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Adaptive control of a Flexible Manipulator With Unknown Hysteresis and Intermittent Actuator Faults

IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 148-158页

作者： Shouyan Chen Weitian He Zhijia Zhao Yun Feng Zhijie Liu Keum-Shik Hong School of Mechanical and Electrical Engineering Guangzhou University the School of Control Science and Engineering Shandong University IEEE the College of Electrical and Information Engineering Hunan University the National Engineering Research Center for Robot Visual Perception and Control Technology Hunan University the School of Intelligence Science and Technology University of Science and Technology Beijing (USTB) the Institute for Future the School of AutomationQingdao University the School of Mechanical Engineering Pusan National University

In this study, we consider a single-link flexible manipulator in the presence of an unknown Bouc-Wen type of hysteresis and intermittent actuator faults. First, an inverse hysteresis dynamics model is introduced, and then the control input is divided into an expected input and an error compensator. Second,a novel adaptive neural network-based control scheme is proposed to cancel the unknown input hysteresis. Subsequently,by modifying the adaptive laws and local control laws, a fault-tolerant control strategy is applied to address uncertain intermittent actuator faults in a flexible manipulator system. Through the direct Lyapunov theory, the proposed scheme allows the state errors to asymptotically converge to a specified interval. Finally,the effectiveness of the proposed scheme is verified through numerical simulations and experiments.

关键词： Adaptive control flexible manipulator intermittent actuator faults inverse hysteresis dynamics vibration control

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Trajectory tracking control for ships with fixed-time prescribed performance considering input saturation and dead zone

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ISA Transactions 2025年 161卷 155-165页

作者： Lei, Yunsong Zhang, Xianku Gao, Shihang Guo, Qiang Key Lab. of Marine Simulation and Control Navigation College Dalian Maritime University Dalian116026 China College of Electrical and Control Engineering Xi'an University Of Science And Technology Xian710054 China

To enable underactuated ships to achieve trajectory tracking under unknown external disturbances, model uncertainties, and actuator saturation and dead zone, a fixed-time prescribed performance trajectory tracking control method is designed. Firstly, the position tracking errors are constrained by designing the barrier Lyapunov function, and the prescribed performance function is set as the constraint boundary to address the issue of fixed constraint boundaries in traditional methods. Secondly, RBF neural networks are employed to estimate the model uncertainties, and adaptive laws are used to estimate the upper bound of the composite disturbances. Finally, the controller is designed by incorporating fixed-time convergence theory and further using fixed-time sliding mode surface in order to overcome the shortcomings of traditional control algorithms in terms of slow response and the use of finite-time convergence with respect to the initial state. Through Lyapunov stability analysis, it is proven that all signals in the closed-loop system are bounded, and the velocity tracking errors can achieve global fixed-time convergence. Simulation results demonstrate that the proposed control scheme enables underactuated ship to achieve trajectory tracking even in the presence of input saturation and dead zone. Statistical results show that the performance indicators of the proposed controller are significantly smaller than those of the first group in the comparative experiments, with a shorter settling time. Moreover, compared to traditional saturation handling methods, the input curves of the proposed controller are smoother and more aligned with practical engineering requirements. © 2025 International Society of Automation

关键词： Lyapunov functions

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Digital Twin Virtual-Real Synchronization for Aeroengine Gas Path System Based on Deep Reinforcement Learning

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IEEE Systems Journal 2025年第1期19卷 75-86页

作者： Xu, Changyi Huo, Yuming Shi, Chunkun Zhao, Ying Dalian University of Technology School of Control Science and Engineering Dalian116023 China Dalian Maritime University College of Marine Electrical Engineering Dalian116026 China

It is crucial to monitor the operational status of aeroengines by using the digital twin technology to realize virtual-real synchronization for the gas path system. The challenge is to accurately monitor deep parameters in real-time during synchronization, although existing digital twin technologies have made good progress in monitoring shallow parameters. This study proposes a virtual-real synchronization method for digital twins of an aeroengine gas path system (AGPS) based on deep reinforcement learning (RL). First, the parameters are divided into directly measurable parameters (DMP) and nondirectly measurable parameters (NDMP). Then, different algorithms are applied to different types of parameters. An unscented Kalman filtering algorithm is utilized to aid in the synchronization of the DMP. An RL approach is employed to train parameter inference models for the NDMP. By combining the two algorithms, synchronization between these two parameter classes is achieved. This method excels by integrating the NDMP into the virtual-real synchronization of the AGPS digital twin, concurrently reducing the inference time for this specific segment. Comparative experiments are conducted, and the results indicate an effective improvement in the accuracy of parameter inference with the proposed method. Simultaneously, it ensures real-time and robust parameter inference. © 2007-2012 IEEE.

关键词： Deep reinforcement learning

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Finite-time stability and stabilization for highly nonlinear stochastic Markov jump systems

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ISA Transactions 2025年 160卷 131-138页

作者： Zhong, Shiyu Zhang, Weihai The College of Intelligent Manufacturing and Control Engineering Shandong Institute of Petroleum and Chemical Technology Dongying257061 China The College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

The research on finite-time stability (FTS) mainly focuses on linear and nonlinear systems, however, there are few studies on such problems for highly nonlinear systems. At present, most studies on FTS use the Lyapunov function method, and most of the results not only require the Lyapunov function in different modes to have the same feature, but also require the diffusion operators in different modes to be constrained by the same type of functions. This is somewhat restrictive to the selection of the Lyapunov function. Based on this, this paper concerns with FTS and asynchronous control of highly nonlinear stochastic Markov jump systems (HNSMJSs). Firstly, the criteria of mth moment finite-time stability (m-MFTS) for HNSMJSs in Lyapunov function form and parameter form are given and the asynchronous controller is provided to guarantee the mth moment finite-time stabilization (m-MFT stabilization). Moreover, HNSMJSs with deterministic time delay are extended to that with time-varying delay, and a more general result is given. Finally, three examples are provided to clarify the effectiveness of the proposed work. © 2025 International Society of Automation

关键词： Lyapunov functions

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Asymptotically Optimal Distributed control for Linear–Quadratic Mean Field Social Systems With Heterogeneous Agents

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IEEE Transactions on Automatic control 2025年第5期70卷 3197-3212页

作者： Liang, Yong Wang, Bing-Chang Zhang, Huanshui Shandong University School of Control Science and Engineering Jinan250061 China Shandong Normal University School of Information Science and Engineering Jinan250358 China Shandong University of Science and Technology College of Electrical Engineering and Automation Qingdao266590 China

The linear–quadratic mean field social control problem is studied in a large-population system with heterogeneous agents following the direct approach. A graph is introduced to represent the network topology of the large-population system, where nodes represent subpopulations called clusters and edges represent communication relationship. Agents in each cluster are homogeneous and coupled with each other through the global cluster mean field term, which is the stack of average state of agents in each cluster. First, under the centralized information pattern, we use variational analysis to obtain the necessary and sufficient conditions for the existence of optimal centralized open-loop controller characterized by a system of forward–backward stochastic differential equations (FBSDEs). Next, by tackling high-dimensional FBSDEs with two coupled low-dimensional Riccati equations, we construct the optimal centralized feedback controller, which composed of the individual state and the global cluster mean field term. Then, under the distributed information pattern, an asymptotically unbiased mean field estimator for each agent is designed to estimate the local cluster mean field terms according to the given network topology. Finally, a set of asymptotically optimal distributed controllers is proposed based on the mean field estimator and its asymptotically social optimality is further proved. A numerical simulation is conducted to demonstrate the effectiveness of the proposed distributed controller. © 1963-2012 IEEE.

关键词： Stochastic systems

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Data-driven output regulation control for constrained linear systems

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science China(Information sciences) 2025年第3期68卷 338-353页

作者： Chaoyu XIA Yi DONG Chaoli WANG Shengyuan XU Shanghai Research Institute for Intelligent Autonomous Systems Tongji University College of Electronic and Information Engineering Shanghai Research Institute for Intelligent Autonomous SystemsTongji University Department of Control Science and Engineering School of Optical-Electrical and Computer EngineeringUniversity of Shanghai for Science and Technology Department of Automation Nanjing University of Science and Technology

This study introduces a data-driven approach for state and output feedback control addressing the constrained output regulation problem in unknown linear discrete-time systems. Our method ensures effective tracking performance while satisfying the state and input constraints, even when system matrices are not available. We first establish a sufficient condition necessary for the existence of a solution pair to the regulator equation and propose a data-based approach to obtain the feedforward and feedback control gains for state feedback control using linear programming. Furthermore, we design a refined Luenberger observer to accurately estimate the system state, while keeping the estimation error within a predefined set. By combining output regulation theory, we develop an output feedback control strategy. The stability of the closed-loop system is rigorously proved to be asymptotically stable by further leveraging the concept of λ-contractive sets.

关键词： output regulation constrained system data-driven.

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Sensitivity Analysis of Multirelay Magnetic Coupling Wireless Power Transfer System

Sensitivity Analysis of Multirelay Magnetic Coupling Wireles...

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International Conference of electrical, Electronic and Networked Energy Systems, EENES 2024

作者： Xia, Hui Shi, Yong Hou, Xinyu College of Electrical and Control Engineering Shaanxi University of Science and Technology Xian710000 China

ISBN: (纸本)9789819620791

Capacitors inherently have manufacturing tolerances and are more susceptible to temperature, humidity, and aging. The output characteristic of the wireless power transfer system can be affected by the variations in resonant capacitors. A global sensitivity analysis of multirelay magnetic coupling wireless power transfer (MC-WPT) system is presented in this paper. The sensitivity of output current, transfer efficiency, and power factor to capacitor variations is analyzed based on the sobol’ method. The first-order indices are calculated to evaluated the effect of capacitance deviation on the system characteristics. It found that the output current and power factor are almost insensitivity to variations in capacitor of the receiving coil. Efficiency is almost insensitivity to variations in a capacitor of the transmitter coil, the sensitivity of efficiency to receiving coil capacitance is low, and the sensitivity of efficiency to relay coil capacitance is high. As an increase in the number of coils, the sensitivity of the multirelay WPT system to capacitance deviations decreases, and the robustness of the system increases. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Relay coil Sensitivity analysis Wireless power transfer

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Improving Power Response of Single-controllable VSG-Based Active Distribution Network

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 102-114页

作者： Shah Fahad Arman Goudarzi Pierluigi Siano Ji Xiang Department of Electrical and Computer Engineering Missouri University of Science and TechnologyUSA University of Victoria Canada Department of Management&Innovation Systems University of SalernoItaly Department of Electrical and Electronic Engineering Science University of JohannesburgJohannesburg2006South Africa National Laboratory of Industrial Control Technology College of Electrical EngineeringZhejiang UniversityHangzhou310058China

controlling an active distribution network(ADN)from a single PCC has been advantageous for improving the performance of coordinated Intermittent RESs(IRESs).Recent studies have proposed a constant PQ regulation approach at the PCC of ADNs using coordination of non-MPPT based ***,due to the intermittent nature of DGs coupled with PCC through uni-directional broadcast communication,the PCC becomes vulnerable to transient *** address this challenge,this study first presents a detailed mathematical model of an ADN from the perspective of PCC regulation to realize rigidness of PCC against ***,an H_(∞)controller is formulated and employed to achieve optimal performance against disturbances,consequently,ensuring the least oscillations during transients at ***,an eigenvalue analysis is presented to analyze convergence speed limitations of the newly derived system ***,simulation results show the proposed method offers superior performance as compared to the state-of-the-art methods.

关键词： Cooperative control of DGs hierarchical control system high penetration of intermittent RESs H_(∞)control optimal control in power systems single-controllable active distribution networks

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Multi-Context Aggregation Network With Foreground Correction for Automated Few-Shot Defect Segmentation

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IEEE Transactions on Automation science and engineering 2025年 22卷 13777-13787页

作者： Ma, Yunfeng Liu, Min Jiang, Shuai Wang, Xueping Bian, Yuan Wang, Yaonan Hunan University College of Electrical and Information Engineering Changsha410082 China National Engineering Research Center of Robot Visual Perception and Control Technology Hunan Changsha410082 China Hunan Normal University College of Information Science and Engineering Hunan Changsha410082 China

State-of-the-art defect segmentation methods rely on sufficient training data and struggle to generalize to unseen categories. Few-Shot Semantic Segmentation (FSS) is introduced to specifically address these issues. However, existing FSS models still face two challenges in the industry. 1) Defects usually present as weak features, resulting in incomplete segmentation;2) Severe background interference often leads to incorrect segmentation. To tackle these problems, we propose the Multi-Context Aggregation Network (MCANet). Specifically, we design a Cross-Layer Multi-Level Feature Aggregation Module (CMAM). CMAM effectively aggregates discretely distributed multi-level defect features across different layers and guides the query image to perceive defects from the pixel level, which avoids incomplete segmentation caused by weak features. Additionally, a Foreground Correction Module (FCM) is developed, which is equipped with a dedicated background predictor (BP) and a foreground corrector (FC). BP places more emphasis on learning features from backgrounds rather than defects. FC achieves efficient feature ensemble and further suppresses the backgrounds misidentified as defects in CMAM. They collaborate to prevent incorrect segmentation caused by background interference. Extensive experiments demonstrate the effectiveness of our method. We achieve state-of-the-art results on both FSSD-12, a public benchmark FSS dataset for strip steel, and FSS-AEB, an FSS dataset for aero-engine blades. Specifically, with 1/5 support images, we achieve 64.6%/65.6% mIoU on FSSD-12 and 55.0%/57.8% mIoU on FSS-AEB. Note to Practitioners—Surface defect segmentation has always been a hot topic in the industry. However, existing methods rely on sufficient training data and struggle to generalize to unseen categories, which significantly hinders the automation of defect segmentation. To address this problem, we propose MCANet for automated few-shot defect segmentation. It achieves effective seg

关键词： Semantic Segmentation

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A Zero-Sequence Current Analysis Approach for Rotating Machinery Fault Diagnosis of Induction Motor Drivetrain Based on Sparse Learning

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IEEE Transactions on Power Electronics 2025年第7期40卷 9800-9810页

作者： Liu, Zhao-Hua Long, Jun-Jie Wei, Hua-Liang Liu, Kan Zhang, Ying-Jie Li, Xiao-Hua Hunan University of Science and Technology School of Information and Electrical Engineering Xiangtan411201 China The University of Sheffield School of Electrical and Electronic Engineering Department of Automatic Control and Systems Engineering SheffieldS1 3JD United Kingdom Hunan University College of Mechanical and Vehicle Engineering Changsha410082 China Hunan University College of Computer Science and Electronic Engineering Changsha410082 China

Fault diagnosis of rotating machinery driven by induction motors has received increasing attention. Current diagnostic methods, which can be performed on existing inverters or current transformers of three-phase induction machines, have become a more economical and reliable alternative to vibration diagnostic methods. Existing references mainly focus on the stator current analysis of single-phase, but most single-phase current analysis methods utilize only a fraction of the total information accessible in the three-phase system. Field experience shows that zero-sequence current (ZSC) has more distinctive fault characteristics compared to single-phase current, and therefore it is better to use in mechanical fault detection and diagnostic tasks. This article proposes a novel sparse learning-based method for ZSC analysis for induction rotating motor drive fault diagnosis. First, it elaborates and compares the effectiveness of ZSC in revealing fault characteristics compared with single-phase current by analyzing the fault diagnosis mechanism of ZSC. In addition, the method proposes a correlation entropy-enhanced sparse learning method for the problem of high-frequency noise and interference in the ZSC signals, so as to enhance the learning of the features of the noise-containing signals. The diagnostic efficacy of the proposed method has been verified through experiments on two real datasets. © 1986-2012 IEEE.

关键词： Induction motors

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