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IEEE Transactions on Artificial Intelligence 2024年第9期5卷 4620-4634页

作者： Wang, Yan Sun, Xiaoyan Zhang, Yong Gong, Dunwei Hu, Hejuan Zuo, Mingcheng China University of Mining and Technology School of Information and Control Engineering Jiangsu Xuzhou221116 China Qingdao University of Science and Technology College of Automation and Electronic Engineering Shandong Qingdao266061 China China University of Mining and Technology Artificial Intelligence Research Institute Jiangsu Xuzhou221116 China

It is very challenging to autonomously generate algorithms suitable for constrained multiobjective optimization problems due to the diverse performance of existing algorithms. In this article, we propose a linear regression (LR)-based autonomous intelligent optimization method. It first extracts typical features of a constrained multiobjective optimization problem by focused sampling to form a feature vector. Then, a LR model is designed to learn the relationship between optimization problems and intelligent optimization algorithms (IOAs). Finally, the trained model autonomously generates a suitable IOA by inputting the feature vector. The proposed method is applied to six constrained multiobjective benchmark test sets with various characteristics and compared with seven popular optimization algorithms. The experimental results verify the effectiveness of the proposed method. In addition, the proposed method is used to solve the operation optimization problems of an integrated coal mine energy system, and the experimental results show its practicability. © 2020 IEEE.

关键词： Feature extraction

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1-Hour Ahead Wind Power Prediction Based on Multi-model Fusion Strategy 19th

1-Hour Ahead Wind Power Prediction Based on Multi-model Fusi...

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19th Annual Conference of China Electrotechnical Society, ACCES 2024

作者： Zhang, Tengyu Di, Shuai Wang, Xu Zhu, Deyu Ren, Xiaochen School of Electrical Engineering and Automation Harbin Institute of Technology Heilongjiang Harbin China Institute of Thermal Control Technology Datang Northeast Electric Power Test and Research Institute Co. Ltd. Jilin Changchun China

ISBN: (纸本)9789819613861

The accuracy of wind power prediction is of great significance for optimizing power system scheduling and improving power output stability. In order to solve the established difficulties in wind prediction, a prediction method combining multiple models is proposed with the aim of realizing a high-precision wind prediction strategy up to 1 hour in advance. Firstly, the raw wind power data is preprocessed. Secondly, the comprehensive feature se-lection (CFS) algorithm is used to calculate the sum of the importance of each feature variable, and the input set of asynchronous eldest child models corresponding to the target feature is selected. Then, the adaptive noise complete set empirical mode decomposition algorithm (CEEMDAN) is used to decompose the wind power sequence, and each component after decomposition is modeled separately. The comparative analysis of a series of experimental methods shows that the method proposed in this study demonstrates excellent prediction accuracy and stable performance in the field of multi-step wind energy prediction. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Wind forecasting

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Application of Active Disturbance Rejection control with Known Improved Bouc-Wen Modeling Items in Microflow control 42

Application of Active Disturbance Rejection Control with Kno...

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42nd Chinese control Conference, CCC 2023

作者： Wang, Yuheng Zhu, Jinyi Liu, Xuhui Long, Jun Wang, Xudong Wang, Tao Wang, Bo School of Automation Beijing Institute of Technology Beijing100081 China Beijing Institute of Control Engineering China Academy of Space Technology Beijing100094 China

ISBN: (纸本)9789887581543

For micro-newton-scale thrust systems in drag-free satellite, cold gas thrust and field ionization thrust usually require fast and stable flow control. In order to achieve high precision, low noise and fast response thrust control, stable and continuous flow control is the premise. At present, piezoelectric proportional valve composed of piezoelectric actuator and needle valve is widely used in flow control. However, the nonlinear characteristics of piezoelectric proportional valve such as hysteresis and creep are the main factors of internal disturbance in flow control system. Therefore, an active disturbance rejection control algorithm based on the improved Bouc-Wen (B-W) model is proposed in this paper. Firstly, the theoretical model and the phenomenological B-W model are combined to establish the improved B-W model, and then the model is applied to the active disturbance rejection control (ADRC) algorithm with known modeling corrections. Finally, simulation experiments are carried out. The simulation results show that the proposed method can effectively compensate and suppress nonlinear disturbances such as hysteresis and creep of piezoelectric proportional valve, thus improving the accuracy of flow control. © 2023 Technical Committee on control Theory, Chinese Association of automation.

关键词： Piezoelectric actuators

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Power System Operation Optimization Method of Combined Renewable Energy with Thermoelectric Units Considering Exergy Efficiency 6

Power System Operation Optimization Method of Combined Renew...

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6th International Conference on Energy Systems and Electrical Power, ICESEP 2024

作者： Shi, Jiakui Zongjie, L. Li, Menghui Xie, Hua Peng, E. Wan, Jie School of Electrical Engineering & Automation Harbin Institute of Technology Harbin China School of Energy Science and Engineering Harbin Institute of Technology Harbin China Guoneng Credit Control Interconnection Technology Co. Ltd Beijing China

ISBN: (纸本)9798350353563

In northern China, the demand for winter heating is substantial, leading to a high proportion of heating loads that reduce the flexibility of the power grid in regulating power generation. The pure condensing unit will enter the normal operation condition of ultra-low load (sometimes even undergoing daily start and stop cycles). The economic consumption method of light, electricity, and heat balance of combined heat and power units is proposed. Based on considering the exergy efficiency, the new energy is transferred to the heat load of the heating network to break the fixed mode of 'fixing electricity by heat, 'reduce the light abandonment rate, and improve the operation economy of the system. It has certain reference significance for promoting the safe and efficient consumption and utilization of local large-scale renewable energy. © 2024 IEEE.

关键词： Cogeneration unit economic operation efficiency renewable energy

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Adaptive Prescribed-Time Neural control of Nonlinear Systems via Dynamic Surface Technique

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第10期5卷 4948-4958页

作者： Wang, Ping Yu, Chengpu Lv, Maolong Zhao, Zilong Beijing Institute of Technology School of Automation Beijing100081 China Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China Air Force Engineering University College of Air Traffic Control and Navigation Xi'an710051 China Delft University of Technology Faculty of Electrical Engineering Mathematics and Computer Science Delft2628 CD Netherlands

The adaptive practical prescribed-time (PPT) neural control is studied for multiinput multioutput (MIMO) nonlinear systems with unknown nonlinear functions and unknown input gain matrices. Unlike existing PPT design schemes based on backstepping, this study proposes a novel PPT control framework using the dynamic surface control (DSC) approach. First, a novel nonlinear filter (NLF) with an adaptive parameter estimator and a piecewise function is constructed to effectively compensate for filter errors and facilitate prescribed-time convergence. Based on this, a unified DSC-based adaptive PPT control algorithm, augmented with a neural networks (NNs) approximator, is developed, where NNs are used to approximate unknown nonlinear system functions. This algorithm not only addresses the inherent computational complexity explosion associated with traditional backstepping methods but also reduces the constraints on filter design parameters compared to the DSC algorithm that relies on linear filters. The simulation showcases the effectiveness and superiority of the devised scheme by employing a two-degree-of-freedom robot manipulator. © 2024 IEEE.

关键词： Flexible manipulators

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Resilient time-varying formation optimal tracking for heterogeneous multi-agent systems with coupled constraints

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IEEE Transactions on automation Science and engineering 2025年 22卷 15274-15285页

作者： Su, Lingfei Lin, Zhi Hua, Yongzhao Shi, Zhexin Dong, Xiwang Lu, Jinhu Wang, Danwei Beihang University School of Artificial Intelligence Institute of Artificial Intelligence Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University School of Automation Science and Electrical Engineering Shenyuan Honors College Beijing100191 China Beijing100191 China Science and Technology on Aircraft Control Laboratory Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Zhongguancun Laboratory Beijing100094 China Nanyang Technological University School of Electrical and Electronic Engineering 639798 Singapore

Formation constrained optimal tracking problems for heterogeneous multi-agent systems under Byzantine attacks are studied. The objective of the honest agents, unaffected by Byzantine attacks, is to find optimal trajectories that minimize the cumulative local cost functions of all honest agents, while simultaneously satisfying the cumulative local inequality constraints and maintaining the formation configuration. A distributed resilient formation tracking controller utilizing preview control and primal-dual strategy is proposed without requiring each agent to know which agents are affected by Byzantine attacks. The performance of the proposed algorithm is analyzed in terms of the upper bounds of dynamic regret and constraint violations. Numerical simulations and experiments, involving one unmanned aerial vehicle and four unmanned ground vehicles, are performed to verify the effectiveness of the obtained results. © 2004-2012 IEEE.

关键词： Cost functions

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Reinforcement Learning Behavioral control for Nonlinear Autonomous System

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1561-1573页

作者： Zhenyi Zhang Zhibin Mo Yutao Chen Jie Huang the College of Electrical Engineering and Automation Fuzhou UniversityFuzhou 350108 the Key Laboratory of Industrial Automation Control Technology and Information Processing Education Department of Fujian ProvinceFuzhou 350108 G+Industrial Internet Institute Fuzhou UniversityFuzhou 350108China

Behavior-based autonomous systems rely on human intelligence to resolve multi-mission conflicts by designing mission priority rules and nonlinear *** this work,a novel twolayer reinforcement learning behavioral control(RLBC)method is proposed to reduce such dependence by trial-and-error ***,in the upper layer,a reinforcement learning mission supervisor(RLMS)is designed to learn the optimal mission *** with existing mission supervisors,the RLMS improves the dynamic performance of mission priority adjustment by maximizing cumulative rewards and reducing hardware storage demand when using neural *** the lower layer,a reinforcement learning controller(RLC)is designed to learn the optimal control *** with existing behavioral controllers,the RLC reduces the control cost of mission priority adjustment by balancing control performance and *** error signals are proved to be semi-globally uniformly ultimately bounded(SGUUB).Simulation results show that the number of mission priority adjustment and the control cost are significantly reduced compared to some existing mission supervisors and behavioral controllers,respectively.

关键词： Behavioral control mission supervisor nonlinear autonomous system reinforcement learning

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eVTOL Performance Analysis: A Review From control Perspectives

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年第5期9卷 1-13页

作者： Su, Jiangcheng Huang, Hailong Zhang, Hong Wang, Yutong Wang, Fei-Yue Department of Aeronautical and Aviation Engineering Hong Kong Polytechnic University Hong Kong China Co. Ltd. Guangzhou China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Electric Vertical Takeoff and Landing (eVTOL) aircraft has gained significant attention as a basic element of urban air mobility (UAM), a potential solution for urban transportation challenges using low-altitude urban airspace. Ensuring the safe operation of eVTOL is crucial for UAM applications, which are related to various professional fields such as aerodynamics, control, structures, and power systems. This article systematically analyzes the characteristics of different design configurations, including multi-rotor, lift+cruise, and tilt-rotor types of eVTOL. The advantages and limitations of each type of eVTOL are analyzed. After that, the overall design problems are analyzed, and challenges of eVTOL control system design are discussed from aspects of overall control structure and subsystems, such as controller, sensors, actuators, and command generator. This article tries to fill the gap in the eVTOL design from a control perspective and provides some resolutions for the eVTOL application. IEEE

关键词： Air mobility

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Psychomotor intervention through serious games in children and adolescents with autism spectrum disorder using a therapeutic robot

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Research on Biomedical engineering 2024年第3-4期40卷 485-497页

作者： da Luz Schreider, Sheila de Souza, Josiany Carlos da Silva Freitas, Éberte Valter Panceri, João Antonio Campos de Oliveira Caldeira, Eliete Maria Bastos-Filho, Teodiano Freire Av. Marechal Campos 1468 Maruipe Vitoria29047-105 Brazil Vitoria Brazil Vitoria Brazil Automation and Control Engineering Department Federal Institute of Espirito Santo Av. Filogônio Peixoto 2220 Aviso Linhares Brazil

Introduction: The autism spectrum disorder (ASD) is a neurodevelopmental disorder, characterized by an atypical neuropsychomotor development and communication. Methodology: In this work, a socially assistive robot termed MARIA T21 (Mobile Autonomous Robot for Interaction with Autistics and Trisomy 21) was used for interaction and application of serious games to children with ASD. The sample was composed of two groups: the first one with seven children with ASD, who had ten sessions with the robot at the Association of Friends of Autistics from Espirito Santo State (AMAES) in Vitoria, Brazil;and second group composed of four children with ASD, who had four sessions with the robot at the Association of Parents and Friends of Exceptional People (APAE) in Vila Velha, Brazil. The protocol was composed of four serious games, which stimulated postural balance, proprioception, and motor coordination. Results and conclusions: The utilization of the robot and serious games proved to be an important therapy tool, providing the children with playful activities, increasing their engagement, and providing them with a greater interaction between body and mind. In the evaluation of the psychomotor profile through the Psychomotor Battery by Victor da Fonseca, both groups had a statistically significant difference before and after the psychomotor intervention. © The Author(s), under exclusive licence to The Brazilian Society of Biomedical engineering 2024.

关键词： Serious games

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Adaptive control of Discrete-time Nonlinear Systems Using ITF-ORVFL

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IEEE/CAA Journal of Automatica Sinica 2022年第3期9卷 556-563页

作者： Xiaofei Zhang Hongbin Ma Wenchao Zuo Man Luo School of Automation Beijing Institute of TechnologyBeijing 100081 School of Vehicle and Mobility Tsinghua UniversityBeijing 100084China School of Automation Beijing Institute of Technologyand also with the State Key Laboratory of Intelligent Control and Decision of Complex Systems(Beijing Institute of Technology)Beijing 100081China School of Automation Beijing Institute of TechnologyBeijing 100081and he is with Beijing Institute of Electronic System EngineeringBeijing 100854China School of Automation Beijing Institute of TechnologyBeijing 100081and she is with Ant GroupBeijing 310013China

Random vector functional ink(RVFL)networks belong to a class of single hidden layer neural networks in which some parameters are randomly *** network structure in which contains the direct links between inputs and outputs is unique,and stability analysis and real-time performance are two difficulties of the control systems based on neural *** this paper,combining the advantages of RVFL and the ideas of online sequential extreme learning machine(OS-ELM)and initial-training-free online extreme learning machine(ITFOELM),a novel online learning algorithm which is named as initial-training-free online random vector functional link algo rithm(ITF-ORVFL)is investigated for training *** link vector of RVFL network can be analytically determined based on sequentially arriving data by ITF-ORVFL with a high learning speed,and the stability for nonlinear systems based on this learning algorithm is *** experiment results indicate that the proposed ITF-ORVFL is effective in coping with nonparametric uncertainty.

关键词： Adaptive control initial-training-free online learning algorithm random vector functional link networks

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