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robotics, control and Automation Engineering (RCAE), International Conference on

作者： Jing Zhang Haoming Yan Hongtian Chen Shuiqing Xu Yiqi Liu Key Laboratory of Autonomous Systems and Networked Control Ministry of Education School of Automation Science & Engineering South China University of Technology Guangzhou China Department of Automation Shanghai Jiao Tong University Shanghai China College of Electrical Engineering and Automation Hefei University of Technology Hefei China

Considering the high energy consumption problem in the wastewater treatment process, this paper proposes a multi-objective optimization control scheme based on NSGA-II algorithm. The proposed scheme can not only ensures meet effluent quality requirements but also can achieves energy cost savings. This method takes the aeration energy consumption and pumping energy consumption of the system as the optimization goal with the effluent water quality being the constraint condition. At the same time, the adaptive fuzzy PID controller is designed to ensure the control accuracy and stability of the controlled system. The results of simulation experiments validated in benchmark simulation platform, BSM1, show that, compared with PI control and single-objective optimization control, the proposed optimization scheme in this paper can achieve the desired quality of the effluent water withmore energy-saving.

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Robust ℋ∞ horizon optimization control for sampled-data systems with constraints

Robust ℋ∞ horizon optimization control for sampled-data sy...

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Chinese control Conference (CCC)

作者： Fuchun Liu Hailong Pei Yueying Zhao Min Li College of Automation Science and Engineering the Key Laboratory of Autonomous Systems and Networked Control (ASNC) Ministry of Education South China University of Technology Guangzhou 510640 China Department of Automation Guangzhou Kangda Vocational Technical College 511363 China School of Electronic Information and Control Engineering Shandong Polytechnic University Jinan 250353 China

In this paper, the problem of designing of robust state-feedback H ∞ controller for uncertain sampled-data control systems with output constraints have been investigated base on jump system model of sampled-data system using constant Lyapunov function (CLF) approach. The online algorithm of the H ∞ receding horizon optimization design for the norm-bounded parametric uncertain system is proposed. The optimal state-feedback H ∞ controllers are obtained and these controller can provide a performance tradeoff with respect to output constraints, i.e., the control strategy offers the capability of relaxing the performance level automatically in order to obey output constraints in the case of a larger disturbance. When the disturbance is restored to a usual situation, this control strategy can also improve the performance of system automatically.

关键词： Electronic mail Robustness control systems Predictive models Modeling Optimization Predictive control

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Segment-Based Trajectory Prediction and Risk Assessment for RSU-assisted CAVs at Signalized Intersections

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-19页

作者： Cao, Yue Shangguan, Wei Visser, Arnoud Chen, Junjie Chai, Linguo Cai, Baigen School of Automation and Intelligence Beijing Jiaotong University Beijing China School of Automation and Intelligence and State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing China Intelligent Robotics and Computer Vision Lab of the Informatics Institute Faculty of Science University of Amsterdam The Netherlands

Detecting surrounding situations and reacting accordingly to avoid collisions remains a challenging task for autonomous driving. This task requires predicting the trajectories of surrounding agents and assessing the potential risk of future situations, which can be difficult to achieve solely through onboard vehicle devices. Therefore, this paper proposes a cooperative architecture for trajectory prediction and risk assessment conducted on roadside devices (RSUs) to assist Connected and Autonomous Vehicles (CAVs). Firstly, we develop a segmentbased prediction model (SegNet) tailored to hub signalized intersections. Intersections are divided into multiple segments, and the Curvilinear coordinates are utilized to indicate the geometric road features. The model leverages individual interaction cues in the ego segment and group features in the merging segments, while also incorporating traffic signal information to generate multimodal prediction results. In terms of risk assessment, we utilize the prediction results to provide hierarchical assistance, such as risk values, risk maps, and reference trajectories. Offline experimental results demonstrate that our SegNet model achieves competitive and well-balanced performance compared to stateof-the-art methods on the CitySim Database, with more accurate and smooth prediction trajectories. Through real-time CARLA and SUMO co-simulation, the performance of assisted CAVs indicates that they can safely and effectively navigate with the support of the proposed architecture. IEEE

关键词： Real time systems

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Communication and control co-design for wireless sensor networked control systems

Communication and control co-design for wireless sensor netw...

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World Congress on Intelligent control and Automation (WCICA)

作者： Jinna Li Peng Zeng Xuejun Zong Meng Zheng Xiaoling Zhang Lab of Operation and Control Shenyang Shenyang University of Chemical Technology Liaoning P. R. China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Liaoning P. R. China College of Information Engineering Shenyang University of Chemical Technology Liaoning P.R. China

This paper is concerned with communication and control co-design for wireless sensor networked control system (WSNCS) with time-varying delay. Jointly designing communication and control is an attractive paradigm for WSNCS, since the control performance of WSNCS is high sensitive to resource-constrained communication networks. The main idea of devised scheme is searching an optimal event-triggered transmission condition on the premise that wireless link capacity constraint is satisfied and stability of systems is guaranteed. The main aim of devised scheme is to greatly optimize control performance of WSNCS. First, two wireless network architectures characterized by multi-hop and star topology are put forward. Secondly, a model of WSNCS with event-triggered transmission mechanism is constructed. It is followed by stability analysis of WSNCS to obtain the asymptotical stability condition of systems. And then a search algorithm is presented for communication and control co-design. Finally, numerical examples are given to illustrate the effectiveness of the proposed method.

关键词： Wireless sensor networks Wireless communication networked control systems Spread spectrum communication Network topology Topology

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Design and Visual Servoing control of a Hybrid Dual-Segment Flexible Neurosurgical Robot for Intraventricular Biopsy

Design and Visual Servoing Control of a Hybrid Dual-Segment ...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Jian Chen Mingcong Chen Qingxiang Zhao Shuai Wang Yihe Wang Ying Xiao Jian Hu Danny Tat Ming Chan Kam Tong Leo Yeung David Yuen Chung Chan Hongbin Liu School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences (CASIA) Beijing China Centre of AI and Robotics Hong Kong Institute of Science and Innovation Chinese Academy of Sciences (CAIR-HKISI-CAS) HKSAR Department of Biomedical Engineering City University of Hong Kong HKSAR CAIR-HKISI-CAS HKSAR State Key Laboratory of Multimodal Artificial Intelligence Systems CASIA Beijing China Department of Surgery The Chinese University of Hong Kong HKSAR State Key Laboratory of Management and Control for Complex Systems CASIA Beijing China School of Biomedical Engineering and Imaging Sciences King’s College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Traditional rigid endoscopes have challenges in flexibly treating tumors located deep in the brain, and low operability and fixed viewing angles limit its development. This study introduces a novel dual-segment flexible robotic endoscope MicroNeuro, designed to perform biopsies with dexterous surgical manipulation deep in the brain. Taking into account the uncertainty of the control model, an image-based visual servoing with online robot Jacobian estimation has been implemented to enhance motion accuracy. Furthermore, the application of model predictive control with constraints significantly bolsters the flexible robot’s ability to adaptively track mobile objects and resist external interference. Experimental results underscore that the proposed control system enhances motion stability and precision. Phantom testing substantiates its considerable potential for deployment in neurosurgery.

关键词： Jacobian matrices Visualization Endoscopes Estimation Interference Predictive models control systems

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A CNN-Based Position control Method for Under-Actuated Cable-Driven Serpentine Manipulator

A CNN-Based Position Control Method for Under-Actuated Cable...

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IEEE International Conference on robotics and Biomimetics

作者： Jiahao Fang Xueyi Zhang Xingchao Wang Xiaoqiang Ji Ning Tan Zhenglong Sun School of Science and Engineering The Chinese University of Hong Kong Shenzhen China Shenzhen Institute of Artificial Intelligence and Robotics for Society (AIRS) Shenzhen China School of Computer Science and Engineering Sun Yat-sen University Guangzhou China State Key Laboratory of Robotics and Systems (HIT) Harbin China

ISBN: (纸本)9781665405362

Continuum robots or serpentine manipulators have dexterous bodies that fit in narrow space and have advantages over traditional robot arms. In this paper, universal joints were involved in our serpentine manipulator to reinforce its stiffness. In order to have a more compact physical body without compensating much of the dexterity, the manipulator should be under-actuated. For mechanical errors, assembly errors and deformation of components, it is not likely to design the full kinematics model. Also for cable-driven manipulator, the actuation of the driven- cables are always highly coupled. In this paper, we proposed a CNN-based control method to learn the actual kinematics of the manipulator by introducing an ideal model mapping from the cable actuation to joint space. In such manner, we can achieve self-learnt kinematics model with reduced risk of damage in cable.

关键词： Shape Conferences Biomimetics Position control Kinematics Arms Aerospace electronics

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Parallel Learning Based Foundation Model for networked Traffic Signal control

Parallel Learning Based Foundation Model for Networked Traff...

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International Conference on Intelligent Transportation

作者： Chen Zhao Xingyuan Dai Yuanyuan Chen Yilun Lin Yisheng Lv Fei-Yue Wang School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Shanghai AI Laboratory Shanghai China Macao Institute of Systems Engineering Macau University of Science and Technology Macao China

networked Traffic Signal control (NTSC) is a fundamental component of Intelligent Transportation systems (ITS) and the broader vision of smart city development. While a plethora of intelligent strategies have been developed, the Sim2Real challenge often impedes their full realization. In response, this paper introduces the Parallel Learning-based Adaptive Network for Traffic Signal control (PLANT) as a foundation model for NTSC. We employ the Wasserstein GAN with Gradient Penalty (WGAN-GP) to generate a wide range of artificial scenarios for robust PLANT training. Further, the Transformer-based Cooperation Mechanism (TCM) is integrated as the primary learner within PLANT, facilitating effective capture of traffic dynamics and knowledge accumulation. This knowledge is readily transferable to real-world applications through meticulous fine-tuning, equipping PLANT to adapt and evolve in alignment with shifting transportation paradigms. Our empirical study on the Hangzhou road network demonstrates PLANT's superiority over both traditional and emerging DRL-based approaches, emphasizing its viability as a potential foundation model for NTSC.

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Formation control of Discrete-time Multi-agent systems Based on Distributed Filter Observer

Formation Control of Discrete-time Multi-agent Systems Based...

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

作者： Huanli Gao Wei Li Ming Qiu He Cai School of Automation Science and Engineering South China University of Technology Guangzhou China Key Laboratory of Autonomous Systems and Networked Control Ministry of Education Guangzhou China Guangdong Engineering Technology Research Center of Unmanned Aerial Vehicle Systems Guangzhou China Department of Shanhaiguan District People’s Armed Forces Qinhuangdao City China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This paper explores the formation control of discrete multi-agent systems under external communication disturbance. Firstly, leveraging the modified algebraic Riccati equation, a disturbed output based discrete filter observer is proposed to minimize network information exchange and mitigate disturbance effects. Then, the formation control issue is transformed into a cooperative output regulation problem, which a certainty equivalent state feedback controller solves. The effectiveness of the control strategy is demonstrated by numerical simulations.

关键词： state feedback Riccati equations Observers Information filters Numerical simulation Filtering theory Formation control

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Online Gyro Bias Estimation from Single Vector Measurements Using Regression Models

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IFAC-PapersOnLine 2023年第1期56卷 252-257页

作者： Bowen Yi Lei Wang Weidong Zhang Australian Centre for Field Robotics The University of Sydney NSW 2006 Australia State Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou 310027 China School of Information and Communication Engineering Hainan University Haikou 570228 China Department of Automation Shanghai Jiao Tong University Shanghai 200240 China

This paper addresses the problem of on-line consistent estimation of gyro bias using the measurements of a single vector and the biased angular velocity - both in the body-fixed frame. We propose two globally convergent gyro bias observers using new regression models, which are capable to deal with the cases of constant and time-varying reference vectors, respectively. Indeed, there are quite a few works discussing the latter case. To address this, we derive a nonlinear regression model, based on which a convexified gradient descent observer is designed, providing globally asymptotically convergent estimates to the gyro bias under some sufficient excitation conditions. The proposed schemes are illustrated by some numerical simulations.

关键词： Nonlinear systems observer parameter identification robotics

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CPnP: Consistent Pose Estimator for Perspective-n-Point Problem with Bias Elimination

arXiv

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arXiv 2022年

作者： Zeng, Guangyang Chen, Shiyu Mu, Biqiang Shi, Guodong Wu, Junfeng School of Data Science Chinese University of Ho ng Kong Shenzhen Shenzhen China Key Laboratory of Systems and Control Institute of Systems Science Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing China Australian Center for Field Robotics School of Aerospace Mechanical and Mechatronic Engineering The University of Sydney NSW2008 Australia

The Perspective-n-Point (PnP) problem has been widely studied in both computer vision and photogrammetry societies. With the development of feature extraction techniques, a large number of feature points might be available in a single shot. It is promising to devise a consistent estimator, i.e., the estimate can converge to the true camera pose as the number of points increases. To this end, we propose a consistent PnP solver, named CPnP, with bias elimination. Specifically, linear equations are constructed from the original projection model via measurement model modification and variable elimination, based on which a closed-form least-squares solution is obtained. We then analyze and subtract the asymptotic bias of this solution, resulting in a consistent estimate. Additionally, Gauss-Newton (GN) iterations are executed to refine the consistent solution. Our proposed estimator is efficient in terms of computations—it has O(n) computational complexity. Experimental tests on both synthetic data and real images show that our proposed estimator is superior to some well-known ones for images with dense visual features, in terms of estimation precision and computing time. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear equations

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