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Data-Driven Learning and control with Event-Triggered Measurements

IEEE Transactions on Automatic control 2025年

作者： Feng, Shilun Shi, Dawei Chen, Tongwen Shi, Ling Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems MIIT Key Laboratory of Servo Motion System Drive and Control School of Automation Beijing100081 China University of Alberta Department of Electrical and Computer Engineering EdmontonABT6G 1H9 Canada Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Kowloon Hong Kong

Event-triggered control has attracted considerable attention for its effectiveness in resource-restricted applications. To make event-triggered control as an end-to-end solution, a key issue is how to effectively learn unknown system dynamics from event-triggered measurements and consequently, develop a learning-based event-triggered controller. Existing works learn system dynamics based on periodic time-triggered measurements, and it is yet to know how to learn a controller with performance guarantee based on event-triggered measurements. To address this issue, we consider the problem of learning an event-triggered state feedback controller for an unknown linear system based on event-triggered state measurements in this work. In particular, we first analyze the event-triggered measurements within a set-membership framework. We prove that the estimation error belongs to a bounded ellipsoid determined by the historical measurements and the event-triggering condition. Subsequently, we demonstrate that all admissible systems compatible with the collected data samples can be explicitly represented in the form of quadratic matrix inequalities using the state estimates. With the acquired set of admissible systems, a co-design problem for the data-driven controller and event-triggering condition is solved using the linear matrix inequality technique, with guaranteed closed-loop stability and L2-gain performance. Finally, numerical examples and comparisons are provided to illustrate the effectiveness of the proposed event-triggered learning and control approach. © 1963-2012 IEEE.

关键词： Networked control systems

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Decoupling Design Based on Active Disturbance Rejection control Approach for Near Space Vehicle Autopilot

Decoupling Design Based on Active Disturbance Rejection Cont...

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Chinese intelligent systems Conference, CISC 2019

作者： Li, Hui Yin, Zhide Li, Fengyi Liu, Hongyu Beijing Electro-Mechanical Institute Beijing100074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100074 China Beijing Institute of Control and Electronic Technology Beijing100038 China

ISBN: (纸本)9789813296855

A decoupled control approach based on linear active disturbance rejection control idea is proposed. The plant model, in which the coupling dynamics is as a part of disturbance, is established, and some virtual control variables are defined. Thus the original coupling plant is divided into some single-input single-output systems and the virtual control variables are willing to be determined by linear active disturbance rejection control method, and the real control variables are easily solved from virtual control variables according to their relationship. The approach is employed to a hypersonic near space vehicle lateral autopilot. The numerical simulations show that the proposed approach has good decoupling effectiveness and guarantees angle command signal tracking accuracy. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Disturbance rejection

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An adaptive fault detection strategy for Cz crystal growth process

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IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Mu, Lingxia Feng, Nan Zhang, Zhenhua Zhang, Youmin Zhang, Jian Xian University of Technology Crystal Growth Equipment and Systems Integration National Engineering Research Center Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xian710048 China University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Concordia University Department of Mechanical Industrial and Aerospace Engineering MontrealQCH3G 1M8 Canada

The monitoring and fault detection for the Czochralski (Cz) crystal growth process is important to ensure the quality of the produced mono-crystalline silicon. The Cz process is a typical multi-modes industrial process, which makes the detection difficult in distinguish the change caused by the fault or mode switching. In this paper, an adaptive fault detection strategy for Cz crystal growth process is proposed. Firstly, quality-related variables are selected from numerous process variables, based on which the training dataset is constructed. Then, a fault detection model is built based on slowly-varying feature and statics indicator. A model switching strategy and updating algorithm are designed to handle the abnormal situation caused by the mode switching or fault occurrence. Three representative experiments are conducted to verify the performance of the proposed strategy, including numerical cases, a publicly available dataset, and Cz crystal growth process from our laboratory. © 1963-2012 IEEE.

关键词： Crystal growth from melt

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Multi-source dynamic time series data processing method based on comprehensive weighted fusion

Multi-source dynamic time series data processing method base...

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12th International Conference on Quality, Reliability, Risk, Maintenance, and Safety Engineering (QR2MSE 2022)

作者： H. Geng F. Yuan B. Suo Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing People's Republic of China School of Mathematics Southwest Jiaotong University Chengdu People's Republic of China School of Information Engineering Southwest University of Science and Technology Mianyang People's Republic of China

Aiming at the fusion problem of multi-source heterogeneous dynamic data sources, based on the subjective and objective comprehensive weighting idea, an efficient multi-source dynamic data fusion algorithm is proposed. First, the outlier detection method based on linear regression model is used to preprocess the multi-source dynamic time series data. Then, determine the weight of the dynamic data. The prior weight of the data source is determined by the AHP method, cyclic scoring method, etc., and the posterior weight is determined according to the similarity between the time series data. Based on the Euclidean distance, a similarity measure between different data sources and a similarity measure between different dynamic data samples are constructed respectively. The former is used for the fusion of dynamic data standard deviation expectations, and the latter is used for the fusion of mean expectations. Finally, the comprehensive weight of each dynamic time series of each data source is obtained, and the comprehensive weighted fusion method is used to obtain the expected value and standard deviation of the dynamic response. The analysis of the calculation example shows that the proposed algorithm has higher computational efficiency than the method that treats dynamic data as several discrete static data.

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Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surface Vehicle in Marine Environment

Point Cloud Preprocessing on 3D LiDAR data for Unmanned Surf...

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2020 IEEE International Conference on Information technology, Big Data and Artificial Intelligence, ICIBA 2020

作者： Qi, Xianzhi Fu, Wenxing An, Pei Wu, Bingli Ma, Jie National Key Laboratory of Science and Technology on Multispectral Information Processing School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory Beijing100071 China

ISBN: (纸本)9781728152240

Point cloud preprocessing is still a challenging task in the marine environment, for it is difficult to filter out non-obstacle points while avoiding damage to the obstacle completeness. In this paper, we propose a novel data preprocessing method on 3D LiDAR data for the unmanned surface vehicle in the marine environment. It consists of two tasks: outlier removal and wake filtering. As the spatial resolution of LiDAR changes with distance, we exploit distance normalization on statistical outlier filter for robust outlier removal. Considering the gradient difference between wave wake and obstacle surface near the water, we define and calculate the vertical state of point cloud on the range image to obtain the pre-filtering point set, and then use the RANSAC method to filter out the wake points. Experiments on real data has demonstrated the effectiveness of the proposed algorithm both in terms of feasibility and accuracy. © 2020 IEEE.

关键词： Wakes

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Aircraft control Method Based on Deep Reinforcement Learning

Aircraft Control Method Based on Deep Reinforcement Learning

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Data Driven control and Learning systems (DDCLS)

作者： Yan Zhen Mingrui Hao Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing

ISBN: (数字)9781728159225

ISBN: (纸本)9781728159232

To address the failure of precise overload tracking and anti-interference caused by the difficulty of accurate modeling of a complex aircraft, the controller designing method based on deep reinforcement learning is studied. This paper trained the control network based on the Proximal Policy Optimization (PPO), studied the tracking control problem of the aircraft, and accurately tracked the typical command signals. Fixed-point simulation of the aircraft is performed, with results showing that, in presence of aircraft model parameter variation and external disturbance, the controller based on deep reinforcement learning can achieve accurate tracking of overload commands.

关键词： Aircraft Reinforcement learning Aerospace control Atmospheric modeling Aerodynamics Mathematical model Heuristic algorithms

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UAV Decision-making system Based on the Rough Set theory and the Optimal Genetic Algorithm

UAV Decision-making System Based on the Rough Set theory and...

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IEEE International Conference on Unmanned systems (ICUS)

作者： Wendi Sun Mingrui Hao Science and Technology on Complex System Control and Intelligent Agent Cooperative Laboratory Beijing

ISBN: (数字)9781728180250

ISBN: (纸本)9781728180267

Air combat decision-making is a critical issue in Unmanned Air Vehicle automatic combat. Precise and efficient maneuvering strategies are extremely important for the final victory. Quantitative research has been conducted on the maneuver strategy. In this study, a knowledge-based maneuver action library for air combat was established by the Rough Set Theory, which can help quick response to the battlefield situation. Since not all influence factors of battlefield situation are that significant and the computing source is finite, the rough set model was simplified to increase reaction rate. This paper introduced an advanced genetic algorithm to reduce the attributes of rough sets, taking the purity of each attribute into account, so as to make the condition attribute as close to 1 or 0 as possible. As a result, the reducing accuracy of the whole decision-making system is improved. The simulation results show that the rough set model built in this paper is efficient, feasible and reasonable, and the algorithm can support the air combat maneuver strategy decision system.

关键词： intelligent agents Conferences complex systems systems simulation Rough sets Power system dynamics intelligent control

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Robust Output Synchronization of Discrete-Time Linear-Time-Invariant Multi-agent systems Using Phase Tool

Robust Output Synchronization of Discrete-Time Linear-Time-I...

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European control Conference (ECC)

作者： Xin Mao Dan Wang Wei Chen Li Qiu School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Department of Mechanics and Engineering Science State Key Laboratory for Turbulence and Complex Systems Peking University Beijing China Southern University of Science and Technology Shenzhen China Hong Kong University of Science and Technology Hong Kong S.A.R. China

ISBN: (数字)9783907144107

ISBN: (纸本)9798331540920

In this paper, the output synchronization in large-scale discrete-time networks is examined by utilizing the novel phase tool, where the agent dynamics are allowed to be significantly heterogeneous. The synchronization synthesis problem is formulated and thoroughly investigated, with the goal of characterizing the allowable heterogeneity among the agents to ensure synchronization under a uniform controller. The solvability condition is provided in terms of the phases of the residue matrices of the agents at the persistent modes. When the condition is satisfied, a design procedure is given, producing a low-gain synchronizing controller. Numerical examples are given to illustrate the results.

关键词： Sufficient conditions Europe Heterogeneous networks Synchronization Multi-agent systems

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Can Digital Intelligence and Cyber-Physical-Social systems Achieve Global Food Security and Sustainability?

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IEEE/CAA Journal of Automatica Sinica 2023年第11期10卷 2070-2080页

作者： Yanfen Wang Mengzhen Kang Yali Liu Juanjuan Li Kai Xue Xiujuan Wang Jianqing Du Yonglin Tian Qinghua Ni Fei-Yue Wang College of Resources and Environment University of Chinese Academy of SciencesBeijing 100049 Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408 State Key Laboratory of Tibetan Plateau Earth System Environment and ResourcesInstitute of Tibetan Plateau ResearchChinese Academy of SciencesBeijing 100101China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190 School of Artificial Intelligence University of Chinese Academy of SciencesBeijing 100049China School of Grassland Science Beijing Forestry UniversityBeijing 100083China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of SciencesBeijing 100190China State Key Laboratory of Plateau Ecology and Agriculture Qinghai UniversityXining 810016 Key Laboratory of Adaptation and Evolution of Plateau Biota Northwest Institute of Plateau BiologyChinese Academy of SciencesXining 810001 Binzhou Institute of Technology Weiqiao-UCAS Science and Technology ParkBinzhou 256606China Beijing Yanshan Earth Critical Zone National Research Station University of Chinese Academy of SciencesBeijing 101408China Department of Engineering Science Faculty of Innovation EngineeringMacao University of Science and TechnologyMacao 999078 State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of AutomationChinese Academy of Sciences(CASIA)Beijing 100190China Faculty of Innovation Engineering Macao University of Science and TechnologyMacao 999078 Beijing Engineering Research Center of Intelligent Systems and Technology Chinese Academy of SciencesBeijing 100098 State Key Laboratory for Management and Control of Complex Systems Chinese Academy of SciencesBeijing 100190China IEEE

Plants sequester carbon through photosynthesis and provide primary productivity for the ecosystem. However, they also simultaneously consume water through transpiration, leading to a carbon-water balance relationship. Agricultural production can be regarded as a form of carbon sequestration *** the perspective of the natural-social-economic complex ecosystem, excessive water usage in food production will aggravate regional water pressure for both domestic and industrial purposes. Hence, achieving a harmonious equilibrium between carbon and water resources during the food production process is a key scientific challenge for ensuring food security and sustainability. Digital intelligence(DI) and cyber-physical-social systems(CPSS) are emerging as the new research paradigms that are causing a substantial shift in the conventional thinking and methodologies across various scientific fields, including ecological science and sustainability studies. This paper outlines our recent efforts in using advanced technologies such as big data, artificial intelligence(AI), digital twins, metaverses, and parallel intelligence to model, analyze, and manage the intricate dynamics and equilibrium among plants, carbon, and water in arid and semiarid ecosystems. It introduces the concept of the carbon-water balance and explores its management at three levels: the individual plant level, the community level, and the natural-social-economic complex ecosystem level. Additionally, we elucidate the significance of agricultural foundation models as fundamental technologies within this context. A case analysis of water usage shows that, given the limited availability of water resources in the context of the carbon-water balance, regional collaboration and optimized allocation have the potential to enhance the utilization efficiency of water resources in the river basin. A suggested approach is to consider the river basin as a unified entity and coordinate the relationship between the

关键词： Carbon-water balance decision-support digital intelligence(DI) foundation models planning

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Performance Assessment for Leader-following UAV Formation via Belief Rule Base

Performance Assessment for Leader-following UAV Formation vi...

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Fully Actuated system Theory and Applications (CFASTA), Conference on

作者： Haoran Zhang Mingrui Hao Ruohan Yang Keyuan Yue Zhichao Feng School of Computer Science and Information Engineering Harbin Normal University Harbin P. R. China Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory School of Electronics and Information Northwestern Polytechnical University Xi’an P. R. China Department of Missile Engineering Rocket Force University of Engineering Xi’an P. R. China

The article puts focus on the the problem of performance assessment for UAV formation with leader-following structure and switching communication topology in the presence of unknown exogenous perturbations. First, two time-varying indicators are devised on the basis of the regulated outputs of the followers. Then, a trainable performance assessment model is constructed by means of belief rule base expert system (BRB) with the two time-varying indicators as the inputs and the assessment utility as the final output. At last, relevant simulation experiments are conducted to validate the practicability of the established performance assessment model for leader-following UAV formation subject to switching communication topology and unknown external perturbations.

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