检索结果-内蒙古大学图书馆

arXiv 2022年

作者： Zheng, Shiqi Shi, Peng Zhang, Huiyan the School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China the School of Electrical and Electronic Engineering The University of Adelaide AdelaideSA5005 Australia the College of Engineering and Science Victoria University MelbourneVIC8001 Australia the National Research Base of Intelligent Manufacturing Service Chongqing Technology and Business University Chongqing400067 China

This study focuses on periodic event-triggered (PET) cooperative output regulation problem for a class of nonlinear multi-agent systems. The key feature of PET mechanism is that event-triggered conditions are required to be monitored only periodically. This approach is beneficial for Zeno behavior exclusion and saving of battery energy of onboard sensors. At first, new PET distributed observers are proposed to estimate the leader information. We show that the estimation error converges to zero exponentially with a known convergence rate under asynchronous PET communication. Second, a novel PET output feedback controller is designed for the underlying strict feedback nonlinear multi-agent systems. Based on a state transformation technique and a local PET state observer, the cooperative semi-global output regulation problem can be solved by the proposed new control design technique. Simulation results of multiple Lorenz systems illustrate that the developed control scheme is effective. © 2022, CC BY.

关键词： Multi agent systems

来源：评论

学校读者我要写书评

暂无评论

Model-Based and Data-Driven control of Event- and Self-Triggered Discrete-Time LTI systems

arXiv

引用

arXiv 2022年

作者： Wang, Xin Berberich, Julian Sun, Jian Wang, Gang Allgöwer, Frank Chen, Jie The Key Laboratory of Intelligent Control and Decision of Complex System Beijing Institute of Technology Beijing10081 China The Beijing Institute of Technology Chongqing Innovation Center Chongqing401120 China The University of Stuttgart Institute for Systems Theory and Automatic Control Stuttgart70550 Germany The Department of Control Science and Engineering Tongji University Shanghai201804 China The State Key Lab of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

The present paper considers the model-based and data-driven control of unknown linear time-invariant discretetime systems under event-triggering and self-triggering transmission schemes. To this end, we begin by presenting a dynamic event-triggering scheme (ETS) based on periodic sampling, and a discrete-time looped-functional approach, through which a model-based stability condition is derived. Combining the model-based condition with a recent data-based system representation, a data-driven stability criterion in the form of linear matrix inequalities (LMIs) is established, which also offers a way of co-designing the ETS matrix and the controller. To further alleviate the sampling burden of ETS due to its continuous/periodic detection, a self-triggering scheme (STS) is developed. Leveraging pre-collected input-state data, an algorithm for predicting the next transmission instant is given, while achieving system stability. Finally, numerical simulations showcase the efficacy of ETS and STS in reducing data transmissions as well as of the proposed co-design methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear matrix inequalities

来源：评论

学校读者我要写书评

暂无评论

Towards Energy-Efficiency: Integrating MATD3 Reinforcement Learning Method for Computational Offloading in RIS-Aided UAV-MEC Environments

引用

IEEE Internet of Things Journal 2025年

作者： Wu, Liangshun Zhang, Cong Zhang, Bin Du, Jianbo Qu, Junsuo Key Laboratory of Embedded System and Service Computing Tongji University Ministry of Education Shanghai201804 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai201210 China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai200240 China Xi'an Key Laboratory of Advanced Control and Intelligent Process School of Automation Xi'an University of Posts & Telecommunications Xi'an710061 China Xinjiang University of Political Science and Law Tumushuke832003 China School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Department of Computer City University of Hong Kong 999077 Hong Kong School of Communications and Information Engineering Xi'an University of Posts & Telecommunications Xi'an710061 China

With the proliferation of IoT devices, there is an escalating demand for enhanced computing and communication capabilities. Mobile Edge Computing (MEC) addresses this need by relocating computing resources to the network edge, thereby delivering swifter and more efficient services. This paper introduces a computation offloading and energy consumption optimization framework that leverages Reconfigurable intelligent Surfaces (RIS), Unmanned Aerial Vehicles (UAVs), and MEC. The scheme aims to maximize energy efficiency through the optimization of task allocation, RIS phase shifts, and UAV trajectories. By employing the Multi-Agent Twin Delayed Deep Deterministic Policy Gradient (MATD3) reinforcement learning algorithm, the paper further refines UAV trajectories and RIS configurations. The simulation results indicate that the proposed method surpasses the traditional Concave-Convex Procedure (CCCP) algorithm in both UAV trajectory control and RIS configuration, demonstrating quicker convergence and enhanced stability. The method proves to be adaptable to diverse environments and tasks, showcasing notable benefits in RIS-assisted interference suppression, particularly with large RIS, thereby enhancing UAV data reception rates. Additionally, MATD3 exhibits faster and smoother convergence for extended task durations and smaller RIS scenarios. Simulation results reveal that UAVs tend to move closer to RIS, with energy efficiency falling as IoT tasks increase, affirming the proposed algorithm's high energy efficiency and effectiveness. © 2025 IEEE.

关键词： Unmanned aerial vehicles (UAV)

来源：评论

学校读者我要写书评

暂无评论

An ensemble model based on weighted support vector regression and its application in annealing heating process

引用

Science china(Information Sciences) 2019年第4期62卷 203-205页

作者： Yongyue ZHANG Weihua CAO Yali JIN Min WU School of Information Science and Engineering Central South University School of Automation China University of Geosciences Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,In the steel industry, the annealing heating production directly impacts the economic benefits of enterprises; hence, accurately predicting the required gas flow is very important [1]. On account of high equipment complexity, it costs lots of time for maintaining a traditional mechanism model at a good working condition; data-driven model, such

关键词： SVR An ensemble model based on weighted support vector regression and its application in annealing heating process

来源：评论

学校读者我要写书评

暂无评论

A Cell Potential and Motion Pattern Driven Multi-robot Coverage Path Planning Algorithm 14th

A Cell Potential and Motion Pattern Driven Multi-robot Cover...

引用

14th International Conference on Bio-inspired Computing: Theories and Applications, BIC-TA 2019

作者： Xu, Meng Xin, Bin Dou, Lihua Gao, Guanqiang School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing100081 China

ISBN: (纸本)9789811534249

This paper proposes an intelligent "Cell Potential and Motion Pattern driven Coverage (CPMPC)" algorithm to solve a cooperative coverage path planning problem for multiple robots in two-dimensional target environment. The target environment is divided into cell areas according to the detection range of robot, and the cell matrix is given correspondingly. The values in the cell matrix are defined as cell potential, which represents the number of times each cell is detected by robots. The priority of the robot’s neighbor cell is called the motion pattern. At different moments, robots can choose within different motion patterns. Genetic algorithm (GA) is used to optimize the combination of motion patterns. By taking account obstacle avoidance and collision avoidance into consideration, the CPMPC algorithm adopts a double-layer choice strategy driven by cell potential and motion pattern to generate the next waypoint. Furthermore, this algorithm contains two optimal strategies: avoiding collision and jumping out of the detected area. Compared with the pattern-based genetic algorithm, the results obtained by us show that the CPMPC algorithm could solve the multi-robot coverage path planning (MCPP) problem effectively with guarantee of complete coverage, and improved makespan. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Multipurpose robots

来源：评论

学校读者我要写书评

暂无评论

Denoising Surface Electromyography Signals Based on Complementary Ensemble Empirical-Mode Decomposition and Multi-Scale Entropy

Denoising Surface Electromyography Signals Based on Compleme...

引用

第40届中国控制会议

作者： Rennong Wang Juan Zhao Zhentao Liu Feng Wang Jinhua She Graduate School of Engineering Tokyo University of Technology School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education

Surface electromyography（sEMG） can capture muscle activity and motor function,which is considered an effective tool for assessing local muscle *** to the complex environment and individual differences,the collected sEMG signals contain lots of noising information.A novel method is devised to effectively solve the problem of sEMG denoising based on complementary ensemble empirical mode decomposition（CEEMD） and multi-scale entropy（MSEn）.The method uses the concept of MSEn and analyzes the feature trend of MSEn of intrinsic mode functions（IMFs） obtained by *** method adaptively determines the main components of IMFs according to the complexity of sEMG on the time scale,avoiding insufficient selection based on *** experiments verified the effectiveness of the method.

关键词： Surface electromyography complementary ensemble empirical mode decomposition multi-scale entropy data processing

来源：评论

学校读者我要写书评

暂无评论

Stability analysis of linear systems with two additive time-varying delays via the extended reciprocally convex matrix inequality

Stability analysis of linear systems with two additive time-...

引用

第40届中国控制会议

作者： Chen Yan Chuan-Ke Zhang Xi-Zi Zhou School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Art and Design Wuhan University of Technology

This paper investigates the stability of linear systems with two additive time-varying delays. Firstly, an augmented Lyapunov-Krasovskii functional(LKF) is constructed by introducing a novel augmented term which contains the derivative of state vector into integral terms. Then the extended reciprocally convex matrix inequality together with the Wirtinger integral inequality is used to estimate the derivative of the proposed LKF. As a result, a stability criterion with less conservatism is established. Finally, the advantage of the stability criterion is demonstrated through a numerical example and the application of the stability criterion to stability analysis of load frequency control is illustrated.

关键词： linear system additive time-varying delays stability analysis reciprocally convex matrix inequality

来源：评论

学校读者我要写书评

暂无评论

Motion Semantic Enhancement and Autonomous Information Mining for Static-Dynamic Visual Emotion Recognition in Human–Robot Interaction

引用

IEEE Transactions on Instrumentation and Measurement 2025年 74卷

作者： Cheng-Shan Jiang Zhen-Tao Liu Edwardo F. Fukushima Jinhua She School of Automation Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Ministry of Education and Engineering Research Center of Intelligent Technology for Geo-Exploration China University of Geosciences Wuhan China School of Engineering Tokyo University of Technology Hachioji Japan

The advancement of static-dynamic visual emotion recognition (DVER) plays a pivotal role in the evolution of intelligent and empathetic machines. Currently, the progress of static visual emotion recognition (SVER) faces challenges, primarily the need to balance model efficiency with robust recognition performance. Moreover, obstacles such as noisy data and limited labeled datasets restrict models from effectively learning the appearance features and dynamic dependencies intrinsic to DVER. In the realm of SVER, facial pixel, and semantic representation are derived using a lightweight surface and landmark features embedding network, followed by neuron-energy-based feature fusion-filtering to enhance the fusion of semantic representations positively. For DVER, a Global Anchor-Dependent Noisy Emotional Data Filtering (GADNEF) method is employed for noisy label learning (NLL), facilitating clip-wise filtering of ambiguous data via iterative computations of frame-wise attention statistics across batches. Furthermore, a self-supervised learning (SSL) paradigm based on a unified appearance and motion-guided masked autoencoder (UAMGMAE) is implemented, enabling large-scale knowledge transfer tailored for video-based facial expression analysis. Our approach has achieved accuracies of 97.07%, 98.90%, 61.39%, and 92.28% on SVER datasets including KDEF, RaFD, SFEW, and RAF-DB, respectively, while the weighted average recall (WAR) and unweighted average recall (UAR) on DVER datasets such as DFEW and MAFW were 75.12%, 64.37%, 55.26%, and 42.53%, respectively. A preliminary application experiment has also been conducted to validate the practical applicability of our method within human–robot interaction (HRI) scenarios.

关键词： Noise measurement Visualization Emotion recognition Semantics Human-robot interaction Filtering Feature extraction Training Neurons Transformers

来源：评论

学校读者我要写书评

暂无评论

Self-Attention based Temporal Intrinsic Reward for Reinforcement Learning

Self-Attention based Temporal Intrinsic Reward for Reinforce...

引用

Chinese automation Congress (CAC)

作者： Zhuo Jiang Daiying Tian Qingkai Yang Zhihong Peng School of Automation Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex System Beijing China Peng Cheng Laboratory Shenzhen China

ISBN: (纸本)9781665426480

This paper proposes a self-attention based temporal intrinsic reward model for reinforcement learning (RL), to synthesize the control policy for the agent constrained by the sparse reward in partially observable environments. This approach can solve the problem of temporal credit assignment to some extent and deal with the low efficiency of exploration. We first introduce a sequence-based self-attention mechanism to generate the temporary features, which can effectively capture the temporal property of the task for the agent. During the training process, the temporary features are employed in each sampled episode to elaborate the intrinsic rewards, which is combined with the extrinsic reward to help the agent learn a feasible policy. Then we use the meta-gradient to update this intrinsic reward model in order that the agent can achieve better performance. Experiments are given to demonstrate the superiority of the proposed method.

关键词： Training automation Reinforcement learning Task analysis

来源：评论

学校读者我要写书评

暂无评论

Outdoor 3D reconstruction method based on multi-line laser and binocular vision ⁎

引用

IFAC-PapersOnLine 2020年第2期53卷 9554-9559页

作者： Xu Jian Xin Chen Wenpeng He Xuan Gong School of Automation China University of Geosciences Wuhan 430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan 430074 China

Three-dimensional (3D) reconstruction of substation fittings is of great significance for live working robots. However, the key problem is that active 3D cameras cannot work in outdoor strong light environment, and the passive 3D cameras cannot extract features of weak texture targets. This paper proposes an outdoor 3D reconstruction method based on multi-line laser and binocular vision. To solve the problem that weak texture target has few features, we use multi-line laser to create artificial features. To reduce the interference of natural light on the laser in the images, the frame-difference method is proposed for natural light filtering. Then we use the gray-centroid method to position the multi-line laser accurately. Finally, the binocular vision model is used to complete 3D reconstruction of the target. The experiments show that, compared with traditional 3D reconstruction methods, our 3D reconstruction method can realize 3D reconstruction of outdoor weak texture targets effectively.

关键词： Live working robot outdoor 3D reconstruction binocular vision frame-difference method laser positioning

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：