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IEEE Transactions on Industrial Cyber-Physical Systems 2025年 3卷 241-250页

作者： Xu, Yong Zhang, Wenyu Zhang, Yifang Wu, Zheng-Guang Beijing Institute of Technology School of Automation Beijing100081 China The University of Hong Kong Department of Mechanical Engineering Hong Kong Hong Kong Zhejiang University Institute of Cyber-Systems and Control Hangzhou310027 China

This paper delves into the distributed resilient state estimation-based secure control in multi-agent systems under false-data injection attacks. Firstly, we propose a novel adaptive distributed output observer approach that is based on resilient outputs. The key feature of our proposed observer is its sole dependence on the coefficients of the minimal polynomial of the leader's system matrix, rather than on individual entries of the leader's system. Subsequently, to identify the target attacker, we assign both trust and confidence values to each agent and its neighbors, thereby enabling attack detection and localization. Furthermore, we propose a distributed finite-time resilient control strategy, grounded in trust and confidence, to safeguard against attackers while ensuring secure output estimation and maintaining a bounded upper limit for finite-time convergence. Additionally, we introduce a piecewise function-based approximation method to achieve a less conservative upper bound for the convergence time, compared to traditional methods. Finally, we provide a numerical example to demonstrate the effectiveness of our proposed theoretical analysis. © 2023 IEEE.

关键词： Cyber attacks

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controller Dynamic Linearization Based Data-Driven Adaptive control for a Vapor-Compression Refrigeration System 13

Controller Dynamic Linearization Based Data-Driven Adaptive ...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Fang, Jingyu Yu, Xian Xiong, Shuangshuang College of Mechatronics and Control Engineering Shenzhen University Shenzhen518060 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9798350361674

This paper applies a data-driven adaptive control method to a benchmark of vapor compression refrigeration system based on the controller dynamic linearization method. Two controllers, namely, a single-input single-output controller and an extended multiple-input multiple-output controller, are designed to track the exit temperature of the evaporator secondary flux and the refrigerant superheat at the evaporator exit, by controlling the valve opening of the evaporator, and the compressor speed. Both the controllers entirely rely on input-output data of the controlled system in the controller design. Comparative results between the applied data-driven adaptive control and the default PID control provided by the benchmark demonstrate the effectiveness of the two designed controllers. © 2024 IEEE.

关键词： Vapor compression refrigeration

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Time-Optimal and Smooth Trajectory Planning Based on Continuous Pseudo-Acceleration 8

Time-Optimal and Smooth Trajectory Planning Based on Continu...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Wang, Xin Gan, Yahui Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing China

ISBN: (纸本)9798350300178

The current time-optimal trajectory planning based on dynamics does not take into account the continuity of joint torque. Although the time obtained by the solution of the original time-optimal path parameterization (TOPP) algorithm is optimal, the joint torque obtained by the solution is not continuous, and the discontinuous joint torque will cause the manipulator to resonate, which will reduce the accuracy of the trajectory, making the obtained trajectory in practical engineering applications cannot be effectively applied. Therefore, this paper improves the problem of discontinuous torque on the basis of the TOPP algorithm, and proposes to use a quadratic polynomial curve to deal with the discontinuous part of the pseudo-acceleration in the phase plane composed of position and pseudo-acceleration, which not only ensures the integrity of the path, but also makes the joint torque continuous and smoothes the joint torque trajectory to some extent. This method is verified by the simulation experiment of the two-link manipulator. © 2023 IEEE.

关键词： Trajectories

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Observer-based quantised control of networked systems with round-robin protocol and transmission delay

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Journal of control and Decision 2025年第1期12卷 24-33页

作者： Ge Guo Xuefei Yan Jian Kang State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyangPeople's Republic of China School of Control Engineering Northeastern University at QinhuangdaoQinhuangdaoPeople's Republic of China College of Information Science and Engineering Northeastern UniversityShenyangPeople's Republic of China

This paper addresses the ultimate boundedness control problem for a class of networked nonlinear systems with the round-robin(RR)protocol and uniform *** communication between sensor nodes and the controller is implemented via a constrained communication *** quantised output of the system is transmitted to the remote controller through a communication channel subject to a transmission *** the purpose of alleviating possible data collision,the well-known RR communication protocol is deployed to schedule the data *** the other hand,the uniform quantisation effects of the network are characterised by a round function(*** nearest integer function).The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that,in the presence of RR protocol and uniform quantisation effects,the closed-loop system is ultimately *** controller is designed based on mean square stability analysis and Lyapunov-like method.A set of sufficient conditions for the ultimate boundedness of the closed-loop system are established and,on the basis of which,the desired controller gains are obtained by solving a set of linear matrix *** effectiveness of the proposed method is verified by numerical examples.

关键词： Networked control systems(NCSs) round-robin(RR)protocol transmission delay uniform quantisation ultimate boundedness control

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A Novel Multimodal Humanoid Robot control System Framework Design Based on SSVEP-BCI and Eye-Tracking 7

A Novel Multimodal Humanoid Robot Control System Framework D...

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7th International Conference on Biological Information and Biomedical engineering, BIBE 2024

作者： Han, Chunxiao Hu, Yue Liu, Yanli Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9783800762910

As population ageing increases, Brain-Computer Interface (BCI) technology combined with humanoid robots has become an innovative solution to alleviate the stress of elderly care. To improve the reliability and stability of the BCI system in practical applications, this paper proposed a novel multimodal humanoid robot control system. There are two different control modalities in parallel: Steady State Visual Evoked Potential (SSVEP)-BCI control modality and Eye Tracking control modality. The system utilized blinks events enable the user to initiate the human-machine interface (HMI) autonomously, selected one of the control modes based on the user's attention state, and sent control commands to the robot for execution. This multimodal framework effectively solves the false triggering problem of the humanoid BCI system, and the humanoid robot can perform tasks more flexibly. © VDE VERLAG GMBH.

关键词： Anthropomorphic robots

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Enhanced Potato Detection Using an Improved YOLOv8 Algorithm 24

Enhanced Potato Detection Using an Improved YOLOv8 Algorithm

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9th International Conference on Multimedia Systems and Signal Processing, ICMSSP 2024

作者： Wang, Zihan Zhang, Yunxi Ma, Yuqi Zhao, Ya Liu, Jia School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin China Tianjin Key Laboratory of Information Sensing and Intelligent Control Tianjin China

ISBN: (纸本)9798400716911

This paper proposes a novel potato detection algorithm YOLOv8-P, based upon the improved YOLOv8 framework to achieve enhanced detection accuracy. The algorithm incorporates the BiFormer attention mechanism and introduces an additional detection layer specifically designed for large targets, thereby significantly improving the model's performance in identifying larger potatoes. Additionally, a comprehensive dataset named potato-2024 was developed to address the limitations of existing public datasets in potato detection. To validate the effectiveness of YOLOv8-P, comparative experiments were conducted with YOLOv5 and YOLOv8 on the potato-2024 dataset. The results demonstrate that, under identical experimental conditions and parameters, YOLOv8-P exhibits superior recognition accuracy in potato identification, thus establishing a new benchmark in potato detection technology. © 2024 Copyright held by the owner/author(s).

关键词： YOLOv8

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Autonomous Path Planning and Realization for Dual Robot Cooperation Based on ROS Framework 8

Autonomous Path Planning and Realization for Dual Robot Coop...

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8th IEEE International Conference on Advanced Robotics and Mechatronics, ICARM 2023

作者： Shao, Jiawei Gan, Yahui Dai, Xianzhong School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education NanJing China

ISBN: (纸本)9798350300178

To realize dual-robot autonomous path planning and realization, the trajectory planning research of dual-robot is carried out using the open-source robot operating system ROS as the simulation platform. The motion planning-related file configuration is completed by using MoveIt! In trajectory planning, cubic spline interpolation is performed on the trajectory points generated by the RRT-Connect path planning algorithm to complete the planning of the dual-arm assembly task. The communication between ROS nodes and ROS is established in the controller, and the processed trajectory points are communicated with the controller through ROS-Industrial. The experimental results show that the trajectory of the dual robot movement process is smooth and continuous, the stability is strong, and the error is small, which can ensure the completion of basic assembly tasks. © 2023 IEEE.

关键词： Motion planning

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Fall Detection System Based on YOLO Algorithm and MobileNetV2 Model 10

Fall Detection System Based on YOLO Algorithm and MobileNetV...

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10th International Conference on Systems and Informatics, ICSAI 2024

作者： Han, Chunxiao Zhang, Jingyan Wu, Han Tianjin Key Laboratory of Information Sensing & Intelligent Control China School of Automation and Electrical Engineering Tianjin University of Technology and Education Tianjin300222 China

ISBN: (纸本)9798331510138

Accidental falls are the major causes of injury among elderly people living alone. However, traditional fall detection algorithms usually have missed or false detections problems. In this paper, we design a fall detection system based on YOLO algorithm and MobileNetV2 model. First, detection frame coordinates and joint coordinates of the human body are fused as feature information, and background information is filtered out. A lightweight deep learning model, MobileNetV2, is then used for classification. Compared with commonly used lightweight classification models such as ShuffleNet and EfficientNet, the MobileNetV2 model performs better in recognizing fall behavior. Our system can effectively distinguish fall behavior from daily activities, meeting the requirements for fall detection. © 2024 IEEE.

关键词： Fall detection

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Deterministic Learning-Based Robust Practical Output Regulation for Second-Order Nonlinear Systems

Deterministic Learning-Based Robust Practical Output Regulat...

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2024 International Annual Conference on Complex Systems and Intelligent Science, CSIS-IAC 2024

作者： Hu, Qingxi Liu, Wei Key Laboratory of Autonomous Systems and Networked Control of Ministry of Education School of Automation Science and Engineering South China University of Technology Guangzhou510641 China

ISBN: (纸本)9798331504755

This article intends to investigate the semi-global robust practical output regulation problem for a class of second-order nonlinear systems with parametric and non-parametric uncertainties based on deterministic learning method. First, by constructing the internal models, the robust output regulation problem is transformed into the semi-global robust practical stabilization problem. Second, we propose an adaptive neural control (ANC) strategy to solve the stabilization problem and utilize the radial basis function neural networks (RBF NNs) to identify unknown dynamic. Moreover, under the persistently exciting (PE) property, the unknown dynamics can be identified and the learned knowledge is saved as some constant NN weights. Finally, we design an deterministic learning-based adaptive neural control (DLANC) law with the learned knowledge to solve the output regulation problem and improve control performance. © 2024 IEEE.

关键词： Contrastive Learning

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ES-MSCNN: An Echo State Multi-Scale Convolutional Neural Network for Multi-Step Prediction of Wastewater Quality Variables 7

ES-MSCNN: An Echo State Multi-Scale Convolutional Neural Net...

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7th International Conference on Robotics, control and automation engineering, RCAE 2024

作者： Sun, Yue Liu, Yiqi South China University of Technology Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science & Engineering Guangzhou510640 China

ISBN: (纸本)9798350355642

Given the limitations of hardware sensors together with strong nonlinearities and nexus between variables in wastewater treatment processes (WWTPs), the measurement of key quality variables is usually inaccurate or even impossible. Moreover, due to the short data sampling period, the single-output single-step prediction model cannot meet the actual demand. Therefore, this paper proposes a new soft sensor, termed as the Echo State Multi-Scale Convolutional Neural Network (ES-MSCNN), designed for accurate multivariate multi-step prediction. ES-MSCNN first generates an echo state representation (ESR) containing temporal information through an echo state network (ESN). Subsequently, a convolutional neural network (CNN) is employed to avoid the shallowness of ESN and further extract high-dimensional feature information from the data. Besides, a multi-scale learning strategy is used in the convolutional module to capture multi-timescale features and improve the multivariate prediction accuracy. Validation on the benchmark simulation model 2 platform and comparison with several models indicate that the proposed ES-MSCNN has higher accuracy and stronger robustness in multi-step prediction tasks with multi-input and multi-output. © 2024 IEEE.

关键词： Convolutional neural networks

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