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Adaptive Neural Network-Based Asynchronous control for Switching Cyber-Physical Systems With Unknown Dead Zone

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IEEE transactions on cybernetics 2025年 PP卷 PP页

作者： Jun Cheng Junhui Wu Huaicheng Yan Dan Zhang Zheng-Guang Wu Ying Zhai Guangxi Normal University School of Mathematics and Statistics Guilin541006 China East China University of Science and Technology Key Laboratory of Advanced Control and Optimization for Chemical Process of Ministry of Education Shanghai200237 China Zhejiang University of Technology Department of Automation Hangzhou310014 China Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China

This study investigates the problem of adaptive neural network asynchronous control for switching cyber-physical systems under unknown dead zones. A generalized switching rule, instead of a Markov/semi-Markov process, is utilized to scrutinize the switching behavior of subsystems. This approach characterizes the dynamic nature of sojourn probabilities using single-mode-based sojourn time, aiming to decrease computational load while meeting the demands of real-world scenarios. Considering the intricacies of network environments, the unknown dead zone inputs are considered, which can be effectively implemented via the adaptive neural network-based control law. To counteract the adverse effects of unforeseen information, a saturation-based observer is developed, in which the saturation level is dynamically adjusted with the hope of providing greater flexibility. Utilizing a Lyapunov function that correlates with the detected mode and the system mode, sufficient criteria are established to ensure that the closed-loop system remains bounded in probability. Eventually, the practicality and effectiveness of the proposed control methodology are verified through two simulated examples.

关键词： Markov processes

Towards Energy-Efficiency: Integrating MATD3 Reinforcement Learning Method for Computational Offloading in RIS-Aided UAV-MEC Environments

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IEEE Internet of Things Journal 2025年

作者： Wu, Liangshun Zhang, Cong Zhang, Bin Du, Jianbo Qu, Junsuo Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai201210 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts & Telecommunications Xi'an710061 China Xinjiang University of Political Science and Law Tumushuke832003 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Department of Computer City University of Hong Kong 999077 Hong Kong School of Communications and Information Engineering Xi'an University of Posts & Telecommunications Xi'an710061 China

With the proliferation of IoT devices, there is an escalating demand for enhanced computing and communication capabilities. Mobile Edge Computing (MEC) addresses this need by relocating computing resources to the network edge, thereby delivering swifter and more efficient services. This paper introduces a computation offloading and energy consumption optimization framework that leverages Reconfigurable Intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and MEC. The scheme aims to maximize energy efficiency through the optimization of task allocation, RIS phase shifts, and UAV trajectories. By employing the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) reinforcement learning algorithm, the paper further refines UAV trajectories and RIS configurations. The simulation results indicate that the proposed method surpasses the traditional Concave-Convex Procedure (CCCP) algorithm in both UAV trajectory control and RIS configuration, demonstrating quicker convergence and enhanced stability. The method proves to be adaptable to diverse environments and tasks, showcasing notable benefits in RIS-assisted interference suppression, particularly with large RIS, thereby enhancing UAV data reception rates. Additionally, MATD3 exhibits faster and smoother convergence for extended task durations and smaller RIS scenarios. Simulation results reveal that UAVs tend to move closer to RIS, with energy efficiency falling as IoT tasks increase, affirming the proposed algorithm's high energy efficiency and effectiveness. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

Distributed Constrained Online Nonconvex Optimization with Compressed Communication

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

Point cloud-based registration and image fusion between cardiac SPECT MPI and CTA

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arXiv 2024年

作者： Shaojie, Tang Penpen, Miao Xingyu, Gao Yu, Zhong Dantong, Zhu Haixing, Wen Zhihui, Xu Qiuyue, Wei Hongping, Yao Xin, Huang Rui, Gao Chen, Zhao Weihua, Zhou School of Automation Xi’an University of Posts and Telecommunications Shaanxi Xi’an710121 China Xi'an Key Laboratory of Advanced Control and Intelligent Process Shaanxi Xi’an710121 China Second Clinical Medical School of Nanjing Medical University Jiangsu Nanjing210011 China Department of Cardiology The First Affiliated Hospital of Nanjing Medical University Jiangsu Nanjing210000 China Department of Pharmacy The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Cardiology The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Nuclear Medicine The First Affiliated Hospital of Xi’an Jiaotong University Shaanxi Xi’an710061 China Department of Computer Science Kennesaw State University MariettaGA30060 United States Department of Applied Computing Center for Biocomputing and Digital Health Institute of Computing and Cybersystems Health Research Institute Michigan Technological University HoughtonMI49931 United States

A method was proposed for the point cloud-based registration and image fusion between cardiac single photon emission computed tomography (SPECT) myocardial perfusion images (MPI) and cardiac computed tomography angiograms (CTA). Firstly, the left ventricle (LV) epicardial regions (LVERs) in SPECT and CTA images were segmented by using different U-Net neural networks trained to generate the point clouds of the LV epicardial contours (LVECs). Secondly, according to the characteristics of cardiac anatomy, the special points of anterior and posterior interventricular grooves (APIGs) were manually marked in both SPECT and CTA image volumes. Thirdly, we developed an in-house program for coarsely registering the special points of APIGs to ensure a correct cardiac orientation alignment between SPECT and CTA images. Fourthly, we employed ICP, SICP or CPD algorithm to achieve a fine registration for the point clouds (together with the special points of APIGs) of the LV epicardial surfaces (LVERs) in SPECT and CTA images. Finally, the image fusion between SPECT and CTA was realized after the fine registration. The experimental results showed that the cardiac orientation was aligned well and the mean distance error of the optimal registration method (CPD with affine transform) was consistently less than 3 mm. The proposed method could effectively fuse the structures from cardiac CTA and SPECT functional images, and demonstrated a potential in assisting in accurate diagnosis of cardiac diseases by combining complementary advantages of the two imaging modalities. © 2024, CC BY.

关键词： Image fusion

Pharmacokinetic characteristics of Jinhong tablets in normal, chronic superficial gastritis and intestinal microbial disorder rats

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arXiv 2025年

作者： Zhang, Tingyu Feng, Jian Gao, Xia Chen, Xialin Peng, Hongyu Fan, Xiaoxue Meng, Xin Yin, Mingke Wang, Zhenzhong Zhang, Bo Cao, Liang Institute for TCM-X Department of Automation Tsinghua University Beijing100084 China State Key Laboratory of Technologies for Chinese Medicine Pharmaceutical Process Control and Intelligent Manufacture Jiangsu Kanion Pharmaceutical Co.Ltd. Jiangsu Nanjing210000 China Jiangsu Kanion Modern Chinese Medicine Institute Nanjing211100 China

Enthnopharmacological relevance: Jinhong tablet (JHT), a traditional Chinese patent medicine prepared from four Chinese medicinal materials, has good efficacy of soothing the liver and relieving depression, regulating qi and promoting blood circulation, regulating stomach and relieving pain, clinically treating chronic superficial gastritis (CSG) with disharmony between liver and stomach. However, its pharmacokinetics research is limited. Aim of the study: This study aims to explore the pharmacokinetic characteristics of JHT in normal rats and reveal its pharmacokinetic difference in normal, CSG and intestinal microbial disorder rats. Materials and methods: A quantitative analytical method was established for seven active ingredients in rat plasma using UPLC-TQ-MS/MS. After oral administrated four different doses of JHT, the plasma concentration of the seven ingredients were determined to assess pharmacokinetic characteristics in normal rats. Subsequently, Pharmacokinetic difference of four main ingredients was observed in normal, CSG, and fecal microbiota transplantation (FMT) rats after JHT-administrated. Simultaneously, the intestinal microbial changes of the three groups were evaluated by high-throughput sequencing technique. Finally, Spearman correlation analysis was applied to characterize the connection between the in vivo exposure of four ingredients and the disturbed gut microbiota. Results: A appropriate quantitative method was successfully established with the good linearity, precision, accuracy, extraction recovery, matrix effect as well as stability. In normal rats, all seven ingredients were rapidly absorbed. Tetrahydropalmatine, corydaline, costunolide, and rhamnosylvitexin demonstrated good exposure, while dehydrocorydaline, allocryptopine, and palmatine hydrochloride had low exposure. Additionally, tetrahydropalmatine, corydaline, and costunolide exhibited linear pharmacokinetics in terms of AUC0-t and Cmax when administrated 0.7~5.6 g/kg of JHT, wh

关键词： Pharmacokinetics

Zeroth-order algorithms for stochastic distributed nonconvex optimization

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

An Efficient Evolutionary Algorithm for High-Speed Train Rescheduling Under a Partial Station Blockage

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SSRN

SSRN 2023年

作者： Wang, Rongsheng Zhang, Qi Dai, Xuewu Yuan, Zhiming Zhang, Tao Ding, Shuxin Jin, Yaochu China Academy of Railway Sciences Corporation Limited Beijing100081 China Signal and Communication Research Institute China Academy of Railway Sciences Corporation Limited Beijing100081 China Train Operation Control Laboratory for High-Speed Railway National Engineering Research Center of System Technology for High-Speed Railway and Urban Rail Transit Beijing100081 China State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Faculty of Technology Bielefeld University BielefeldD-33615 Germany Department of Computer Science University of Surrey GuildfordGU2 7XH United Kingdom

This paper investigates the high-speed train rescheduling (HSTR) problem under a partial station blockage and proposes an efficient problem-specific strengthen elitist genetic algorithm (PS-SEGA) for HSTR. An HSTR model that is subject to train operation constraints is established to minimize the total train delay. The PS-SEGA framework consists of the following main steps. Firstly, a permutation-based encoding method is developed to define an efficient search space based on a train departure sequence. A decoding method is employed to output the rescheduled timetable and objective value based on the departure sequence. Moreover, a hybrid initialization method involving an efficient heuristic strategy (EHS) is put forward to accelerate the convergence speed of Evolutionary algorithms (EAs). Using problem-specific knowledge, EHS generates an efficient and feasible solution for the initial population. Finally, a restart strategy is presented to maintain genetic diversity. Compared with other advanced EAs and their improved variants also using the PS-SEGA framework, experimental results demonstrate the effectiveness of the proposed PS-SEGA for addressing HSTR scenarios under the partial station blockage. As for the scenarios that CPLEX can not obtain optimal solutions within 10 minutes, PS-SEGA can all provide quasi-optimal solutions in real-time. Furthermore, compared with the other two strategies (i.e., First-Scheduled-First-Served and EHS), PS-SEGA can find the best departure sequence that can output the timetable with a quasi-optimal solution. © 2023, The Authors. All rights reserved.

关键词： Genetic algorithms

Determination the installation efficiency of the evaporative air cooling in the greenhouse by temperature-moisture regime 1

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Determination the installation efficiency of the evaporative...

1st International Conference on Energetics, Civil and Agricultural Engineering, ICECAE 2020

作者： Anarbaev, A. Tursunov, O. Zakhidov, R. Kodirov, D. Vakhidov, U. Bozorov, E. Tuhtaeva, G. Babaev, A. Department of Power Supply and Renewable Energy Sources Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Tashkent100000 Uzbekistan School of Mechanical and Power Engineering Shanghai Jiao Tong University Shanghai200240 China Research Institute of Forestry Tashkent111104 Uzbekistan Department of Automation and Control of Technology Process Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Tashkent100000 Uzbekistan Department of Hydrology and Ecology Bukhara Branch of Tashkent Institute of Irrigation and Agricultural Mechanization Engineers Bukhara Uzbekistan

The results of theoretical studies and experiments of the developed exhaust ventilation system with direct evaporative air-cooling with using "wet mats"are given. It has shown sufficient efficiency with increasing quality of flower cutting in the summer months. The effect of moisture on the operation of this system was studied. It is established that the heat absorption capacity of air directly depends on its temperature and relative humidity. It is also determined that the temperature of leaves and flowers in summer is usually 2 ÷ 7 °C greater than the air temperature in the greenhouses. In an experimental greenhouse, according to the results of experiments, the effectiveness of the developed installation for evaporative cooling of its operation was determined. © Published under licence by IOP Publishing Ltd.

关键词： Greenhouses

Internal short circuit fault diagnosis for automotive lithium-ion batteries using an adaptive parameter identification model

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Measurement: Journal of the International Measurement Confederation 2025年 253卷

作者： Tao, Qian Wang, Yiming Tian, Engang Tao, Hongfeng Chen, Hongtian Chen, Yiyang School of Mechanical and Electrical Engineering Soochow University Suzhou215137 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China Key Laboratory of Advanced Process Control for Light Industry of Ministry of Education Jiangnan University Wuxi Jiangsu214122 China Department of Automation Shanghai Jiao Tong University Shanghai200240 China

This paper develops a model-based diagnostic method for internal short circuit (ISC) faults in lithium-ion batteries. This method utilizes a second-order equivalent circuit model (ECM) combined with a recursive least squares method with an adaptive forgetting factor for online parameter identification, with initial parameters optimized by a particle swarm optimization (PSO) algorithm. An extended Kalman filter (EKF) is then employed for state estimation to generate residuals, which are analyzed using the refined cumulative sum (CUSUM) statistical method to detect and diagnose ISC faults. Experimental results show that this method effectively identifies ISC faults in automotive power batteries under various initial state of charge (SOC) levels and fault-free conditions. At 100% initial SOC, fault detection times are 104 seconds for a 15Ω fault, 77 seconds for a 10Ω fault, and 27 seconds for a 1Ω fault;at 90% initial SOC, detection for a 10Ω fault takes 97 seconds, demonstrating high accuracy and robustness. © 2025 Elsevier Ltd

关键词： Lithium-ion batteries