检索结果-内蒙古大学图书馆

2nd IEEE International Conference on Electronics, control, Optimization and Computer Science, ICECOCS 2020

作者： Kumari, Neetu Rakotondrabe, Micky CNRS - University Bourgogne Franche-Comté FEMTO-ST Institute Automatic Control and Micromechatronic Systems Department Besançon France Laboratoire Génie de Production Tarbes France

ISBN: (纸本)9781728169217

Piezoelectric and pyroelectric effects are well known and have been widely used in the field of energy harvesting, actuators or sensors. This paper presents a cantilever structure based on a lead free piezoelectric-pyroelectric hybrid transducer based on PVDF (Polyvinylidene fluoride) piezoelectric, a Lithium Niobate piezoelectric, and a SMA (Shape Memory Alloy) materials which is capable of simultaneously harvesting mechanical and thermal energies. The piezoelectric cantilever has been studied using finite element modeling for application in self-powered sensors in automobiles. The cantilever are able to resonate under 300 Hz of frequency range. We calculated the output voltage from both the thermal and vibrational excitations with the help of Comsol Multiphysics finite-element software. We shows that the configuration in which the PVDF is the top layer, then SMA as the middle layer and Lithium niobate as the bottom layer has the highest value of harvested energy with an output voltage up to 12Vpp. © 2020 IEEE.

关键词： Energy harvesting

来源：评论

学校读者我要写书评

暂无评论

Numerical simulation of regenerative thermal oxidizer 10th

Numerical simulation of regenerative thermal oxidizer

引用

10th China Academic Conference on Printing and Packaging, 2019

作者： Chen, Xulan Hou, Heping Liu, Shanhui Wen, Qing Faculty of Printing Packaging Engineering and Digital Media Technology Xi’an University of Technology Xi’an China North Automatic Control Technology Institute China North Industries Group Corporation Taiyuan China

ISBN: (纸本)9789811518638

The emission of VOCs (Volatile Organic Compounds, VOCs) during packaging and printing production endangers human health and causes serious pollution to the environment. The regenerative thermal oxidizer is a widely used VOCs processing equipment. In order to fully grasp the law between its structural parameters and treatment effects, this paper numerically simulates the regenerative thermal oxidizer. Firstly, the working principle is analyzed, and the internal structure and 3D modeled are designed. Secondly, the simulation calculation of the regenerator is carried out, and the variation of temperature and pressure inside the regenerator is obtained. Thirdly, according to the simulation results and numerical analysis, the relationship between the pressure drop of the regenerator bed and the bed height, thermal efficiency and bed height under different mesh types is obtained. The results show that when the pore shape and flow rate are the same, the pressure drop is positively correlated with the bed height. The thermal efficiency increases with the increase of the bed height until the thermal efficiency reaches 100%. When the thermal efficiency meets the actual operation requirements, the bed height should be reduced as much as possible to improve equipment utilization. © Springer Nature Singapore Pte Ltd. 2020.

关键词： Pressure drop

来源：评论

学校读者我要写书评

暂无评论

Robust Containment control of Heterogeneous Uncertain Multi-Agent systems under Markovian Switching Topologies

Robust Containment Control of Heterogeneous Uncertain Multi-...

引用

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

作者： Haihua Guo Cong Bi Xiang Xu Shenzhen Key Laboratory of Control Theory and Intelligent Systems Southern University of Science and Technology Shenzhen China Hong Kong Institute for Data Science City University of Hong Kong Hong Kong China College of Artificial Intelligence Nankai University Tianjin China School of System Design and Intelligent Manufacturing Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350373691

ISBN: (纸本)9798350373707

This study addresses the robust output containment control problem of heterogeneous uncertain multi-agent systems under Markovian switching topologies. A novel distributed output feedback controller is proposed. Based on the internal model approach, the main result shows that the output of each follower agent converges to the convex hull formed by the outputs of the leader agents under the proposed distributed controller. An illustrative example is given to validate the effectiveness of the proposed controller.

关键词： Switches control systems Formation control Topology Output feedback Multi-agent systems

来源：评论

学校读者我要写书评

暂无评论

Average consensus with resilience and privacy guarantees without losing accuracy

arXiv

引用

arXiv 2025年

作者： Ramos, Guilherme Silvestre, Daniel Teixeira, André M.H. Pequito, Sérgio Instituto Superior Técnico Universidade de Lisboa Instituto de Telecomunicações Lisboa1049-001 Portugal COPELABS Lusófona University Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Caparica2829-516 Portugal Division of Systems and Control Department of Information Technology Uppsala University Sweden Instituto Superior Técnico Universidade de Lisboa Institute for Systems and Robotics Instituto Superior Técnico Universidade de Lisboa Lisbon1049-001 Portugal

This paper addresses the challenge of achieving private and resilient average consensus among a group of discrete-time networked agents without compromising accuracy. State-of-the-art solutions to attain privacy and resilient consensus entail an explicit trade-off between the two with an implicit compromise on accuracy. In contrast, in the present work, we propose a methodology that avoids trade-offs between privacy, resilience, and accuracy. We design a methodology that, under certain conditions, enables non-faulty agents, i.e., agents complying with the established protocol, to reach average consensus in the presence of faulty agents, while keeping the non-faulty agents’ initial states private. For privacy, agents strategically add noise to obscure their original state, while later withdrawing a function of it to ensure accuracy. Besides, and unlikely many consensus methods, our approach does not require each agent to compute the left-eigenvector of the dynamics matrix associated with the eigenvalue one. Moreover, the proposed framework has a polynomial time complexity relative to the number of agents and the maximum quantity of faulty agents. Finally, we illustrate our method with examples covering diverse faulty agents scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Differential privacy

来源：评论

学校读者我要写书评

暂无评论

A Swing-Up and Stable control Strategy for Pendubot Based on Nonlinear Model Predictive Method

A Swing-Up and Stable Control Strategy for Pendubot Based on...

引用

2023 China Automation Congress, CAC 2023

作者： Wang, Lejun Liu, Yiqin Zhang, Ruihuan Huang, Zixin Cai, Zhen School of Automation School of Industrial Internet Chongqing University of Posts and Telecommunications Chongqing400065 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan430200 China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan430205 China School of Information Engineering Wuhan City Polytechnic Wuhan430064 China

ISBN: (纸本)9798350303759

The control objective of Pendubot is to stabilise the system in a vertically upward position by swinging up from a vertically downward position. Facing various physical constraints in practical applications, this paper proposes a swing-up stabil-isation control strategy based on a nonlinear model prediction method to accomplish the above control objective. On the basis of the system dynamics model, the forward Euler method is used to construct a nonlinear prediction model of the system. According to the control objectives and physical constraints of the system, the performance index function is designed, and then the control inputs of each sampling cycle are obtained through rolling optimisation and feedback correction, so that the system state gradually converges to the target trajectory, thus achieving the motion control objective. Based on the simulation results, it can be seen that the strategy proposed in this paper is efficient and robust under external disturbances. © 2023 IEEE.

关键词： Model predictive control

来源：评论

学校读者我要写书评

暂无评论

Robust Optimization for Quantum Reinforcement Learning control using Partial Observations

arXiv

引用

arXiv 2022年

作者： Jiang, Chen Pan, Yu Wu, Zheng-Guang Gao, Qing Dong, Daoyi State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control College of Control Science and Engineering Zhejiang University Hangzhou310027 China The School of Automation Science and Electrical Engineering Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Beijing100191 China The School of Engineering and Information Technology University of New South Wales CanberraACT2600 Australia

The current quantum reinforcement learning control models often assume that the quantum states are known a priori for control optimization. However, full observation of quantum state is experimentally infeasible due to the exponential scaling of the number of required quantum measurements on the number of qubits. In this paper, we investigate a robust reinforcement learning method using partial observations to overcome this difficulty. This control scheme is compatible with near-term quantum devices, where the noise is prevalent and predetermining the dynamics of quantum state is practically impossible. We show that this simplified control scheme can achieve similar or even better performance when compared to the conventional methods relying on full observation. We demonstrate the effectiveness of this scheme on examples of quantum state control and quantum approximate optimization algorithm. It has been shown that high-fidelity state control can be achieved even if the noise amplitude is at the same level as the control amplitude. Besides, an acceptable level of optimization accuracy can be achieved for QAOA with noisy control Hamiltonian. This robust control optimization model can be trained to compensate the uncertainties in practical quantum computing. © 2022, CC BY.

关键词： Robust control

来源：评论

学校读者我要写书评

暂无评论

An Adaptive Dynamic Programming Algorithm Based on ITF-OELM for Discrete-Time systems

An Adaptive Dynamic Programming Algorithm Based on ITF-OELM ...

引用

第33届中国控制与决策会议

作者： Xiaofei Zhang Hongbin Ma Junyong Chen Weixue Li School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems

Adaptive dynamic programming(ADP) is a kind of intelligent control method,and it is a non-model-based method that can directly approximate the optimal control policy via online *** gradient algorithm is usually used to update weights of action networks and critic networks,however it is clear that gradient descent-based learning methods are generally very slow due to improper learning steps or may easily converge to local *** this paper,in order to overcome those disadvantages of gradient descent-based learning methods,a novel ADP algorithm based on initial-training-free online extreme learning machine(ITF-OELM),in which the critic network link weights of hidden nodes to output nodes can be obtained by least squares instead of gradient algorithm,is ***,the ADP algorithm based on ITF-OELM is tested on a discrete time torsional pendulum system,and simulation results indicate that this algorithm makes the system converge in a shorter time compared with the ADP based on gradient algorithm.

关键词： Adaptive Dynamic Programming Extreme Learning Machine Discrete-time systems

来源：评论

学校读者我要写书评

暂无评论

Teaching Nonlinear Model Predictive control with MATLAB/Simulink and an Internal Combustion Engine Test Bench

引用

IFAC-PapersOnLine 2020年第2期53卷 17190-17197页

作者： Martin Keller Dennis Ritter Lukas Schmitt Severin Hänggi Christopher Onder Dirk Abel Thivaharan Albin Institute of Automatic Control RWTH Aachen University Aachen Germany Institute for Dynamic Systems and Control ETH Zurich Zurich Switzerland Embotech AG Zurich Switzerland

Model Predictive control (MPC) is used for more and more applications in an industrial context. The applications are characterized by increasing complexity while the available computation time is getting smaller and smaller. MPC is the most important advanced control technique with even increasing importance. Hence, this topic should be covered in control lectures during the academic studies in order to prepare students for their future work. For the successful implementation of MPC algorithms, knowledge from multiple disciplines is crucial and needs to be taught. Besides teaching knowledge in classical control theory, especially fundamentals in the fields of modeling, simulation and numerical optimization are required for understanding MPC. Programming skills are inevitable to apply the concept in real-world applications. This paper presents a concept for teaching MPC from the theory to the application to real-world systems. Details about the lectures covering the relevant topics are given. In the hands-on exercises, students implement their own linear as well as nonlinear MPC in MATLAB/Simulink. As example application in the exercises, the air path of a turbocharged diesel engine with high pressure exhaust gas recirculation is investigated. At the end of the semester, students can test their developed controllers on a real diesel engine test bench and compete against each other for the best control performance.

关键词： Nonlinear Model Predictive control Modeling Optimization Engine control

来源：评论

学校读者我要写书评

暂无评论

Modeling and operating point analysis for aquatic translational motion of a cross-medium vehicle

Modeling and operating point analysis for aquatic translatio...

引用

第42届中国控制会议

作者： Minghao Dou Xuchen Liu Dongyue Huang Biao Wang Jinqiang Cui Qinyuan Ren Lihua Dou Jie Chen Ben M.Chen Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Department of Mechanical and Automation Engineering The Chinese University of Hong Kong College of Automation Engineering Nanjing University of Aeronautics and Astronautics Peng Cheng Laboratory College of Control Science and Engineering Zhejiang University Beijing Institute of Technology

Modeling of cross-medium vehicles with complex shapes still requires a thorough *** paper proposes a multi-method combination modeling approach to tackle such a ***-principle model is derived to determinate a model *** are then set up to estimate parameters related to its rigid-body model and propulsion *** fluid dynamics(CFD) is performed to calculate and identify coefficients related to surrounding *** on the model obtained,we systematically investigate the possible steady motion of the cross-medium vehicle and analyze their related *** are instrumental for designing controllers for the vehicle to perform autonoumous missions.

关键词：

来源：评论

学校读者我要写书评

暂无评论

High-Speed Trajectory Tracking control for Quadrotors via Deep Reinforcement Learning

High-Speed Trajectory Tracking Control for Quadrotors via De...

引用

Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Hean Hua Hang Zhong Hui Zhang Yongchun Fang Yaonan Wang College of Electrical and Information Engineering Hunan University Changsha China National Engineering Research Center for Robot Visual Perception and Control Technology Changsha China School of Robotics Hunan University Changsha China Institute of Robotics and Automatic Information System College of Artificial Intelligence Nankai University Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798350379228

ISBN: (纸本)9798350390780

This paper presents a learning-based high-speed trajectory tracking control strategy for quadrotors, which achieves efficient learning and strong reliability by the collaboration of deep reinforcement learning (RL) and self-tuning mechanism. Different from existing methods, the proposed strategy is designed to explore optimal control performance by taking advantage of model-based self-tuning mechanism and deep reinforcement learning. Specifically, the self-tuning guided deep RL scheme is put forward for quadrotors, with superior learning efficiency and strong adaptability. Firstly, a novel self-tuning mechanism is constructed and some auxiliary variables are introduced to enhance the tracking performance. Then, based on the model-driven self-tuning design, the deep RL is proposed to achieve model-guided learning, where the tuning actions are adopted in the evaluation process during training, aiming at removing the bad explorations by the carefully designed parallel evaluation. Finally, the convergence is analyzed based on the proposed learning framework, which indicates the efficient cooperation of exploration and self-tuning mechanism. To verify the effectiveness of the proposed controller, the guided training and hardware experiments are implemented to show efficient cooperation and satisfactory high-speed trajectory tracking control of the proposed method.

关键词： Training Adaptation models Trajectory tracking Heuristic algorithms Optimal control Deep reinforcement learning Hardware

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：