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A Multi-Condition Sequential Network Ensemble for Industrial Energy Storage Prediction Considering the Condition Switching Characteristics

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IEEE/CAA Journal of Automatica Sinica 2025年第2期12卷 369-380页

作者： Tianyu Wang Fan Zhou Yangjie Wu Jun Zhao Wei Wang IEEE the School of Control Science and Engineering Dalian University of Technology the School of Information Science and Engineering Dalian Polytechnic University

As a crucial storage and buffering apparatus for balancing the production and consumption of byproduct gases in industrial processes, accurate prediction of gas tank levels is essential for optimizing energy system scheduling. Considering that the continuous switching of the pressure and valve status(mechanism knowledge) would bring about multiple working conditions of the equipment, a multi-condition time sequential network ensembled method is proposed. In order to especially consider the time dependence of different conditions, a centralwise condition sequential network is developed, where the network branches are specially designed based on the condition switching sequences. A branch combination transfer learning strategy is developed to tackle the sample imbalance problem of different condition data. Since the condition or status data are real-time information that cannot be recognized during the prediction process, a pre-trained and ensemble learning approach is further proposed to fuse the outputs of the multi-condition networks and realize a transient-state involved prediction. The performance of the proposed method is validated on practical energy data coming from a domestic steel plant, comparing with the state-of-the-art algorithms. The results show that the proposed method can maintain a high prediction accuracy under different condition switching cases, which would provide effective guidance for the optimal scheduling of the industrial energy systems.

关键词： Ensemble learning industrial energy prediction multi-working condition structural deep network transfer learning

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A Constraint Adaptive Multi-Tasking Differential Evolution Algorithm:Designed for Dispatch of Integrated Energy System in Coal Mine

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Tsinghua Science and technology 2024年第2期29卷 368-385页

作者： Canyun Dai Xiaoyan Sun Hejuan Hu Yong Zhang Dunwei Gong School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116China School of Information Science and Technology Qingdao University of Science and TechnologyQingdao 266061China

The dispatch of integrated energy systems in coal mines(IES-CM)with mine-associated supplies is vital for efficient energy utilization and carbon emissions ***,IES-CM dispatch is highly challenging due to its feature as multi-objective and strong *** constrained multi-objective evolutionary algorithms often fall into locally feasible domains with poorly distributed Pareto front,which greatly deteriorates dispatch *** tackle this problem,we transform the traditional dispatch model of IES-CM into two tasks:the main task with all constraints and the helper task with constraint *** we propose a constraint adaptive multi-tasking differential evolution algorithm(CA-MTDE)to optimize these two tasks *** helper task with constraint adaptive is developed to obtain infeasible solutions near the feasible *** purpose of this infeasible solution is to transfer guiding knowledge to help the main task move away from local ***,a dynamic dual-learning strategy using DE/current-to-rand/1 and DE/current-to-best/1 is developed to maintain task diversity and ***,we comprehensively evaluate the performance of CA-MTDE by applying it to a coal mine in Shanxi Province,considering two IES-CM *** demonstrate the feasibility of CA-MTDE and its ability to generate a Pareto front with exceptional convergence,diversity,and distribution.

关键词： dispatch integrated energy system coal mine evolutionary multi-tasking constraint differential evolution

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Research on tracking strategy of manipulator based on fusion reward mechanism

AIMS Electronics and Electrical Engineering

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AIMS Electronics and Electrical engineering 2025年第1期9卷 99-117页

作者： Dong, Ruyi Yang, Kai Wang, Tong College of Information and Control Engineering Jilin Institute of Chemical Technology Jilin China

Deep reinforcement learning algorithms are widely used in the field of robot control. Sparse reward signals lead to blind exploration, affecting the efficiency of the manipulator during path planning for multi-axis systems at any given end-effector start and target position. To address the problem of tracking randomly located targets in three-dimensional space, this paper proposes a PPO (proximal policy optimization) algorithm with a fused reward mechanism, which enhances the tracking and guidance capabilities of the manipulator in multiple dimensions and reduces the blind randomness of the manipulator during the detection and sampling process. The fusion reward mechanism consists of four dimensions: trajectory correction reward, core area acceleration guidance reward, ladder adaptability reward, and abnormal termination penalty. Finally, a 7-degree-of-freedom Kuka manipulator is built on the PyBullet platform for simulation experiments. Experimental results show that, compared with the sparse reward mechanism, the PPO algorithm with the fused reward mechanism has a higher average success rate as high as 94.88% in task tracking, which can effectively improve the tracking efficiency and accuracy of the spatial manipulator. © 2025 the Author(s)

关键词： deep reinforcement learning fusion reward mechanism intelligent control manipulator proximal policy optimization tracking

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Grouping Decision Algorithm for Dynamic Terminals in Random Access Networks

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Journal of Communications and information Networks 2024年第2期9卷 176-183页

作者： Hongliang Sun Tongfei Chen Chuangye Zhao Mengxin Chen College of Information and Control Engineering Jilin Institute of Chemical TechnologyJilin 132022China

This paper proposes a grouping decision algorithm for random access networks with the carrier sense multiple access (CSMA) mechanism, which can balance the traffic load and solve the hidden terminal issue. Considering the arrival characteristics of terminals and quality of service (QoS) requirements, the traffic load is evaluated based on the effective bandwidth theory. Additionally, a probability matrix of hidden terminals is constructed to take into account the dynamic nature of hidden terminal relations. In the grouping process, an income function is established with a view to the benefits of decreasing the probability of hidden terminal collisions and load balancing. Then, we introduce the grey wolf optimization (GWO) algorithm to implement the grouping decision. Simulation results demonstrate that the grouping algorithm can effectively alleviate the performance degradation and facilitate the management of network resources.

关键词： random access network hidden terminal collision probability effective bandwidth traffic load grey wolf optimization

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Adaptive Finite-Time Trajectory Tracking control for Underactuated Surface Vehicles Based on Adaptive Disturbance Compensating

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Hu, Xiangyu Chen, Jian Lv, Chengxing Yang, Zhibo Li, Jinhai School of Information and Control Engineering Qingdao University of Technology Qingdao China

This paper studies the trajectory tracking problem of underactuated surface vehicles with model uncertainties and external disturbances. We propose an adaptive finite-time control method, in which the disturbance compensating is considered. To deal with the underactuated problem in the model, a sliding mode technique is introduced, and the system is divided into two subsystems which coupled with each other. New parameter adaptive law is designed for the parameter uncertainties. A new finite-time disturbance observer with a set of adaptive parameters is constructed to estimate the model uncertainties and external disturbances. Then, the adaptive finite-time trajectory tracking controller is achieved by using a new integral-type Lyapunov function. It is theoretically proved that all tracking errors in the closed-loop system are finite-time stable. To verify the feasibility, simulation on the surface vessels has been conducted. IEEE

关键词： Closed loop systems

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Robust Offline Actor-Critic With On-policy Regularized Policy Evaluation

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IEEE/CAA Journal of Automatica Sinica 2024年第12期11卷 2497-2511页

作者： Shuo Cao Xuesong Wang Yuhu Cheng the Engineering Research Center of Intelligent Control for Underground Space Ministry of Educationand the School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221116China IEEE

To alleviate the extrapolation error and instability inherent in Q-function directly learned by off-policy Q-learning(QL-style)on static datasets,this article utilizes the on-policy state-action-reward-state-action(SARSA-style)to develop an offline reinforcement learning(RL)method termed robust offline Actor-Critic with on-policy regularized policy evaluation(OPRAC).With the help of SARSA-style bootstrap actions,a conservative on-policy Q-function and a penalty term for matching the on-policy and off-policy actions are jointly constructed to regularize the optimal Q-function of off-policy *** naturally equips the off-policy QL-style policy evaluation with the intrinsic pessimistic conservatism of on-policy SARSA-style,thus facilitating the acquisition of stable estimated *** with limited data sampling errors,the convergence of Q-function learned by OPRAC and the controllability of bias upper bound between the learned Q-function and its true Q-value can be theoretically *** addition,the sub-optimality of learned optimal policy merely stems from sampling *** on the well-known D4RL Gym-MuJoCo benchmark demonstrate that OPRAC can rapidly learn robust and effective tasksolving policies owing to the stable estimate of Q-value,outperforming state-of-the-art offline RLs by at least 15%.

关键词： Offline reinforcement learning off-policy QL-style on-policy SARSA-style policy evaluation(PE) Q-value estimation

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Design and Validation of Substrate Integrated Waveguide-based Blood Glucose Measurement Sensor

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IEEE Sensors Journal 2025年第11期25卷 20362-20373页

作者： Alsultani, Ameer B. Chase, J. Geoffrey Benyo, Balazs Budapest University of Technology and Economics Faculty of Electrical Engineering and Information Technology Department of Control Engineering and information Technology Budapest Hungary University of Canterbury Department of Mechanical Engineering Christchurch New Zealand

The increasing global prevalence of diabetes necessitates the development of accurate, reliable, and miniaturised glucose sensing technologies. Microwave-based sensors offer a promising alternative to conventional electrochemical methods due to their less invasive nature and real-time monitoring capabilities. However, previous microwave glucose sensors have often lacked comprehensive validation, limiting their practical usability. Many existing studies rely on simplified simulations without detailed parametric studies or fail to establish a strong correlation between theoretical models and experimental results, resulting in discrepancies in sensor performance. This study introduces a Cross-Slot Substrate Integrated Waveguide (CSSIW) sensor that overcomes these limitations by implementing a rigorous multi-level validation approach, including analytical modeling, full-wave electromagnetic simulations, and experimental verification. The sensor’s X-slot structure enhances electric field concentration, significantly improving sensitivity while maintaining a compact form factor (13×9 mm). Through eigenmode analysis and parametric studies, the sensor’s resonant frequency shift is optimised to detect glucose concentration variations with high precision. Experimental validation using glucose solutions at physiological concentrations (20–200 mg/dL) demonstrates a sensitivity of 0.563 MHz/(mg/dL), closely aligning with simulated results (0.415 MHz/(mg/dL)), confirming its accuracy and robustness. Compared to previous works, this study addresses prior shortcomings by providing a detailed investigation of field interactions, quality factor evaluation, and environmental dependencies, ensuring a comprehensive understanding of the CSSIW sensor’s performance. The findings confirm that the proposed sensor achieves low insertion loss (1.13 dB), strong impedance matching (-18.7 dB return loss), and full physiological range coverage, making it a promising candidate for next-generation g

关键词： Substrate integrated waveguides

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Quantum color image encryption: Dual scrambling scheme based on DNA codec and quantum Arnold transform

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Chinese Physics B 2025年第1期34卷 235-244页

作者： Tao Cheng Run-Sheng Zhao Shuang Wang Kehan Wang Hong-Yang Ma School of Sciences Qingdao University of TechnologyQingdao 266033China School of Information and Control Engineering Qingdao University of TechnologyQingdao 266033China

In the field of Internet, an image is of great significance to information transmission. Meanwhile, how to ensure and improve its security has become the focus of international research. We combine DNA codec with quantum Arnold transform(QAr T) to propose a new double encryption algorithm for quantum color images to improve the security and robustness of image encryption. First, we utilize the biological characteristics of DNA codecs to perform encoding and decoding operations on pixel color information in quantum color images, and achieve pixel-level diffusion. Second, we use QAr T to scramble the position information of quantum images and use the operated image as the key matrix for quantum XOR operations. All quantum operations in this paper are reversible, so the decryption operation of the ciphertext image can be realized by the reverse operation of the encryption process. We conduct simulation experiments on encryption and decryption using three color images of “Monkey”, “Flower”, and “House”. The experimental results show that the peak value and correlation of the encrypted images on the histogram have good similarity, and the average normalized pixel change rate(NPCR) of RGB three-channel is 99.61%, the average uniform average change intensity(UACI) is 33.41%,and the average information entropy is about 7.9992. In addition, the robustness of the proposed algorithm is verified by the simulation of noise interference in the actual scenario.

关键词： DNA codec quantum Arnold transform quantum image encryption algorithm

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Global receptive field transformer decoder method on quantum surface code data and syndrome error correction

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Chinese Physics B 2025年第3期34卷 267-276页

作者： Ao-Qing Li Ce-Wen Tian Xiao-Xuan Xu Hong-Yang Ma Jun-Qing Liang School of Information and Control Engineering Qingdao University of TechnologyQingdao 266033China School of Sciences Qingdao University of TechnologyQingdao 266033China

Quantum computing has the potential to solve complex problems that are inefficiently handled by classical ***,the high sensitivity of qubits to environmental interference and the high error rates in current quantum devices exceed the error correction thresholds required for effective algorithm ***,quantum error correction technology is crucial to achieving reliable quantum *** this work,we study a topological surface code with a two-dimensional lattice structure that protects quantum information by introducing redundancy across multiple qubits and using syndrome qubits to detect and correct ***,errors can occur not only in data qubits but also in syndrome qubits,and different types of errors may generate the same syndromes,complicating the decoding task and creating a need for more efficient decoding *** address this challenge,we used a transformer decoder based on an attention *** mapping the surface code lattice,the decoder performs a self-attention process on all input syndromes,thereby obtaining a global receptive *** performance of the decoder was evaluated under a phenomenological error *** results demonstrate that the decoder achieved a decoding accuracy of 93.8%.Additionally,we obtained decoding thresholds of 5%and 6.05%at maximum code distances of 7 and 9,*** results indicate that the decoder used demonstrates a certain capability in correcting noise errors in surface codes.

关键词： quantum error correction surface code transformer decoder

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Quantum decoder design for subsystem surface code based on multi-head graph attention and edge weighting

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Chinese Physics B 2025年第2期34卷 165-176页

作者： Nai-Hua Ji Hui-Qian Sun Bo Xiao Ping-Li Song Hong-Yang Ma School of Information and Control Engineering Qingdao University of TechnologyQingdao 266033China School of Sciences Qingdao University of TechnologyQingdao 266033China

Quantum error-correcting codes are essential for fault-tolerant quantum computing,as they effectively detect and correct noise-induced errors by distributing information across multiple physical *** subsystem surface code with three-qubit check operators demonstrates significant application potential due to its simplified measurement operations and low logical error ***,the existing minimum-weight perfect matching(MWPM)algorithm exhibits high computational complexity and lacks flexibility in large-scale ***,this paper proposes a decoder based on a graph attention network(GAT),representing error syndromes as undirected graphs with edge weights,and employing a multihead attention mechanism to efficiently aggregate node features and enable parallel *** to MWPM,the GAT decoder exhibits linear growth in computational complexity,adapts to different quantum code structures,and demonstrates stronger robustness under high physical error *** experimental results demonstrate that the proposed decoder achieves an overall accuracy of 89.95%under various small code lattice sizes(L=2,3,4,5),with the logical error rate threshold increasing to 0.0078,representing an improvement of approximately 13.04%compared to the MWPM *** result significantly outperforms traditional methods,showcasing superior performance under small code lattice sizes and providing a more efficient decoding solution for large-scale quantum error correction.

关键词： quantum error correction graph attention network subsystem surface code circuit-level noise

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