检索结果-内蒙古大学图书馆

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

来源：评论

学校读者我要写书评

暂无评论

Predicting Interaction Shape of Soft Continuum Robots using Deep Visual Models

Predicting Interaction Shape of Soft Continuum Robots using ...

引用

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)

作者： Yunqi Huang Abdulaziz Y. Alkayas Jialei Shi Federico Renda Helge Wurdemann Thomas George Thuruthel Department of Computer Science University College London London UK Department of Mechanical and Nuclear Engineering Khalifa University Abu Dhabi UAE Department of Mechanical Engineering University College London London UK Department of Mechanical Engineering Mechatronics in Medicine The Hamlyn Centre for Robotic Surgery Imperial College London UK Khalifa University Center for Autonomous Robotic Systems (KUCARS) Khalifa University Abu Dhabi UAE

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

Soft continuum robots, characterized by their inherent compliance and dexterity, are increasingly pivotal in applications requiring delicate interactions with the environment such as the medical field. Despite their advantages, challenges persist in accurately modeling and controlling their shape during interactions with surrounding objects. This is because of the difficulty in modeling the large degrees of freedom in soft-bodied objects that become more active during interactions. In this study, we present a deep visual model to predict the interaction shapes of a soft continuum robot in contact with surrounding objects. By formulating this task as a forward-statics problem, the model uses the initial state images containing the object configuration and future actuation values to predict interactive state images of the robot under this actuation condition. We developed and tested the model in both simulated and physical environments, explored the model’s predictive capabilities using monocular and binocular views, and tested the model’s generalization ability on different datasets. Our results show that deep learning methods are a promising tool for solving the complex problem of predicting the shape of a soft continuum robot interacting with the environment, requiring no prior knowledge about the system dynamics and explicit mapping of the environment. This study paves the way for future explorations in robot-environment interaction modeling and the development of more adaptable interaction shape control strategies.

关键词： Adaptation models Visualization Accuracy Uncertainty Shape Robot kinematics Predictive models Data collection Data models Continuum robots

来源：评论

学校读者我要写书评

暂无评论

Language-Conditioned Affordance-Pose Detection in 3D Point Clouds

arXiv

引用

arXiv 2023年

作者： Nguyen, Toan Vu, Minh Nhat Huang, Baoru Van Vo, Tuan Truong, Vy Le, Ngan Vo, Thieu Le, Bac Nguyen, Anh FPT Software AI Center Viet Nam Automation & Control Institute TU Wien Vienna Austria Imperial College London United Kingdom Department of Computer Science & Computer Engineering University of Arkansas United States Faculty of Mathematics and Statistics Ton Duc Thang University Ho Chi Minh City Viet Nam Department of Computer Science University of Science Viet Nam Department of Computer Science University of Liverpool United Kingdom

Affordance detection and pose estimation are of great importance in many robotic applications. Their combination helps the robot gain an enhanced manipulation capability, in which the generated pose can facilitate the corresponding affordance task. Previous methods for affodance-pose joint learning are limited to a predefined set of affordances, thus limiting the adaptability of robots in real-world environments. In this paper, we propose a new method for language-conditioned affordance-pose joint learning in 3D point clouds. Given a 3D point cloud object, our method detects the affordance region and generates appropriate 6-DoF poses for any unconstrained affordance label. Our method consists of an open-vocabulary affordance detection branch and a language-guided diffusion model that generates 6-DoF poses based on the affordance text. We also introduce a new high-quality dataset for the task of language-driven affordance-pose joint learning. Intensive experimental results demonstrate that our proposed method works effectively on a wide range of open-vocabulary affordances and outperforms other baselines by a large margin. In addition, we illustrate the usefulness of our method in real-world robotic applications. Our code and dataset are publicly available at https://***. © 2023, CC BY-NC-SA.

关键词： Robotics

来源：评论

学校读者我要写书评

暂无评论

Learning-based control for PMSM Using Distributed Gaussian Processes with Optimal Aggregation Strategy

Learning-based Control for PMSM Using Distributed Gaussian P...

引用

Annual Conference of Industrial Electronics Society

作者： Zhenxiao Yin Xiaobing Dai Zewen Yang Yang Shen Georges Hattab Hang Zhao Robotics and Autonomous Systems Thrust The Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Chair of Information-oriented Control Technical University of Munich Munich Germany Center for Artificial Intelligence in Public Health Research (ZKI-PH) Robert Koch Institute Berlin Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany Department of Electronic & Computer Engineering The Hong Kong University of Science and Technology Hong Kong China

The growing demand for accurate control in varying and unknown environments has sparked a corresponding increase in the requirements for power supply components, including permanent magnet synchronous motors (PMSMs). To infer the unknown part of the system, machine learning techniques are widely employed, especially Gaussian process regression (GPR) due to its flexibility of continuous system modeling and its guaranteed performance. For practical implementation, distributed GPR is adopted to alleviate the high computational complexity. However, the study of distributed GPR from a control perspective remains an open problem. In this paper, a control-aware optimal aggregation strategy of distributed GPR for PMSMs is proposed based on the Lyapunov stability theory. This strategy exclusively leverages the posterior mean, thereby obviating the need for computationally intensive calculations associated with posterior variance in alternative approaches. Moreover, the straightforward calculation process of our proposed strategy lends itself to seamless implementation in high-frequency PMSM control. The effectiveness of the proposed strategy is demonstrated in the simulations.

关键词：

来源：评论

学校读者我要写书评

暂无评论

IoT Based Health Monitoring System with AI-Powered Disease Prediction

IoT Based Health Monitoring System with AI-Powered Disease P...

引用

International Conference on science Technology engineering and Management (ICONSTEM)

作者： S. Radha Mahendran Mohammad Shahbaz Khan Hari Priya M P Ahmed J. Obaid Karrar Shareef Mohsen Ashraf Mohammed Shareef Department of Bioinformatics School of Life Sciences Vels Institute of Science Technology and Advanced Studies (VISTAS) Chennai India operations and regulatory affairs Children's National Hospital Washington DC USA Department of Computer Science Kristu Jayanti College (Autonomous) Bangalore Karnataka India Najaf Iraq Department of Computer Technical Engineering Faculty of Computer Science and Mathematics University of Kufa Technical Engineering College Al-Ayen University Thi-Qar Iraq Information and Communication Technology Research Group Scientific Research Center Al-Ayen University Thi-Qar Iraq National University of Science and Technology DhiQar Iraq

ISBN: (数字)9798350365092

ISBN: (纸本)9798350365108

Healthcare monitoring systems have advanced significantly in emergency rooms and many other health settings. Today, many nations are deeply concerned about the rise of small healthcare monitoring systems. In-person advising and telemedicine are two different ways that the Internet of Things (IoT) is further developing healthcare. The Internet of Things makes things and individuals reliably available, and its relationship with the cloud improves our personal satisfaction. Proactive clinical exploration can help change a responsive healthcare approach into a proactive one, as man-made reasoning (AI) and high-level human insight become increasingly more coordinated into the healthcare area. Within the field of machine learning, deep learning holds significant potential in precisely and swiftly analysing vast quantities of data, producing perceptive experiences, and resolving intricate issues. Preventive treatment and early intervention for persons who are at risk depend on accurate and useful illness prediction. The constant inflow of electronic medical information necessitates the need for more accurate prediction models in recurrent neural network versions of deep learning that handle successive time-series data. Devices connected to the Internet of Things provide data to the proposed system, and future analysis will be conducted on cloud-stored electronic clinical records pertaining to patient histories.

关键词： Deep learning Cloud computing Accuracy Telemedicine Medical services Internet of Things Reliability

来源：评论

学校读者我要写书评

暂无评论

Data-Driven Self-Triggered control for Linear Networked control Systems

Data-Driven Self-Triggered Control for Linear Networked Cont...

引用

IEEE Conference on Decision and control

作者： Xin Wang Yifei Li Jian Sun Gang Wang Jie Chen Lihua Dou National Key Lab of Autonomous Intelligent Unmanned Systems School of Automation Beijing Institute of Technology Beijing China Beijing Institute of Technology Chongqing Innovation Center Chongqing China Department of Control Science and Engineering Tongji University Shanghai China

This paper considers data-driven control of unknown linear discrete-time systems under a self-triggered transmission scheme. While self-triggered control has received much attention in the literature, its design and implementation typically require explicit model knowledge. Due to the difficulties in obtaining accurate models and the abundance of data in applications, this paper proposes a novel data-driven self-triggered control scheme for unknown systems. To this end, we begin by presenting a model-based self-triggered scheme (STS) in form of quadratic matrix inequalities, on the basis of an equivalent switched system representation. Combining the model-based triggering law and a data-based system representation, a data-driven STS is developed leveraging pre-collected input-state data for predicting the next transmission instant while ensuring system stability. A data-based method for co-designing the controller gain and the triggering matrix is then provided. Finally, a numerical simulation showcases the efficacy of STS in reducing transmissions as well as practicality of the proposed co-design methods.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Optimized fractional-order PID controller for temperature control of CSTH: a comparative study with PID cascade controller

Optimized fractional-order PID controller for temperature co...

引用

International Conference on Energy, Power, Environment, control and Computing (ICEPECC 2025)

作者： Abdulaziz F. Alaswadi Nezar M. Alyazidi Fatima N. Al-Aswadi Amjed Abbas Ahmed Department of Control and Instrumentation Engineering King Fahd University of Petroleum and Minerals Dhahran 31261 Saudi Arabia Institute of Computer Science & Digital Innovation (ICSDI) UCSI University Kuala Lumpur 56000 Malaysia Center for Cyber Security Faculty of Information Science and Technology Universiti Kebangsaan Malaysia Bangi Malaysia

ISBN: (数字)9781837243150

controlling the temperature in chemical reactors, heating furnaces, distillation columns, and reboilers for circulating heatin g fluids is crucial across all industries. This project is a simulation-based study where both PID-cascade and fractional order PID (FO-PID) controllers were used to control the temperature of water in the continuously stirred tank heater system. The simulation was designed by using SIMULINK. Initially, the work reproduces results from a previous study that evaluated the performance of PID cascade controller applied for controlling the temperature of continuous stirred tank heater. Building on this foundat ion, a novel fractional-order PID (FO-PID) controller was designed and its parameters were optimized using the Whale Optimizer Algorithm (WOA). Results showed that the FO-PID outperforms the PID-cascade controller in terms of settling time and percentage overshoot. This study demonstrates significant advancements in process innovation and optimization, supporting sustainable industrial systems. The FO-PID controller in comparison to the Cascade PID controller reduced the percentage overshoot by approximately 97%, reduced settling time by 87% and maintained comparable steady-state error.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Recurrent Attentional Reinforcement Learning for Machinery Fault Diagnosis

SSRN

引用

SSRN 2024年

作者： Tang, Zhenhui Wang, Jingcheng Wu, Shunyu The Department of Automation The Key Laboratory of System Control and Information Processing Ministry of Education of China The Shanghai Engineering Research Center of Intelligent Control and Management Shanghai Jiao Tong University No.800 Dongchuan Road Shanghai200240 China The SJTU Sanya Yazhou Bay Institute of Deepsea Science and Technology Sanya572024 China The Autonomous Systems and Intelligent Control International Joint Research Center Xi’an Technological University Xi’an710021 China

Recognizing fault types of machinery system is a fundamental but challenging task in industrial application. Although remarkable progress has been attained by learning fault features and predicting the corresponded fault type with deep neural networks, the existing fault diagnosis pipelines usually learn non-discriminative information. Contextual sequence dependency between the localized time fragments is often ignored. To deal with these problem, a recurrent attention framework with reinforcement learning is proposed to find a series of informative features of local time fragments related to different faults in an iterative manner. Fault labels are further predicted on these time fragments. The proposed framework also explicitly models long-term dependencies among these attentional time fragments to capture historical fault information. Experiments on two typical machinery systems, bearing system and hydraulic system, show that the proposed framework achieves superior diagnosis performance and increases no computation burden on CPU. © 2024, The Authors. All rights reserved.

关键词： Reinforcement learning

来源：评论

学校读者我要写书评

暂无评论

RFT Based Efficient Broadband Chebyshev Filter Design of (K and Ka) Range

RFT Based Efficient Broadband Chebyshev Filter Design of (K ...

引用

International Conference on engineering and Emerging Technologies (ICEET)

作者： Raqia S. Almusali Dogu Cagdas Atilla Department of electrical and computer science Altinbas university Electric Autonomous Unmanned Vehicle Application and Research Center (AUTONOM) Altinbas University Istanbul Türkıye Faculty of Engineering and Architecture Altinbas University Istanbul Türkıye

ISBN: (数字)9798350316926

ISBN: (纸本)9798350316933

A stepped impedance bandpass Chebyshev filter design covers the K and Ka bands which includes three of 5G RF2 bands n257, n258, and n261 via real frequency technique (RFT) is studied, synthesized and simulated in this work. RFT is a complex math work, for that reason MATLAB employed for generating polynomials needed for this technique, ADS utilized for designing and simulating the BP-filter for verifying the resulted gain of the circuit. The characteristics of the filter listed in details in this paper, the characteristics of the final design after optimization are fl, f2 are 22.22, and 29.5 GHz respectively, Insertion Loss (IL) is set as 0.5dB. The achieved attenuation reached -55, the initial and final number of order before and after the optimization are n=3 and n=8 respectively. RFT technique yielded an accurate synthesized values, small size, and sharp slop.

关键词： Band-pass filters Microstrip filters Regulators Simulation Chebyshev approximation Attenuation Broadband communication

来源：评论

学校读者我要写书评

暂无评论

Analysis of the Effect of Time Delay for Unmanned Aerial Vehicles with Applications to Vision Based Navigation

arXiv

引用

arXiv 2022年

作者： Humais, Muhammad Ahmed Chehadeh, Mohamad Boiko, Igor Zweiri, Yahya The Center for Autonomous Robotic Systems Khalifa University Abu Dhabi United Arab Emirates The Department of Electrical Engineering and Computer Science The Department of Aerospace Engineering Khalifa University Abu Dhabi United Arab Emirates

In this paper, we analyze the effect of time delay dynamics on controller design for Unmanned Aerial Vehicles (UAVs) with vision based navigation. Time delay is an inevitable phenomenon in cyber-physical systems, and has important implications on controller design and trajectory generation for UAVs. The impact of time delay on UAV dynamics increases with the use of the slower vision based navigation stack. We show that the existing models in the literature, which exclude time delay, are unsuitable for controller tuning since a trivial solution for minimizing an error cost functional always exists. The trivial solution that we identify suggests use of infinite controller gains to achieve optimal performance, which contradicts practical findings. We avoid such shortcomings by introducing a novel nonlinear time delay model for UAVs, and then obtain a set of linear decoupled models corresponding to each of the UAV control loops. The cost functional of the linearized time delay model of angular and altitude dynamics is analyzed, and in contrast to the delay-free models, we show the existence of finite optimal controller parameters. Due to the use of time delay models, we experimentally show that the proposed model accurately represents system stability limits. Due to time delay consideration, we achieved a tracking results of RMSE 5.01 cm when tracking a lemniscate trajectory with a peak velocity of 2.09 m/s using visual odometry (VO) based UAV navigation, which is on par with the state-of-the-art. Copyright © 2022, The Authors. All rights reserved.

关键词： Time delay

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：