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From Static and Dynamic Perspectives:A Survey on Historical Data Benchmarks of control Performance Monitoring

IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 300-316页

作者： Pengyu Song Jie Wang Chunhui Zhao Biao Huang the State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University IEEE the Department of Chemical and Materials Engineering University of Alberta

In recent decades, control performance monitoring(CPM) has experienced remarkable progress in research and industrial applications. While CPM research has been investigated using various benchmarks, the historical data benchmark(HIS) has garnered the most attention due to its practicality and effectiveness. However, existing CPM reviews usually focus on the theoretical benchmark, and there is a lack of an in-depth review that thoroughly explores HIS-based methods. In this article, a comprehensive overview of HIS-based CPM is provided. First, we provide a novel static-dynamic perspective on data-level manifestations of control performance underlying typical controller capacities including regulation and servo: static and dynamic properties. The static property portrays time-independent variability in system output, and the dynamic property describes temporal behavior driven by closed-loop feedback. Accordingly,existing HIS-based CPM approaches and their intrinsic motivations are classified and analyzed from these two ***, two mainstream solutions for CPM methods are summarized, including static analysis and dynamic analysis,which match data-driven techniques with actual controlling behavior. Furthermore, this paper also points out various opportunities and challenges faced in CPM for modern industry and provides promising directions in the context of artificial intelligence for inspiring future research.

关键词： control performance monitoring (CPM) data-driven method historical data benchmark (HIS) industrial process performance index static and dynamic analysis

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Dynamic Event-Triggered Networked Adaptive Tracking control of Wind Turbine Systems

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 14371-14382页

作者： Chen, Jun Meng, Wenchao Gong, Yingjie Yang, Qinmin Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310000 China

This paper addresses the co-design problem of adaptive control for networked wind turbine systems that track the desired rotor speed while efficiently scheduling network communication. Unlike existing approaches, the proposed method integrates the control design and the communication considerations, ensuring asymptotic tracking of rotor speed under the generator torque saturation with significantly reduced communication load. Firstly, the communication scheme is developed using the dynamic event-triggering mechanism, which introduces the feedback signal in the sampling loop. Secondly, an auxiliary signal is designed to mitigate the negative effect of inevitable generator torque saturation, ensuring that the bounded controller asymptotically exits from saturation. Then, the adaptive torque controller is constructed with the compensation signals to guarantee asymptotic stability, and the measurement function for dynamic event-triggering is co-designed alongside the controller to regulate the sampling-induced error. Furthermore, the requirement for exact knowledge of the wind turbine systems is eliminated by utilizing an online approximator to learn the uncertain aerodynamics and parameters. Finally, it is theoretically proven that all the signals in the closed-loop system are bounded, and the rotor speed asymptotically tracks the reference rotor speed. The feasibility and advantages of the proposed method are demonstrated on the NREL 5-MW wind turbine using the high-fidelity OpenFAST simulation platform. © 2004-2012 IEEE.

关键词： Networked control systems

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Toward Universal controller: Performance-Aware Self-Optimizing Reinforcement Learning for Discrete-Time Systems With Uncontrollable Factors

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IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3249-3260页

作者： Zhang, Jianfeng Zhang, Haoran Zhao, Chunhui Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China

The industrial system usually contains not only controllable variables (CVs) but also uncontrollable variables (unCVs), e.g., weather conditions and friction. These unCVs have a direct impact on system control performance. Despite the success of current deep reinforcement learning (DRL) control algorithms, most of them neglect the impact of unCVs, which can cause the deterioration of control performance and instability of the system. To perceive and eliminate the impact of unCVs, a performance-aware self-optimizing universal controller (PASOUC) is designed in this article. The PASOUC aims at integrating the representation of unCVs and controller design to perceive and eliminate the impact of unCVs under different conditions, which goes beyond most existing control methods. Technically, a historical trajectory-inspired control performance perceptron is developed to perceive the impact of unCVs on system control performance under different conditions. Subsequently, a new performance-aware reward is designed to integrate the representation of unCVs and controller design while training the DRL controller. In addition, the domain randomization (DR) training strategy is employed to learn a universal control policy, which can access the approximate optimal trajectory under nonideal conditions. In this way, the impact of unCVs can be eliminated. To handle the low efficiency of the DR training, the policy improvement-policy proximal optimization (PI-PPO) is proposed to enhance the convergence speed of the DR training by performing explicit policy improvement. Finally, illustrative examples are presented to demonstrate the superiority of the proposed method. © 2013 IEEE.

关键词： Deep reinforcement learning

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Theoretical and Experimental Analysis of Nonlinear Large Tensile Deformation of Superelastic SMA-Based Honeycomb Structures

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Acta Mechanica Solida Sinica 2025年第1期38卷 45-64页

作者： Yahao Wang Wenjiong Chen Renjing Gao Shutian Liu State Key Laboratory of Structural Analysis for Industrial Equipment Dalian University of TechnologyDalian116024China

Honeycomb structures of shape memory alloy(SMA)have become one of the most promising materials for flexible skins of morphing aircraft due to their excellent mechanical ***,due to the nonlinear material and geometric large deformation,the SMA honeycomb exhibits significant and complex nonlinearity in the skin and there is a lack of relevant previous *** this paper,the nonlinear properties of the SMA honeycomb structure with arbitrary geometry are investigated for the first time for large deformation flexible skin applications by theoretical and experimental ***,a novel theoretical model of SMA honeycomb structure considering both material and geometric nonlinearity is proposed,and the corresponding calculation method of nonlinear governing equations is given based upon the shooting method and Runge–Kutta ***,the tensile behaviors of four kinds of SMA honeycomb structures,i.e.,U-type,V-type,cosine-type,and trapezoid-type,are analyzed and predicted by the proposed theoretical model and compared with the finite element analysis(FEA)***,the tensile experiments were carried out by stretching U-type and V-type honeycomb structures to a global strain of 60%and 40%,respectively,to perform large deformation analysis and verify the theoretical ***,experimental verification and finite element validation show that the curves of the theoretical model results,experimental results,and simulation results are in good agreement,illustrating the generalizability and accuracy of the proposed theoretical *** theoretical model and experimental investigations in this paper are considered to provide an effective foundation for analyzing and predicting the mechanical behavior of SMA honeycomb flexible skins with large extensional deformations.

关键词： Morphing wing Flexible skin Large deformation Geometric nonlinearity Material nonlinearity Shape memory alloy

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Dynamic Modeling and control for an Offshore Semisubmersible Floating Wind Turbine

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 12371-12382页

作者： Gong, Yingjie Yang, Qinmin Geng, Hua Meng, Wenchao Wang, Lin Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Huzhou Institute Zhejiang University State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Hangzhou310027 China Tsinghua University Beijing National Research Center for Information Science and Technology Department of Automation Beijing100084 China Zhejiang Windey Company Ltd. Hangzhou310027 China

Floating wind turbines (FWTs) hold significant potential for the exploitation of offshore renewable energy resources. Nevertheless, prior to the construction of FWTs, it is imperative to tackle several critical challenges, especially the issue of performance degradation under combined wind and wave loads. This study initiates with the development of a simplified nonlinear dynamical model for a semi-submersible FWT. In particular, both the rotor dynamics and the finite rotations of the platform are considered in presented modeling approach, thereby effectively capturing the complex interplay between the platform, tower, nacelle, and rotor under combined wind and wave loads. Subsequently, based on the developed FWT model, a novel adaptive nonlinear pitch controller is formulated with the goal of striking a trade-off between regulating power generation and reducing platform motion. Notably, the proposed control strategy adopts a continuous control approach, strategically beneficial in circumventing the chattering phenomenon commonly associated with sliding mode control. Furthermore, the controller integrates an online approximator and a robust integral of the sign of the tracking error, facilitating real-time learning of system unknown dynamics while compensating for bounded disturbances. Finally, both the accuracy of the established nonlinear FWT model in predicting key dynamics and the superiority of the presented pitch controller are validated through comprehensive comparative studies. Note to Practitioners - This paper addresses the conflicting goals between power regulation and load mitigation for floating wind turbines (FWTs) to ensure the reliable operation of wind turbine systems. This remains an ongoing challenge due to the inherent complexity of existing FWT models, frequently resulting in controllers crafted using linearized representations that fail to accommodate real-world uncertainties effectively. Through the utilization of a simplified physical-based n

关键词： Renewable energy

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Distributed asynchronous double accelerated optimization for ethylene plant considering delays

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Chinese Journal of Chemical Engineering 2025年 78卷 245-250页

作者： Wang, Ting Li, Zhongmei Du, Wenli State Key Laboratory of Industrial Control Technology East China University of Science and Technology Shanghai200237 China Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education East China University of Science and Technology Shanghai200237 China

Considering the complexity of plant-wide optimization for large-scale industries, a distributed optimization framework to solve the profit optimization problem in ethylene whole process is proposed. To tackle the delays arising from the residence time for materials passing through production units during the process with guaranteed constraint satisfaction, an asynchronous distributed parameter projection algorithm with gradient tracking method is introduced. Besides, the heavy ball momentum and Nesterov momentum are incorporated into the proposed algorithm in order to achieve double acceleration properties. The experimental results show that the proposed asynchronous algorithm can achieve a faster convergence compared with the synchronous algorithm. © 2024 Chemical Industry and Engineering Society of China (CIESC) and Chemical Industry Press Co., Ltd. (CIP)

关键词： Optimization algorithms

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A Decoder-Free Reconstruction Method for Semi-Supervised Rail Surface Defect Detection

IEEE Transactions on Industrial Cyber-Physical Systems

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IEEE Transactions on industrial Cyber-Physical Systems 2025年 3卷 285-295页

作者： Liu, Chen Shi, Zhenyu He, Shibo Tang, Shunpu Yang, Qianqian The State Key Lab. of Industrial Control Technology Zhejiang University Hangzhou310027 China

Detecting defects on railway tracks is critical for the operation of high-speed trains. Despite a plethora of machine vision-based methods designed to tackle this problem, the majority adopt a supervised setting and demand considerable labeled training data, inclusive of defective samples, which is expensive and impractical. In this paper, we propose an Invertible Reconstruction neural Network (IRNet) for semi-supervised rail surface defect detection, where only normal images are accessible during training. Firstly, we devise an information-preserving feature encoder comprising several invertible blocks. This structure safeguards subtle visual patterns distinguishing normal and defective images from being obscured by background information, guaranteed by its mathematical reversibility property. Second, to overcome the overgeneralization issue of conventional autoencoders caused by imperfectly crafted decoders, we propose a novel decoder-free reconstruction workflow based on the invertible feature encoder. Specifically, we force one portion of extracted features to approach a predefined constant tensor during the training stage by minimizing their mean squared error. Next, we feed the remained features and the predefined constant tensor backward into the encoder to reconstruct the original images. During the testing phase, we formulate an anomaly score that consolidates the reconstruction error and mean squared error to spot defects. Extensive experiments are conducted on 4 real-world datasets. Our method consistently outperforms state-of-the-art techniques, demonstrating an average increase of 8.5% on the F1 score. © 2023 IEEE. All rights reserved.

关键词： Decoding

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Multi-Task Load Identification and Signal Denoising via Hierarchical Knowledge Distillation

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IEEE Transactions on Network Science and Engineering 2025年第3期12卷 1967-1980页

作者： Jiang, Jiahao Wang, Zhelong Qiu, Sen Li, Xiang Zhang, Chenming Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of the Ministry of Education School of Control Science and Engineering Dalian116024 China

Complex neural networks with deep structures are beneficial for solving problems such as load classification in Non-intrusive load monitoring (NILM) due to their powerful feature extraction capabilities. Unfortunately, corresponding complex models designed based on deep learning algorithms require high computational and memory resources. Additionally, the external noise interference during practical load identification poses a challenge. To solve these difficulties with practical industrial significance, this paper proposes a multi-task-knowledge distillation (MTL-KD) framework for NILM. The main contributions within this framework include a new feature extraction method that combines variational mode extraction (VME) and mutual information (MI) to extract unique features and filter out noise interference, an attention-based MTL model to simultaneously perform the load identification and signal de-noising tasks, and new KD modules to transfer knowledge from a complex teacher model to a small student model. Experimental evaluations conducted on public datasets such as the plug-load appliance identification dataset (PLAID) and the worldwide household and industry transient energy dataset (WHITED), as well as a private load dataset collected in the lab, demonstrate that the proposed MTL-KD framework surpasses state-of-the-art approaches. © 2013 IEEE.

关键词： Signal denoising

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Deployment dynamics and experiments of a tendon-actuated flexible manipulator

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Chinese Journal of Aeronautics 2025年第2期38卷 459-477页

作者： Benteng ZHANG Jialiang SUN Haiyan HU State Key Laboratory of Mechanics and Control for Aerospace Structures Nanjing University of Aeronautics and AstronauticsNanjing 210016China MOE Key Laboratory of Dynamics and Control of Flight Vehicle School of Aerospace EngineeringBeijing Institute of TechnologyBeijing 100081China

The quantity of space debris on Earth orbit has escalated tremendously in recent years, presenting a significant hazard to human space operations. It is urgent to develop effective measures to capture and remove various space debris. For this purpose, this paper presents a tendon-actuated flexible deployable manipulator. The flexible manipulator consists of several deployable units connected by Cardan joints and actuated by tendons. Compared with the present technologies for capturing space debris such as rigid robotic arm or flying net, this flexible manipulator is deployable, reusable, lightweight and applicable to the capture of large space debris. In order to investigate its deployment dynamics, an accurate dynamic model of the flexible manipulator is established based on the natural coordinate formulation (NCF) and the absolute nodal coordinate formulation (ANCF). Subsequently, numerical simulations are carried out to study the effects of system parameters and the base satellite on its deployment dynamics. Finally, ground experiments for both deployment and bending of the flexible manipulator are conducted to verify its effectiveness and feasibility.

关键词： Flexible manipulator Tendon-actuated Dynamic modeling Deployment dynamics Ground experiments

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A comparison on the effects of coal fines and sand fouling on the shear behaviors of railway ballast using large scale direct shear tests

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Journal of Traffic and Transportation Engineering(English Edition) 2025年第1期12卷 52-67页

作者： Xu Zhang Shunying Ji Yang Feng Yongjun Li Chunfa Zhao School of Civil and Transportation Engineering Guangdong University of Technology State Key Laboratory of Rail Transit Vehicle System Southwest Jiaotong University State Key Laboratory of Structural Analysis Optimization and CAE Software for Industrial EquipmentDalian University of Technology

Railway ballast is easily contaminated by different fouling material and the fouled ballast always causes the deterioration of railway track. Many previous studies focused on the effect of a certain kind of fouling material on ballast performance, but few studies compared the influence of different fouling material. This paper presents a series of direct shear tests on the clean ballast and the fouled ballast mixed with coal fines or sand to understand the effects of different fouling material. A unified empirical model is proposed to well capture the shear stress-displacement responses of the clean and fouled *** equations are also obtained to characterize the variation of the nonlinear shear strength envelope of the fouled ballast with the fouling content. Based on these equations,a simple method is proposed to predict the shear strength of the fouled ballast using the shear test results of clean ballast. The measured results demonstrate significant differences between the effects of coal fines and sand on the shear behaviors of ballast, to which particular attention should be paid in order to take targeted maintenance measures for the fouled ballast. The mechanisms for the different effects of coal fines and sand are also analyzed to understand the roles that various fouling material plays in the fouled ballast.

关键词： Railway ballast Fouled ballast Shear strength Direct shear test Contamination

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