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Sliding Mode control for Flexible-link Manipulators Based on Adaptive Neural Networks

International Journal of automation and computing 2018年第2期15卷 239-248页

作者： Hong-Jun Yang Min Tan State Key Laboratory of Management and Control for Complex Systems Institute of AutomationChinese Academy of Sciences

This paper mainly focuses on designing a sliding mode boundary controller for a single flexible-link manipulator based on adaptive radial basis function （RBF） neural network. The flexible manipulator in this paper is considered to be an Euler-Bernoulli beam. We first obtain a partial differential equation （PDE） model of single-link flexible manipulator by using Hamiltons approach. To improve the control robustness, the system uncertainties including modeling uncertainties and external disturbances are compensated by an adaptive neural approximator. Then, a sliding mode control method is designed to drive the joint to a desired position and rapidly suppress vibration on the beam. The stability of the closed-loop system is validated by using Lyapunov＇s method based on infinite dimensional model, avoiding problems such as control spillovers caused by traditional finite dimensional truncated models. This novel controller only requires measuring the boundary information, which facilitates implementation in engineering practice. Favorable performance of the closed-loop system is demonstrated by numerical simulations.

关键词： Sliding mode control adaptive control neural network flexible manipulator partial differential equation （PDE）.

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Fuzzy PID control for suppressing stick-slip vibration of drill-string system

Fuzzy PID control for suppressing stick-slip vibration of dr...

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Chinese automation Congress (CAC)

作者： Shuaikang Hu Chengda Lu Min Wu Zhaoqing He Haitao Song Wangnian Li School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China China Coal Technology and Engineering Group Xi'an Research Institute Co. Ltd Xi'an China

In this paper, a fuzzy PID (Proportional Integral Derivative) controller is introduced to suppress the stick-slip vibration present in the drilling process. First, the dynamical model of stick-slip vibration is composed of the multi-DOF (Degree-Of-Freedom) drill-string model and the Karnopp model describing the interaction of the drill bit with the rock. Then, stability analysis is made for the initial PID parameters of our controller. To suppress the stick-slip vibration and at the same time mitigate the effects of the stratigraphic environment variation on the control performance, the fuzzy adaptive algorithm is chosen as the method of optimization controller parameters. From the experimental results, it is clear that our controller has good control performance in the complex and changing stratigraphic environment.

关键词： Vibrations Drilling PI control Delay effects Process control Rocks Stability analysis

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Coordinated Guiding Vector Field Design for Ordering-Flexible Multi-Robot Surface Navigation

arXiv

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arXiv 2024年

作者： Hu, Bin-Bin Zhang, Hai-Tao Yao, Weijia Sun, Zhiyong Cao, Ming The School of Artificial Intelligence and Automation The Engineering Research Center of Autonomous Intelligent Unmanned Systems The Key Laboratory of Image Processing and Intelligent Control The State Key Lab of Digital Manufacturing Equipment and Technology Huazhong University of Science and Technology Wuhan430074 China The School of Robotics Hunan University Hunan410082 China The Institute of Engineering and Technology University of Groningen Groningen9747 AG Netherlands Department of Electrical Engineering Eindhoven University of Technology Netherlands

We design a distributed coordinated guiding vector field (CGVF) for a group of robots to achieve ordering-flexible motion coordination while maneuvering on a desired two-dimensional (2D) surface. The CGVF is characterized by three terms, i.e., a convergence term to drive the robots to converge to the desired surface, a propagation term to provide a traversing direction for maneuvering on the desired surface, and a coordinated term to achieve the surface motion coordination with an arbitrary ordering of the robotic group. By setting the surface parameters as additional virtual coordinates, the proposed approach eliminates potential singularity of the CGVF and enables both the global convergence to the desired surface and the maneuvering on the surface from all possible initial conditions. The ordering-flexible surface motion coordination is realized by each robot to share with its neighbors only two virtual coordinates, i.e. that of a given target and that of its own, which reduces the communication and computation cost in multi-robot surface navigation. Finally, the effectiveness of the CGVF is substantiated by extensive numerical simulations. Copyright © 2024, The Authors. All rights reserved.

关键词： Navigation

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Grouping Methods for Facilitating Emergency Evacuations

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IFAC-PapersOnLine 2020年第5期53卷 845-850页

作者： Linyao Yang Ke Tan Xin Liu Xiao Wang Fei-Yue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China State Key Laboratory of Nuclear Power Safety Monitoring Technology and Equipment Shenzhen China

It is widely believed that the motion of crowds can be described by the “social force” model, and small group behaviors have great impacts on evacuation efficiency as a common phenomenon in pedestrian evacuations. Some previous works have modeled group behaviors in social force models by depicting group members’ interaction forces. However, the impacts of different grouping schemes have not been considered and evaluated. This paper proposes four different grouping methods to explore the evacuation dynamics of different group structured pedestrians. Results show that group evacuations based on the spatial partitioning outperform those clustering-based schemes with the larger group number. More importantly, simulations indicate that the number of groups also highly affects the evacuation efficiency, and the larger the number of groups, the more efficient the evacuation.

关键词： Evacuation Simulation Social force Clustering methods Agent based modeling

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AGV Semantic Attack Detection Based on Hidden Markov Model

AGV Semantic Attack Detection Based on Hidden Markov Model

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IEEE International Conference on Industrial Technology (ICIT)

作者： Sichao Zhang Wei Liang Yinlong Zhang Zhibo Pang State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Key Laboratory of Networked Control Systems Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China University of Chinese Academy of Sciences Beijing China Department of Automation Technology ABB Corporate Research Sweden Vasteras Sweden

ISBN: (纸本)9781728119496

Automatic Guided Vehicle (AGV) semantic attack is now becoming an important research topic in digital workshops. Unfortunately, the conventional attack detections could trigger the wrong attack detection alarms, because of the unexpected wireless radio frequency interference. This paper investigates a new method for AGV semantic attack detection based on Hidden Markov Model (HMM). Our method is able to discriminate the typical wireless retransmission in presence of environment interference or in the context of AGV semantic attack by comparing the hidden state transition probability with the predefined threshold. Our model has been evaluated on our developed platform. The extensive experimental results and analysis prove the effectiveness of our method.

关键词： Wireless communication Conferences Semantics Hidden Markov models Interference Markov processes Radiofrequency interference

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Distributed Model-Free Adaptive Learning control of Discrete-Time Nonlinear Multiagent systems

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IEEE transactions on neural networks and learning systems 2025年 PP卷 PP页

作者： Yong-Sheng Ma Wei-Wei Che Shi-Xu Xu Chao Deng Zheng-Guang Wu Beijing Institute of Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems School of Automation Beijing 100081 China Northeastern University State Key Laboratory of Synthetical Automation for Process Industries College of Information Science and Engineering Shenyang 110819 China Qingdao University Shandong Key Laboratory of Industrial Control Technology Department of Automation Qingdao 266071 China Nanjing University of Posts and Telecommunications Institute of Advanced Technology Nanjing 210000 China Zhejiang University State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Hangzhou 310027 China

This article investigates the distributed control problem for nonlinear multiagent systems (MASs) with unknown system models. A novel distributed model-free adaptive learning algorithm is developed to learn a controller from the online system data. Notably, a significant advancement over conventional methods is that the proposed algorithm requires only local interaction data from neighboring agents, eliminating dependencies on both a priori system structural knowledge and global topology information. Comprehensive simulations validate the theoretical results and demonstrate the superior efficacy of the devised algorithm.

关键词： Distributed control model-free adaptive control (MFAC) multiagent systems (MASs)

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Social Manufacturing Pattern in the Intelligent Reform of the Shoes and Clothing Industry

Social Manufacturing Pattern in the Intelligent Reform of th...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Yansong Cao Yutong Wang Juwu Dai Xihao Zhu Fei-Yue Wang Macau Institute of Systems Engineering Macau University of Science and Technology Macau China The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Ningbo Sanbody Intelligent Technology co. LTD Ningbo China Faculty of Science and Engineering University of Nottingham Ningbo China

Along with economic globalization, the shoes and clothing market is undergoing huge changes and is facing increasing individualized demands. To realize personalized customization, we propose a social manufacturing pattern for the shoes and clothing industry. On the customer side, we collect costumer information with the help of 3D scanning and virtual fitting. On the production side, we replace human labor with intelligent production equipment. On the enterprise management side, we construct a cloud platform to realize source maximization. Through this social manufacturing pattern, we expect to accelerate the intelligent reform of the shoes and clothing industry.

关键词： Product customization Cloud computing Three-dimensional displays Social networking (online) Production equipment Footwear Clothing industry

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A KG-based Enhancement Framework for Fact Checking Using Category Information

A KG-based Enhancement Framework for Fact Checking Using Cat...

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IEEE International Conference on Intelligence and Security Informatics, ISI

作者： Shuai Wang Lei Wang Wenji Mao State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences School of Artificial Intelligence University of Chinese Academy of Sciences

ISBN: (数字)9781728188003

ISBN: (纸本)9781728188010

The massive spread of false information has brought about severe security-related problems to individuals and society. To debunk misinformation automatically, fact checking has become an important task that aims at retrieving evidence from external sources to verify the truthfulness of a given claim. As knowledge graph (KG) is a classic external source for retrieving relevant evidence. Previous methods typically check a claim by making inferences over it. Entity category information can be utilized to strengthen both the learning and verification process. However, this information was largely ignored in previous research. To make better use of the category information, in this paper, we propose a category-based framework for improving the performance of fact checking with KGs. We first learn prototypes for each category as their representatives, and then propose a prototype-based learning technique for effectively modeling the entity dependency in KG. We further develop a prototype matching technique to explore the category-level relations between head and tail entities for more robust verification. Experimental results on two benchmark datasets and a real-world dataset show that our framework can significantly improve the reasoning abilities of KG reasoning methods on Fact Checking task.

关键词： Conferences Prototypes Benchmark testing Cognition Security Task analysis Informatics

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Dual Role of Pulmonary Surfactant Corona in Modulating Carbon Nanotube Toxicity and Benzo[A]Pyrene Bioaccessibility

SSRN

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SSRN 2023年

作者： Luo, Zhen Xu, Dongfang Xu, Yan Zhao, Jian Hu, Guoqing Yue, Tongtao Department of Engineering Mechanics State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou310027 China Institute of Coastal Environmental Pollution Control Key Laboratory of Marine Environment and Ecology Ministry of Education Frontiers Science Center for Deep Ocean Multispheres and Earth System Ocean University of China Qingdao266100 China College of Electronic Engineering and Automation Shandong University of Science and Technology Qingdao266590 China

Inhaled carbon nanotubes (CNTs) can deposit in the deep lung, where they interact with pulmonary surfactant (PS) to form coronas, potentially altering the fate and toxicity profile of CNTs. However, the presence of other contaminants in combination with CNTs may affect these interactions. In this study, we investigated the effects of coexisting contaminants, specifically benzo[a]pyrene (BaP), on the interaction between CNTs and PS. We used passive dosing and fluorescence-based techniques to demonstrate that PS increases the solubility of BaP pre-adsorbed on CNTs. Subsequently, molecular dynamics simulations were performed to gain insight into the intricate interactions between CNTs, BaP, and PS. Our results suggest that the PS corona plays a dual role in modulating the toxicity of CNTs. First, it mitigates toxicity by reducing the hydrophobicity and apparent aspect ratio of CNTs. Second, it exacerbates toxicity due to energetically dominant PS-BaP interactions, which increase the solubility and thus bioaccessibility of BaPs. Importantly, these interactions are strongly influenced by the size and aggregation state of the CNTs. Our findings highlight the need to consider the bioaccessibility of coexisting contaminants when assessing the inhalation toxicity of PS-modified CNTs. © 2023, The Authors. All rights reserved.

关键词： Toxicity

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Parallel Governance for Decentralized Autonomous Organizations enabled by Blockchain and Smart Contracts

Parallel Governance for Decentralized Autonomous Organizatio...

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Digital Twins and Parallel Intelligence (DTPI), IEEE International Conference on

作者： Wen Wen Ding XiaoLong Liang JiaChen Hou Ge Wang Yong Yuan Junqing Li Fei-Yue Wang Institute of Systems Engineering Macau University of Science and Technology Macau China School of Mathematics Renmin University of China Beijing China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China

Decentralized autonomous organizations(DAOs) enabled by blockchain and smart contracts is regarded as an effective tool to solve corporate governance problems. It can minimize the contract risks, principal-agent dilemmas, and other issues in corporate governance. However, DAOs also face a variety of governance issues, such as internal governance issues and external governance issues caused by the technical attributes of blockchain and smart contracts. DAO is a typical complex system with the characteristics of both social and engineering complexity. It is difficult for existing governance theories to solve governance problems in DAOs. The parallel intelligence theory based on the artificial systems + computational experiments + parallel execution (ACP) method is a suitable research and practical approach to solve management and control problems for complex systems. Therefore, we propose a parallel governance framework for DAO based on the parallel intelligence theory and discuss its key research issues. Finally, we construct a parallel governance system for GnosisDAO, and conduct computational experiments on its voting mechanism. The results show the defects of GnosisDAO governance mechanism and we thus propose further research directions. We consider that parallel governance represents the future trend of DAO research and practice. This paper is aimed at stimulating further effort and providing helpful guidance and reference for future research works.

关键词： Computational modeling Digital twin Conferences Smart contracts Tools systems modeling Market research

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