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Deep Reinforcement Learning-based Multi-Objective Scheduling for Distributed Heterogeneous Hybrid Flow Shops with Blocking Constraints

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Engineering 2025年第3期46卷 278-291页

作者： Xueyan Sun Weiming Shen Jiaxin Fan Birgit Vogel-Heuser Fandi Bi Chunjiang Zhang State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Institute of Automation and Information Systems Technical University of MunichGarching 85748Germany

This paper investigates a distributed heterogeneous hybrid blocking flow-shop scheduling problem(DHHBFSP)designed to minimize the total tardiness and total energy consumption simultaneously,and proposes an improved proximal policy optimization(IPPO)method to make real-time decisions for the DHHBFSP.A multi-objective Markov decision process is modeled for the DHHBFSP,where the reward function is represented by a vector with dynamic weights instead of the common objectiverelated scalar value.A factory agent(FA)is formulated for each factory to select unscheduled jobs and is trained by the proposed IPPO to improve the decision *** FAs work asynchronously to allocate jobs that arrive randomly at the shop.A two-stage training strategy is introduced in the IPPO,which learns from both single-and dual-policy data for better data *** proposed IPPO is tested on randomly generated instances and compared with variants of the basic proximal policy optimization(PPO),dispatch rules,multi-objective metaheuristics,and multi-agent reinforcement learning *** experimental results suggest that the proposed strategies offer significant improvements to the basic PPO,and the proposed IPPO outperforms the state-of-the-art scheduling methods in both convergence and solution quality.

关键词： Multi-objective Markov decision process Multi-agent deep reinforcement learning Proximal policy optimization Distributed hybrid flow-shop scheduling Blocking constraints

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Online Digital Twin Adaptive Critic Design With Long Short-Term Memory for Wastewater Treatment Plants

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IEEE Transactions on Automation Science and Engineering 2025年 22卷 15241-15250页

作者： Wang, Ding Ma, Hongyu Ren, Jin Han, Honggui Qiao, Junfei Beijing University of Technology School of Information Science and Technology Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Laboratory of Smart Environmental Protection Beijing Institute of Artificial Intelligence Beijing100124 China

The wastewater treatment system is a complex unknown system with nonlinear and uncertain characteristics. It is necessary to control the concentration of the dissolved oxygen and the nitrate nitrogen at the set value in the wastewater treatment process. However, traditional control methods are difficult to meet the accuracy requirements for the required concentration value. At the same time, the digital twin (DT) technology has been widely applied to practical industrial systems like the wastewater treatment system in recent years. Based on the above backgrounds, an online DT adaptive critic design (DTACD) is developed by combining the long short-term memory (LSTM) neural network with the action-critic structure. First, a set of historical data is collected, which is used to build a digital model using LSTM. Then, the digital model is used to guide the real wastewater treatment system to control the nitrate nitrogen concentration and the dissolved oxygen concentration at set values. Finally, we select the Benchmark Simulation Model No.1 as the model for the simulation experiment. Compared with other methods, DTACD shows a better performance. © 2004-2012 IEEE.

关键词： Reinforcement learning

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An improved efficient adaptive method for large-scale multiexplosives explosion simulations

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Defence technology(防务技术) 2025年第3期45卷 28-47页

作者： Tao Li Cheng Wang Baojun Shi School of Mechanical Engineering Key Laboratory of Advanced Intelligent Protective Equipment TechnologyMinistry of EducationHebei University of TechnologyTianjin300401China State Key Lab of Explosion Science and Safety Protection Beijing Institute of TechnologyBeijing 100081China

Shock wave caused by a sudden release of high-energy,such as explosion and blast,usually affects a significant range of *** utilization of a uniform fine mesh to capture sharp shock wave and to obtain precise results is inefficient in terms of computational *** is particularly evident when large-scale fluid field simulations are conducted with significant differences in computational domain *** this work,a variable-domain-size adaptive mesh enlargement(vAME)method is developed based on the proposed adaptive mesh enlargement(AME)method for modeling multi-explosives explosion *** vAME method reduces the division of numerous empty areas or unnecessary computational domains by adaptively suspending enlargement operation in one or two directions,rather than in all directions as in AME method.A series of numerical tests via AME and vAME with varying nonintegral enlargement ratios and different mesh numbers are simulated to verify the efficiency and order of *** estimate of speedup ratio is analyzed for further efficiency *** large-scale near-ground explosion experiments with single/multiple explosives are performed to analyze the shock wave superposition formed by the incident wave,reflected wave,and Mach ***,the vAME method is employed to validate the accuracy,as well as to investigate the performance of the fluid field and shock wave propagation,considering explosive quantities ranging from 1 to 5 while maintaining a constant total *** results show a satisfactory correlation between the overpressure versus time curves for experiments and numerical *** vAME method yields a competitive efficiency,increasing the computational speed to 3.0 and approximately 120,000 times in comparison to AME and the fully fine mesh method,*** indicates that the vAME method reduces the computational cost with minimal impact on the results for such large-scale high-energy release problems with signi

关键词： Large-scale explosion Shock wave Adaptive method Fluid field simulations Efficient method

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Extended eigenvalue calibration method for Mueller matrix polarimetry with four photoelastic modulators

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Optics Letters 2025年第3期50卷 840-843页

作者： Chen, Wenlong Chen, Xiuguo Wang, Yifu Yang, Shilong Yue, Hang Hu, Jing Liu, Shiyuan State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China Optics Valley Laboratory Wuhan430074 China

The Mueller matrix polarimeter with four photoelastic modulator (4-PEM MMP), known for its high-speed and high-precision measurement capabilities, holds great potential in material characterization and nanoscale measurements. We propose an extended eigenvalue calibration method (eECM) to the 4-PEM MMP by introducing two temporal basis vectors to project the continuously modulated light intensity into a time-independent projection matrix, which can then be acquired by a nonlinear regression method. The eECM enables complete calibration of system parameters of the 4-PEM MMP in a model-free manner without any approximation, including the parameters associated with each PEM and the alignment errors in the azimuths of all the polarization elements. Moreover, it is unnecessary to precisely adjust the orientations of the polarization elements, and it does not require precise reference sample information either. Consequently, the eECM allows the 4-PEM MMP to achieve accurate Mueller matrix measurement under not only the usual system configurations but also other unusual system configurations in a simple and unified approach. Simulation results have verified the effectiveness and advantages of the eECM. © 2025 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.

关键词： Calibration

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Edge-Cloud Cooperation-Driven intelligent Sustainability Evaluation Strategy Based on IoT and CPS for Energy-Intensive Manufacturing Industries

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IEEE Internet of Things Journal 2025年第9期12卷 12287-12297页

作者： Ma, Shuaiyin Huang, Yuming Chen, Yanping Xiao, Qinge Xu, Jun Leng, Jiewu Xi’an University of Posts and Telecommunications Shaanxi Key Laboratory of Network Data Analysis and Intelligent Processing Xi’an Key Laboratory of Big Data and Intelligent Computing School of Computer Science and Technology Xi’an710121 China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Xidian University Advanced Manufacturing Technology Innovation Center Guangzhou Institute of Technology Guangzhou510555 China Guangdong University of Technology Guangdong Provincial Key Laboratory of Computer Integrated Manufacturing System State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment Guangzhou510006 China

The advancement of the Industry 5.0 in information technology has led to increased interest in integrating edge-cloud cooperation with Internet of Things (IoT) and cyber-physical system (CPS) designs. This integration effectively reduces service delays and provides real-time analysis feedback to physical spaces, attracting attention from both academia and industry. These advanced technologies enhance production system intelligence, their alignment with circular economy principles for promoting sustainability has been overlooked. To address this gap, this article proposes an intelligent sustainability evaluation strategy driven by edge-cloud cooperation, IoT, and CPS. The proposed approach aims to enhance production sustainability and intelligence through circular economy perspectives. It introduces improved gray relation analysis and deep clustering network techniques to extract meaningful insights from diverse indicators within the evaluation system. By analyzing relationships between different equipment and workshops, it provides an analytical method that enhances production efficiency while reducing energy consumption and resource waste. To further validate the proposed method, an illustrative example using a partner company’s production data demonstrates its accuracy. © 2014 IEEE.

关键词： Circular economy

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A novel rotor dynamic balancing method based on blade tip clearance measurement without the once per revolution sensor

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Chinese Journal of Aeronautics 2025年第2期38卷 445-458页

作者： Weibo LI Weimin WANG Shuai ZHANG Jiale WANG Yulong LIN Tianqing LI Key Lab of Engine Health Monitoring-Control and Networking of Ministry of Education Beijing University of Chemical TechnologyBeijing 100029China State Key Laboratory of High-end Compressor and System Technology Beijing University of Chemical TechnologyBeijing 100029China

The existence of the aeroengine casing,limited monitoring points,and multi-fault characteristics make obtaining the rotor’s vibration transmission characteristics challenging,resulting in difficulties accurately identifying the rotor *** paper utilizes a high-frequency composite sensor to monitor the engine’s blade tip clearance(BTC)and extracts unbalanced information from BTC signals for rotor dynamic balancing,while avoiding the need for the once per revolution(OPR)***,the vibration characteristics of the rotor-blade system under multi-fault conditions are ***,based on BTC measurement,a none OPR method and an unbalance identification method are proposed,in which the radial vibration of the blade tip in the BTC signals at different speeds is extracted and operated in the time domain to obtain the rotor unbalanced vibration,the signal is reconstructed,and cross-correlation analysis is used to accurately identify the magnitude and phase of the unbalanced ***,a rotor test bench is utilized for experimental *** results reveal that the dynamic balancing method based on the BTC signal can more precisely identify the rotor unbalance than the traditional rotor dynamic balancing *** application of this technique will effectively improve engine health management and fault prediction.

关键词： Aeroengine Rotor unbalance Composite sensor None once per revolution Blade tip clearance Dynamic balancing

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Penalty Function-Based Distributed Primal-Dual Algorithm for Nonconvex Optimization Problem

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 394-402页

作者： Xiasheng Shi Changyin Sun IEEE the Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Anhui University the School of Artificial Intelligence Anhui University Anhui Provincial Engineering Research Center for Unmanned System and Intelligent Technology Anhui University the Anhui Key Laboratory Industrial Energy-Saving and Safety Anhui University

This paper addresses the distributed nonconvex optimization problem, where both the global cost function and local inequality constraint function are nonconvex. To tackle this issue, the p-power transformation and penalty function techniques are introduced to reframe the nonconvex optimization problem. This ensures that the Hessian matrix of the augmented Lagrangian function becomes local positive definite by choosing appropriate control parameters. A multi-timescale primal-dual method is then devised based on the Karush-Kuhn-Tucker(KKT) point of the reformulated nonconvex problem to attain convergence. The Lyapunov theory guarantees the model's stability in the presence of an undirected and connected communication network. Finally, two nonconvex optimization problems are presented to demonstrate the efficacy of the previously developed method.

关键词： Constrained optimization Karush-Kuhn-Tucker (KKT) point nonconvex p-power transformation

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Gradient-based attitude planning for rigid spacecraft on SO(3)

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Science China Technological Sciences 2025年第5期68卷 167-178页

作者： Tao HUO Jin YANG Chengfei YUE Xueqin CHEN Xibin CAO School of Astronautics Harbin Institute of Technology School of Management Harbin Institute of Technology State Key Laboratory of Micro-Spacecraft Rapid Design and Intelligent Cluster Harbin Institute of Technology School of Aerospace Science Harbin Institute of Technology Shenzhen

Attitude planning of rigid bodies has many applications in robotics and aerospace. However, because the attitude configuration space is non-Euclidean and the constraints are complex and non-linear, the design of the attitude curve has always been a tricky problem. In this paper, a gradient-based attitude planning method is proposed to simultaneously handle attitude pointing, angular velocity, torque, and time constraints on Lie group SO(3). Firstly, the attitude interpolation algorithm on SO(3) gives an attitude curve connecting the initial and target attitudes. The shape of the curve is determined by the fitting coefficients and maneuvering time. Secondly, to match the curve with suitable angular velocity and control torque, a nonlinear planning model with fitting coefficients and maneuver time as decision variables is proposed. Solving the problem gives a smooth attitude curve that satisfies both kinematic and dynamic constraints and also avoids complicated time allocation. Then, to apply the gradientbased solver, analytical formulas for the derivatives of each order of the attitude curve with respect to the decision variables are given in this paper. Finally, the effectiveness of the proposed algorithm is verified by a series of numerical simulations.

关键词： attitude planning attitude constraints gradient optimization three-dimensional special orthogonal group (SO(3))

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Distributed Temperature Sensing Based on Chaotic Brillouin Scattering Power Measurement

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IEEE Sensors Journal 2025年第9期25卷 15968-15974页

作者： Xu, Jinglang Zhang, Jianzhong Li, Jian Ma, Zhe Liu, Shuangshuang Zhang, Yubo Wang, Zhikun Zhang, Mingjiang Taiyuan University of Technology Key Laboratory of Advanced Transducers and Intelligent Control System Ministry of Education and Shanxi Province College of Physics and Optoelectronic Engineering Taiyuan030024 China

A high-accuracy distributed temperature sensing scheme utilizing chaotic Brillouin scattering power (BSP) combined with the cross correlation measurement method was proposed and experimentally demonstrated. The proposed scheme employs the chaotic laser as the sensing signal, adopting the chaotic cross correlation positioning principle instead of the conventional optical time-domain reflection (OTDR) principle. Additionally, it combines a single-path ratio method to accurately demodulate the temperature. This positioning method uses the random amplitude characteristics of chaotic lasers in the time domain. It overcomes the limitation of pulsewidth on spatial resolution in distributed temperature sensing based on OTDR principles. And it resolves the trade-off between spatial resolution and sensing distance. Experimental results demonstrated that the spatial positioning accuracy was optimized from 5.0 to 0.43 m with a 50 ns pulsewidth modulation, achieving a sensing distance of up to 10 km. This scheme aims to achieve high spatial positioning accuracy while maintaining a long sensing distance. This is crucial for early fire warning and effective emergency response in long-distance fire monitoring applications. © 2025 IEEE.

关键词： Brillouin scattering

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Modeling and control of a rigid-flexible coupling robot for narrow space manipulations

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Science China(Technological Sciences) 2025年第2期68卷 136-152页

作者： Kuangda CHEN Huan ZHAO Jiexin ZHANG Mei FENG Yiwei WANG Jinliang WANG Han DING State Key Laboratory of Intelligent Manufacturing Equipment and Technology Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of CNC Equipment Reliability Ministry of EducationJilin UniversityChangchun 130021China School of Medical Equipment Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China

Narrow space manipulations are crucial for equipment maintenance,as they eliminate the need for disassembly,thus reducing costs and increasing ***-driven flexible robots possess exceptional capabilities in maneuvering through narrow spaces,thanks to their interaction compliance and distal ***,their inherent low stiffness causes a decline in the location accuracy of the robot and could even lead to manipulation *** address this challenge,this paper proposes a novel type of rigid-flexible coupling robot,which increases the stiffness of the robot while ensuring the reachability within a narrow *** achieve high-accuracy location in a narrow space,kinematic and control methods are ***,the robot forward kinematics are uniformly represented,and the closed-form inverse kinematics solution is ***,in cases where the robot's structure fails to align with Pieper's solution,a two-stage search strategy is utilized to solve the inverse kinematics,resulting in a high success rate of 99.1%.Based on the proposed kinematics,a rigid-dominated control method is then proposed to facilitate localization and pose alignment of target objects in narrow *** practical comparative experiments show that the proposed robot has the capability of high accuracy control in narrow spaces.

关键词： narrow space manipulation rigid-flexible coupling robot kinematics rigid-dominated control

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