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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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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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Light-Weight Low-Cost Drive control Modules Design and Mass Production Research in SAR Satellites 4

Light-Weight Low-Cost Drive Control Modules Design and Mass ...

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4th China International SAR Symposium, CISS 2023

作者： Liu, Pengfei Ma, Xiaoyan Wang, Jun Qian, Weixin Feng, Zhengkang Aerospace System Engineering Shanghai Department of Electrical Control Shanghai China Shanghai Aerospace Electronic Technology Institute Department of Radar System Shanghai China

ISBN: (纸本)9798350307955

In order to adapt to the development trend of light-weight and low-cost SAR (Synthetic Aperture Radar) satellites, products of drive control modules, especially drive control modules of SAR antenna deployment mechanism and solar array, are required to be light-weight and low-cost. At the level of product design, the mechanical structure of light-weight drive control module and low-cost hardware circuit design are given. The design scheme mainly involves the electromechanical integration interface of the drive control module and the drive mechanism, and the protection and reinforcement of the industrial components of the hardware circuit. At the level of product production, firstly, the product is designed according to modularization. Secondly, a series of standard systems from production to test are established. Finally, automatic production lines and automatic testing equipment are used for mass production and testing of products. The above design and production optimization measures reduce the weight and cost of drive control module products. The light-weight and low-cost drive control modules is conducive to carrying more payloads on SAR satellites and networking between satellites. © 2023 IEEE.

关键词： Synthetic aperture radar

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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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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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Abnormal Data Identification and Reconstruction Based on Wind Speed Characteristics

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CSEE Journal of Power and Energy systems 2025年第2期11卷 612-622页

作者： Mao Yang Tian Peng Wei Zhang Xin Su Chao Han Fulin Fan Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of EducationNortheast Electric Power UniversityJilin 132012China Department of Electronic and Electrical Engineering University of StrathclYdeGlasgow G11XWUnited Kingdom

High availability of wind power data is the basis for wind power research, but there are a large number of abnormal data in actual collected data, which seriously affects analysis of wind power law and reduces prediction accuracy. Measured power data of wind farm are analyzed, influence of wind speed fluctuation characteristics on wind power is discussed, and abnormal points are identified for data of different wind types. The Cluster-Based Local Outlier Factor (CLOF) algorithm based on K-means is used to identify outlier abnormal points, and conditional constraints based on physical background are used to identify accumulation abnormal points. Reconstructed data segment is divided according to fluctuation of wind speed. The Bidirectional Gate Recurrent Unit (BiGRU) model with wind speed as input reconstructs fluctuation segment data, and bi-directional weighted random forest model reconstructs stationary segment data. Based on analysis of measured data of a wind farm, results show the method can effectively identify various abnormal data, and complete high-quality reconstruction of data, thereby improving accuracy of wind power prediction.

关键词： Abnormal data bidirectional weighted random forest BiGRU CLOF reconstruction wind power prediction wind speed characteristics

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Perturbation Event Oriented Dynamic Task Scheduling Algorithm for Parallel Testing of control systems

Perturbation Event Oriented Dynamic Task Scheduling Algorith...

引用

2024 IEEE International Conference on Sensing, Diagnostics, Prognostics, and control, SDPC 2024

作者： Chen, Jingyi Wang, Shenhang Tong, Xiaoxuan Xiang, Gang Yu, Yang Zhan, Ziyuan School of Electronic and Information Engineeer Harbin Institute of Technology Harbin China Beijing Aerospace Automatic Control Institute System Design Department Beijing China Beijing Aerospace Automatic Control Institute Beijing China Beijing Aerospace Automatic Control Institute Department of System Engineering Beijing China

ISBN: (纸本)9798350388855

Task scheduling algorithms are key to research and practice in parallel testing techniques, especially in control system applications. The complexity of control system testing requires higher scheduling efficiency. However, perturbation events caused by test equipment problems, data transmission obstacles, or task changes are almost unavoidable and may reduce the scheduling effectiveness or even lead to system crashes. Therefore, in this paper, based on the analysis of the dynamic test scheduling model, a disturbance factor is designed to judge the urgency of disturbance events for evaluating the dynamic scheduling cycle. On this basis, based on the comprehensive rescheduling index, a suitable adjustment strategy is selected to formulate the dynamic test scheduling scheme. The experimental results show that the algorithm proposed in this paper can achieve fast response capability for different disturbance events and exhibit good adaptivity. © 2024 IEEE.

关键词： Scheduling algorithms

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Grey-box Modeling for IPMSMs Considering Nonlinearity of Torque and Current 50

Grey-box Modeling for IPMSMs Considering Nonlinearity of Tor...

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50th Annual Conference of the IEEE Industrial electronics Society, IECON 2024

作者： Ohnuma, Takumi Watanabe, Keiya Mano, Shou Department of Electronic Control System Engineering National Institute of Technology Numazu College Shizuoka Japan Multidisciplinary Engineering Course National Institute of Technology Numazu College Shizuoka Japan

ISBN: (纸本)9781665464543

This paper proposes a grey-box model for IPMSMs (Interior Permanent Magnet Synchronous Motors) that accounts for the nonlinear relationship between currents and torque directly. IPMSMs with high power density typically exhibit complex torque characteristics due to the effects of magnetic saturation and spatial harmonics, necessitating the introduction of various nonlinear compensation tables based on magnetic field analysis to ensure control performance. However, inputting data without considering the physical properties can lead to many variables and increased memory usage, which does not necessarily improve control performance. Consequently, models representing magnetic saturation characteristics with a reduced number of parameters, as well as torque estimation methods, are under investigation. Moreover, advancements in high-precision and rapid-response torque sensors, along with magnetic field analysis technologies, have enabled detailed offline measurements of IPMSM torque, with promising prospects for control applications. In this study, we propose an Extended Torque Coefficient (ETC) matrix to express the grey-box model for control purposes, utilizing accurate map data reflective of the actual machine. In addition, the proposed model can be applied to calculate torque gradient in the current vector space, which is maximize torque control performance, while maintaining the ETC matrix. © 2024 IEEE.

关键词： Permanent magnets

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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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