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Enhanced Tube-Based Event-Triggered Stochastic Model Predictive control With Additive Uncertainties

IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 596-605页

作者： Chenxi Gu Xinli Wang Kang Li Xiaohong Yin Shaoyuan Li Lei Wang the School of Control Science and Engineering Shandong University IEEE the School of Electronic and Electrical Engineering University of Leeds the Qingdao University of Science and Technology the Department of Automation Shanghai Jiao Tong University the Key Laboratory of System Control and Information Processing Ministry of Education of China

This paper proposes an event-triggered stochastic model predictive control for discrete-time linear time-invariant(LTI) systems under additive stochastic disturbances. It first constructs a probabilistic invariant set and a probabilistic reachable set based on the priori knowledge of system *** with enhanced robust tubes, the chance constraints are then formulated into a deterministic form. To alleviate the online computational burden, a novel event-triggered stochastic model predictive control is developed, where the triggering condition is designed based on the past and future optimal trajectory tracking errors in order to achieve a good trade-off between system resource utilization and control performance. Two triggering parameters σ and γ are used to adjust the frequency of solving the optimization problem. The probabilistic feasibility and stability of the system under the event-triggered mechanism are also examined. Finally, numerical studies on the control of a heating, ventilation, and air conditioning(HVAC) system confirm the efficacy of the proposed control.

关键词： Event-triggered mechanism heating, ventilation, and air conditioning (HVAC) control probabilistic reachable set stochastic model predictive control

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controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Active Front-Steering electronic Stability control system Based on a Safety-Critical control Extension

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-11页

作者： Alves, Jorge Augusto Vasconcelos Angelico, Bruno Augusto Department of Electronic Engineering Federal University of Technology—Paraná Toledo Paraná Brazil Department of Telecommunications and Control Engineering Escola Politécnica University of São Paulo São Paulo Brazil

This article presents an electronic stability control system that uses active front steering to keep the system state constrained to a subset of the system's lateral stability region with absolutely no possibility of failure and safety-critical control based on control barrier functions to obtain the control signal. We propose a method that maximizes the safe set to the largest convex subset of the lateral stability region, rendering the closed-loop system least invasive to the driver's commands. To achieve this, we introduce a safety-critical control formulation that considers exponential control-dependent barrier or Lyapunov functions of arbitrary relative degree. We validate the proposal through commercial vehicle simulation software. IEEE

关键词： Lyapunov methods

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Optimal Cyber Attack Strategy Using Reinforcement Learning Based onCommon Vulnerability Scoring system

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Computer Modeling in engineering & Sciences 2024年第11期141卷 1551-1574页

作者： Bum-Sok Kim Hye-Won Suk Yong-Hoon Choi Dae-Sung Moon Min-Suk Kim Department of Electronic Information System Engineering Sangmyung UniversityCheonan31066Republic of Korea Department of Human Intelligence&Robot Engineering Sangmyung UniversityCheonan31066Republic of Korea Intelligent Convergence Research Laboratory Electronics and Telecommunications Research InstituteDaejeon34129Republic of Korea

Currently,cybersecurity threats such as data breaches and phishing have been on the rise due to the many differentattack strategies of cyber attackers,significantly increasing risks to individuals and *** technologies such as intrusion detection have been developed to respond to these cyber ***,advanced integrated cybersecurity that incorporates Artificial Intelligence has been the *** this paper,wepropose a response strategy using a reinforcement-learning-based cyber-attack-defense simulation tool to addresscontinuously evolving cyber ***,we have implemented an effective reinforcement-learning-basedcyber-attack scenario using Cyber Battle Simulation,which is a cyber-attack-defense *** scenarioinvolves important security components such as node value,cost,firewalls,and ***,we applieda new vulnerability assessment method based on the Common Vulnerability Scoring *** approach candesign an optimal attack strategy by considering the importance of attack goals,which helps in developing moreeffective response *** attack strategies are evaluated by comparing their performance using a variety ofReinforcement Learning *** experimental results show that RL models demonstrate improved learningperformance with the proposed attack strategy compared to the original *** particular,the success rateof the Advantage Actor-Critic-based attack strategy improved by 5.04 percentage points,reaching 10.17%,whichrepresents an impressive 98.24%increase over the original ***,the proposed method canenhance security and risk management capabilities in cyber environments,improving the efficiency of securitymanagement and significantly contributing to the development of security systems.

关键词： Reinforcement learning common vulnerability scoring system cyber attack cyber battle simulation

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Characteristics of controlled Bridge Circuit and Its Application in Magnetic Field Induction Measurement

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Tsinghua Science and Technology 2024年第4期29卷 1105-1117页

作者： Yanchu Li Qingqing Ding Mingchen Yan Jiyao Wang Jun Xu Xinzhou Dong Department of Electrical Engineering Tsinghua UniversityBeijing 100084China State Key Laboratory of Control and Simulation of Power System and Generation Equipments Tsinghua UniversityBeijing 100084China School of Electrical and Electronic Engineering North China Electric Power UniversityBeijing 100096China

The article designs a new type of bridge circuit with a controlled source—when the resistance on the bridge arm of the controlled source bridge circuit meets the bridge balance condition, and the bridge branch contains only one Current-controlled Current Source (CCCS), a Voltage-controlled Current Source (VCCS), a Current-controlled Voltage Source (CCVS), or a Voltage-controlled Voltage Source (VCVS), the circuit is called a controlled bridge circuit, which has the characteristics of bridge balance. Due to the relationship between the controlled source and the bridge arm, the sensitivity of the components on the bridge is higher mathematically and logically. When applied to measurement, engineering, automatic control, and other fields, the controlled bridge circuit has higher control ac-curacy. Mathematical derivation and simulation results prove the correctness of the bridge balance conclusion and the special properties of this bridge when applied to the measurement field.

关键词： bridge bircuit bridge circuit applications bridge balanced condition controlled bridge circuit magnetic field induction measurement

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Improved Artificial Neural Networks Based Whale Optimization Algorithm

Iraqi Journal for Computer Science and Mathematics

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Iraqi Journal for Computer Science and Mathematics 2023年第3期4卷 195-202页

作者： Ibrahem Alhayali, Royida A. Aladamey, Mostafa Khaled Abd Alrahman Subhi, Mohammed Rashid Mohammed, Mostafa Abdulghafoor Amir, Amiza Abdalkareem, Zahraa A. Department of Architecture Engineering College of Engineering University of Diyala Diyala Iraq Alimam Aladham University College Baghdad Iraq Department of Petroleum System Control Engineering College of Petroleum Processes Engineering Tikrit University Iraq Faculty of Engineering & Electronic Engineering Technology University Malaysia Malaysia

Owing to the increasing interest in artificial neural networks (ANNs) across various fields of study, many studies have focused on enhancing their performance through the utilisation of different learning algorithms. This study examines the use of the Whale Optimization Algorithm (WOA) as a training algorithm to improve the classification accuracy of ANNs. To achieve a high level of classification accuracy with ANN models, it is imperative to ensure that the model is appropriately designed in terms of the employed structure, training algorithm and activation function. In this work, WOA was adopted to train ANN models using 10 well-known datasets sourced from the UCI machine learning repository. The classification accuracy of a WOA-trained ANN was compared with that of a backpropagation-trained ANN, and the results showed that the WOA-trained ANN exhibited superior performance. © 2023 College of Education, Al-Iraqia University. All rights reserved

关键词： Neural networks

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Process Monitoring Based on Temporal Feature Agglomeration and Enhancement

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IEEE/CAA Journal of Automatica Sinica 2023年第3期10卷 825-827页

作者： Xiao Liang Weiwu Yan Yusun Fu Huihe Shao Department of Automation the School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China Department of Automation the School of Electronic Information and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240 Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

Dear Editor,This letter proposes a process-monitoring method based on temporal feature agglomeration and enhancement,in which a novel feature extractor called contrastive feature extractor(CFE)extracts the temporal and relational features among process *** the feature representations are enhanced by maximizing the separation among different classes while minimizing the scatter within each class.

关键词： among while letter

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Time-Variant Radio Map Reconstruction with Optimized Distributed Sensors in Dynamic Spectrum Environments

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IEEE Internet of Things Journal 2025年第12期12卷 20927-20941页

作者： Gao, Qianhao Zhu, Qiuming Lin, Zhipeng Mathiopoulos, P. Takis Zhao, Yi Huang, Yang Wang, Jie Wu, Qihui Nanjing University of Aeronautics and Astronautics Key Laboratory of Dynamic Cognitive System of Electromagnetic Spectrum Space College of Electronic and Information Engineering Nanjing211106 China National and Kapodistrian University of Athens Department of Informatics and Telecommunications Athens15784 Greece

Radio environment maps (REMs) have been used to visualize the information of invisible electromagnetic spectrum. Although in the past there have been many research activities dealing with the reconstruction of static REMs, they did not consider the time variation of the dynamic spectrum operational environment. In this paper, we present a novel time-variant REM reconstruction methodology based on sparsely distributed sensors which jointly considers sensor layout optimization, propagation model improvement, and missing spectrum data recovery. Firstly, a low complexity and computationally efficient method is proposed to improve the sampling efficiency. The proposed method jointly employs the gradient descent method and an upgraded greedy matching algorithm to optimize the sensor positions even when large-scale scenarios are considered. Then, by using the sampled spectrum data obtained from these sensors, the accuracy of commonly employed propagation models is improved and subsequently used to construct a channel dictionary for such time-varying environments. By exploring the heterogeneity of dynamic spectrum operational environments, an improved optimal reconstruction method is designed to recover the spectrum data using their spatial-temporal correlation. By considering a typical university campus environment as a case study, simulation and measurement data are obtained to reconstruct the time-variant REM. Through the simulation data, the reconstruction performance results are compared with those obtained from other state-of-the-art methods showing that the proposed methodology outperforms the others with respect to the sampling scheme and missing rate. Additionally, field measurement results have demonstrated that the proposed approach can effectively reconstruct time-variant REMs under dynamic scenarios. © 2014 IEEE.

关键词： Compressed sensing

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AIoT for Aircraft Final Assembly:An Intelligent and Collaborative Framework

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Journal of Communications and Information Networks 2024年第3期9卷 262-276页

作者： Cheng Ren Xiaojing Wen Xinping Guan Cailian Chen Yehan Ma Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the advent of artificial intelligence of things(AIoT)technologies has introduced advancements in certain AFAL scenarios,systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence(AI)technologies remain significant *** address these challenges,we propose the intelligent and collaborative aircraft assembly(ICAA)framework,which integrates AI technologies within a cloud-edge-terminal *** ICAA framework is designed to support AI-enabled applications in the AFAL,with the goal of improving assembly efficiency at both individual and multiple process *** analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these *** three-tier ICAA framework consists of the assembly field,edge data platform,and assembly cloud platform,facilitating the collection of heterogeneous terminal data and the deployment of AI *** framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple *** provide detailed descriptions of how AI functions at each level of the ***,we apply the ICAA framework to a real AFAL,focusing explicitly on the flight control system testing *** practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.

关键词： intelligent aircraft final assembly line AIoT cloud-edge-terminal framework design

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Learning-based MPC of sampled-data systems with partially unknown dynamics

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ISA Transactions 2025年 162卷 64-74页

作者： Han, Seungyong Guo, Xuyang Kommuri, Suneel Kumar Department of Mechanical System Engineering Jeonbuk National University 567 Baekje-daero Deokjin-gu Jeonju54896 Korea Republic of Department of Control Science and Engineering Tongji University Shanghai China Department of Electrical and Electronic Engineering Xi'an Jiaotong-Liverpool University Suzhou215123 China

In this paper, a novel learning-based model predictive control (LMPC) method is proposed for sampled-data control systems with partially unknown dynamics. Many real-world processes are subject to time-varying parameters and irregular data sampling, making accurate modeling and stability guarantees extremely challenging. To address this, the proposed method uses a neural ordinary differential equation (NODE) to learn unknown time-varying parameter dynamics from irregularly observed data. This learned model is then integrated into the sampled-data MPC framework. In particular, the LMPC method guarantees the system's ultimate boundedness by deriving conditions based on the Gronwall–Bellman inequality. Finally, two practical examples illustrate the applicability of the LMPC method to real-world systems and demonstrate its quantitative stability analysis. © 2025

关键词： Sampled data control systems

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