, Yebin Wang, Huazhen Fang
Summary: This paper proposes two new frameworks that integrate physics-based models with machine learning to achieve high-precision modeling for lithium-ion batteries. The models have been extensively tested and proven to provide accurate voltage predictions.
Article
Automation & Control Systems
Yangsheng Hu, Raymond A. de Callafon, Ning Tian, Huazhen Fang
Summary: Accurate battery modeling is crucial for optimizing battery performance. This article presents a tensor network-based Volterra double-capacitor model for lithium-ion batteries, which improves prediction accuracy compared to traditional models. Experimental results demonstrate that the proposed model outperforms existing models, making it a promising tool for future battery applications.
IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY
(2023)
Article
Automation & Control Systems
Kunwu Zhang, Yang Shi, Stamatis Karnouskos, Thilo Sauter, Huazhen Fang, Armando Walter Colombo
Summary: Industrial cyber-physical systems (ICPS) have gained increasing attention due to their potential benefits to society, economy, environment, and citizens. This article provides an overview of ICPS, including its architecture, developments, and future research directions.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Editorial Material
Automation & Control Systems
Yang Shi, Stamatis Karnouskos, Thilo Sauter, Huazhen Fang
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Engineering, Ocean
Canjun Yang, Dingze Wu, Puzhe Zhou, Shuyang Ma, Rui Zhou, Xin Zhang, Yang Zhang, Qingchao Xia, Zeliang Wu
Summary: The Argo Global Ocean Observing Network is the preeminent ocean observation network worldwide, but its buoys fail to complete long-term observations in designated sea areas due to their lack of lateral movement. To solve this problem, a portable underwater profiler (PUP) that combines buoy and underwater glider functionalities was developed. The PUP is lightweight, allows for rapid deployment, and enables continuous observation.
APPLIED OCEAN RESEARCH
(2024)
Article
Engineering, Ocean
Knut Andreas Kvale, Bernt Leira, Ole Oiseth
Summary: As future floating bridges become longer, the chance of encountering significant inhomogeneous wave conditions increases. This paper presents an approach to model these conditions using generalized harmonic decomposition and applies it to a conceptual floating bridge model in Norway. The paper focuses on frequency-domain simulation and highlights the importance of considering the coherency in swell sea conditions.
APPLIED OCEAN RESEARCH
(2024)
