检索结果-内蒙古大学图书馆

Optimal Tracking control for Leader-Following Consensus of Nonlinear Multiagent Systems

IEEE Transactions on Systems, Man, and Cybernetics: Systems 2025年第5期55卷 3098-3107页

作者： Su, Wei Mu, Chaoxu Yang, Xiong Bian, Jinshan Sun, Changyin Tianjin University School of Control Science and Engineering Tianjin300072 China Anhui University Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education Hefei230601 China Anhui University School of Artificial Intelligence Hefei230000 China Southeast University School of Automation Nanjing210096 China

This article investigates distributed adaptive leader-following consensus tracking optimal control problem for nonlinear multiagent systems (MASs) subject to unknown nonlinearities and uncertain external disturbances. In contrast to traditional centralized control, the primary challenge is that only partial subsystems can access the desired reference trajectory. To address this, positive time-varying smooth function compensating terms are introduced to counteract the effects of uncertain external disturbances and unknown desired trajectories. Then, by fusing consensus errors into the backstepping technique, feedforward controllers are given. On this basis, the controlled nonlinear systems are transformed into an equivalent affine form, and feedback optimal controllers are designed using actor and critic neural networks (NNs) to execute control behavior and evaluate control performance. The whole control laws comprise both feedforward and feedback controllers. The proposed distributed adaptive consensus control protocol can simultaneously achieve desired optimal control performance and minimize the cost function, as demonstrated through theoretical analysis and simulation results. © 2025 IEEE.

关键词： Cost functions

来源：评论

学校读者我要写书评

暂无评论

State Estimation of a Spatial 2-D Linear Diffusion Process With Mobile Sensors

引用

IEEE Transactions on automation science and engineering 2025年 22卷 12024-12032页

作者： Zhang, Xiao-Wei Chen, Kui Wu, Huai-Ning Wang, Jin-Liang Wang, Zi-Peng Beijing University of Technology School of Information Science and Technology Beijing100124 China Tiangong University School of Control Science and Engineering Tianjin300387 China Beihang University Science and Technology on Aircraft Control Laboratory School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China Tiangong University Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems School of Computer Science and Technology Tianjin300387 China Beijing University of Technology School of Information Science and Technology Beijing Institute of Artificial Intelligence Beijing100124 China

This paper studies the state observer design of a spatial two-dimensional (2-D) linear diffusion process described by a linear parabolic partial differential equation (PDE) under mobile sensors. Firstly, we analyze the well-posedness of the PDE system and give the structure form of the state observer with mobile sensors. Subsequently, according to the number of mobile sensors, the 2-D space domain is divided into multiple sub-domains, and the mobile sensors are guided by the projection operator method, which can guarantee that the mobile sensors can only move in their respective 2-D sub-domains. Then, in the light of Lyapunov theory, Poincaré-Wirtinger inequality and Barbalat lemma, we propose an observation-plus-guidance design method to ensure the asymptotic stability of the state estimation error system. In the designed mobile strategy, the actual guidance of mobile sensors is essentially a physical synthesis of two direction guidance laws, where two dimensional guidance laws are designed separately. Moreover, the existence condition of the observer is given by linear matrix inequalities. At last, a numerical example is provided to demonstrate the efficacy of the proposed design scheme. © 2004-2012 IEEE.

关键词： Asymptotic stability

来源：评论

学校读者我要写书评

暂无评论

Thermal constraint control of reversible solid oxide cell for optimal system efficiency

引用

International Journal of Hydrogen Energy 2025年 134卷 198-211页

作者： Xu, Yuanwu Yin, Jie Wang, Jingjing Wu, Xiao-long Peng, Jingxuan Tang, Ruifeng Zou, Suhang Fu, Xiaowei Li, Xi School of Artificial Intelligence and Automation Wuhan University of Science and Technology Hubei Wuhan430081 China School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Hubei Wuhan430074 China School of Information Engineering Nanchang University Jiangxi Nanchang330031 China School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore China-Poland Belt and Road Joint Laboratory on Measurement and Control Technology Huazhong University of Science and Technology Hubei Wuhan430074 China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen518055 China

Reversible solid oxide cell (RSOC) demonstrates considerable promise in multimodal energy conversion architectures, particularly as a technology for hydrogen-based energy storage systems. Nevertheless, under dynamic operating regimes with time-varying current inputs, realizing time-efficient and reliable transitions to steady-state operation remains difficult. This difficulty arises from the intricate coupling of thermal, electrical, and gaseous processes within the RSOC system. This study aims to address these challenges by developing a 5 kW mathematical model of the RSOC system. The proposed model enables systematic investigation of thermal safety issues arising during current switching operations while introducing a thermal constraint control strategy to enhance both system efficiency and thermal safety performance. This efficiency-driven study employs the Grid Search algorithm to identify optimal steady-state operating points for the RSOC system, ensuring strict adherence to safety constraints across varying current inputs. Furthermore, by integrating the pre-identified optimal operating points as feedforward control with Model Predictive control (MPC)-based feedback correction, this hybrid strategy effectively mitigates stack temperature gradient overshoot while synchronously ensuring optimal system efficiency throughout current transition processes. Under simulated variable current inputs, the proposed RSOC system model and control strategy demonstrate the capability to constrain stack temperature gradient overshoot within 2.3K while enhancing transient efficiency by 5 %–8 %, achieving a peak system efficiency of 85 %. It provides a novel methodology for safe and efficient working with intermittent renewable energy. © 2025 Hydrogen Energy Publications LLC

关键词： Thermal variables control

来源：评论

学校读者我要写书评

暂无评论

Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

引用

IEEE Robotics and automation Letters 2025年第6期10卷 6456-6463页

作者： Sun, Ning Wang, Zelong Cheng, Long Li, Houcheng Niu, Ben Sun, Xijin Li, Ke Shandong Normal University School of Information Science and Engineering Jinan China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Shandong University Institute of Intelligent Medical Engineering School of Control Science and Engineering Jinan China

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while providing sufficient assistance torque is still a challenge. This paper develops a series-parallel self-aligning index finger exoskeleton to assist the index finger in flexion/extension and adduction/abduction training. A series-parallel mechanism driven by two motors simultaneously was proposed for the metacarpophalangeal (MCP) joint, which can ensure human-robot joint axes self-alignment and increase the joint assistance torque. A kinematic compatibility analysis method was proposed, and the kinematic compatibility of the series-parallel mechanism was analyzed. The degrees of freedom and forward kinematics of the proposed mechanism were analyzed, and its workspace was calculated, which results show that the motion range of the MCP joint can meet the grasping training requirements. Preliminary experiments were carried out, and the results indicate that the motion trajectory coefficients of the marker points at the MCP, PIP, and DIP joints averaged for all subjects with and without the proposed exoskeleton are 0.993, 0.956, and 0.939, respectively, which can verify the kinematic transparency of the proposed mechanism. The assistance torque generated by the proposed mechanism on the MCP joint can meet the joint assistance torque requirements. In a word, the proposed exoskeleton can achieve flexion/extension and adduction/abduction training, human-robot joint axes self-alignment, and provide sufficient assistance torque. © 2016 IEEE.

关键词： Exoskeleton (Robotics)

来源：评论

学校读者我要写书评

暂无评论

An FE-S-BiLSTM and Heatmap-Based State-of-Health Estimation Method for Lithium-Ion Batteries

引用

IEEE Sensors Journal 2025年第10期25卷 17727-17738页

作者： Shao, Kui Zhai, Chao Zhang, Chaolong He, Yigang Du, Bolun Wu, Ji China University of Geosciences School of Future Technology Wuhan430074 China China University of Geosciences School of Automation Wuhan430074 China Jinling Institute of Technology College of Intelligent Science and Control Engineering Nanjing211169 China China Electric Power Research Institute Wuhan430074 China Wuhan University School of Electrical Engineering and Automation Wuhan430072 China Hefei University of Technology School of Automotive and Transportation Engineering Anhui Hefei230009 China

Accurate battery state-of-health (SOH) estimation can improve battery reliability and ensure its safe and efficient operation. Therefore, this study proposes a novel method for battery SOH estimation. First, a thermocouple temperature sensor monitors the battery’s operating temperature and provides feedback to the thermostat for precise temperature control during experiments. The battery’s charging voltage and current are measured using voltage transmitters and Hall current sensors, respectively, and the two are fused to obtain the battery’s charging power. Next, 1-D charging power data are converted into 2-D heatmaps using image encoding techniques. The heatmap corresponding to the first cycle is selected as the reference image, and the difference between the heatmaps of subsequent cycles and the reference image is quantified using structural similarity (SSIM). The final results serve as an indicator for battery health. In addition, this study proposes a novel battery SOH estimation model, the feature enhancement-simplification-bidirectional long short-term memory (FE-S-BiLSTM). The feature enhancement layer in the FE-S-BiLSTM model enriches global static features through enhancement learning. Based on the model’s bidirectional long short-term memory (BiLSTM) layer and simplification layer, dynamic features in the time-space domain are double captured. Finally, this study utilizes six batteries and designed a variety of experiments to validate the effectiveness of the proposed method. The experimental design comprises three tasks: SOH estimation based on full-charging data, SOH estimation based on random SOC interval charge data, and cross-battery SOH estimation. The experimental results demonstrate that the proposed SOH estimation method for batteries exhibits significant potential for practical applications. © 2001-2012 IEEE.

关键词： Lithium-ion batteries

来源：评论

学校读者我要写书评

暂无评论

Research on LSTM-based winding state prediction method 7

Research on LSTM-based winding state prediction method

引用

2024 7th International Conference on Power Electronics and control engineering, ICPECE 2024

作者： Wang, Yiyang Guo, Haifeng Li, Jianan Liu, Xinen Li, Xiang Du, Zhongbo Shen, Yang School of Electrical and Automation Engineering Liaoning Institute of Science and Technology Benxi117004 China Liaoning Province Robot Drive Control Engineering Laboratory Benxi117004 China

Mechanical and electrical equipment is widely used in various links of the manufacturing industry and is also the key to the implementation of modern industrial technology. Winding is the core component of transformers, electromagnetic valves, motors, robots, and other mechanical and electrical equipment. The safe and reliable operation of winding is the premise for the healthy operation of industrial equipment. Therefore, taking the core component of many industrial equipment, the winding, as the research object, and aiming to improve the safety and reliability of the equipment, this study focuses on the state prediction method of winding with the help of sensitive feature information. With the rapid development of industrial big data technology, data-driven technology, especially time series prediction technology, has developed rapidly. Considering the characteristics of winding degradation data, a winding state prediction method based on the Long Short-Term Memory (LSTM) approach is proposed. By using experimental data of winding, a health index reflecting their health status is constructed, and the LSTM is utilized for training the health index, thereby achieving time series-based state prediction of winding. This provides reliable support for the health status assessment of industrial mechanical and electrical equipment and enhances the reliability of the equipment. © Published under licence by IOP Publishing Ltd.

关键词： Machine windings

来源：评论

学校读者我要写书评

暂无评论

Distributed Adaptive Coordination control for Autonomous Road Traffic at Multiple Intersections

Distributed Adaptive Coordination Control for Autonomous Roa...

引用

International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Ji, Honghai Shi, Qirui Liu, Shida Fan, Lingling wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9789819639724

As societal demands on traffic control increase, traditional model-based traffic control methods are showing their limitations. This paper introduces a Distributed Adaptive Coordination control (DACC) algorithm, which integrates data-driven control and multi-agent systems, aimed at optimizing traffic signal control across multiple intersections to effectively balance queuing times. Through joint simulation experiments with SUMO and Python, and comparison with the Proportional-Integral-Derivative Coordination control (PIDCC) algorithm, the DACC algorithm has demonstrated advantages in reducing average queuing times and improving traffic flow efficiency. The results indicate that the DACC algorithm excels in managing traffic flow variations. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Traffic signals

来源：评论

学校读者我要写书评

暂无评论

Vibration Suppression of AMBs-High Speed Motor Using an Enhanced Linear Extended State Observer

引用

IEEE Access 2025年 13卷 80822-80833页

作者： Gong, Lei He, Pai Dai, Dali Hua, Zhiguang Chen, Jingwen Shaanxi University of Science and Technology School of Electrical and Control Engineering Xi’an710021 China Chongqing Dema Inverter Motor Research and Development Manufacturing Company Ltd. Chongqing400000 China Northwestern Polytechnical University School of Automation Xi’an710129 China

In order to solve the problem of rotor vibration caused by the unbalanced mass of the Active magnetic bearing (AMBs) rotor system, an Enhanced Linear Extended State Observer (ELESO) is designed based on the linear Extended State Observer (LESO). Firstly, the lumped disturbance including the unbalanced force is observed by ELESO, and the observed value is filtered by the band-pass filter (BF), and secondly, the lumped disturbance is compensated in the frequency band where the peak of rotor vibration is generated, so as to reduce the peak vibration of the rotor, and the saturation of the power amplifier caused by compensation in the full frequency band can be avoided. Then, the poles of the closed-loop AMBs rotor system are analyzed, and it is proved that the proposed control method can ensure the stable operation of the system. Finally, the correctness and effectiveness of the proposed method are verified under the working conditions of no disturbance and sensor runout. The results show that the designed control method has a smaller unbalanced vibration peak and a significant reduction in the control current when the rotor is operating in the full speed range compared with the direct use of LESO. © 2013 IEEE.

关键词： State estimation

来源：评论

学校读者我要写书评

暂无评论

A Data-Driven Adaptive Optimal control with Input Saturation for Driverless Heavy-Duty Truck

A Data-Driven Adaptive Optimal Control with Input Saturation...

引用

International Conference on Artificial Intelligence and Autonomous Transportation, AIAT 2024

作者： Ji, Honghai Yang, Jianfeng Liu, Shida Fan, Lingling Wang, Li School of Electrical and Control Engineering North China University of Technology Beijing100144 China School of Automation Beijing Information Science and Technology University Beijing100192 China

ISBN: (纸本)9789819639687

This paper mainly studies the longitudinal speed tracking problem of driverless heavy-duty trucks based on data-driven methods. A data-driven adaptive optimal control algorithm with control input saturation constraints is proposed in this paper to solve the problems of control input saturation and difficulty in establishing an accurate model in driverless heavy-duty truck systems. First, control constraints are added to the control input saturation problem of driverless heavy-duty trucks. Then, the dynamic linearization technology is used to model the nonlinear system of driverless heavy-duty trucks. After that, an appropriate index function is selected and the Newton-type optimization method is used to obtain the optimal controller. The method proposed in this paper only uses a small amount of input and output data and does not need to establish an accurate mathematical model. The simulation results show that compared with the PID algorithm, the proposed algorithm has advantages in speed tracking when applied to driverless heavy-duty truck systems. © Beijing Paike Culture Commu. Co., Ltd. 2025.

关键词： Automobiles

来源：评论

学校读者我要写书评

暂无评论

Deterministic Learning-Based Tracking control for Parabolic PDE Systems With Infinite-Dimensional Nonlinear Uncertain Dynamics

引用

IEEE Transactions on Automatic control 2025年第5期70卷 3272-3287页

作者： Zhang, Jingting Yuan, Chengzhi Wu, Fen Wang, Cong Cheng, Hong University of Electronic Science and Technology of China Center for Robotics School of Automation Engineering Chengdu611731 China University of Rhode Island Mechanical Industrial and Systems Engineering Department KingstonRI02881 United States North Carolina State University Mechanical and Aerospace Engineering Department RaleighNC27695 United States Shandong University School of Control Science and Engineering Jinan250061 China

In this article, we investigate the joint problem of dynamics learning and tracking control for a class of parabolic partial differential equation (PDE) systems with infinite-dimensional uncertain nonlinear dynamics. A new learning control scheme is proposed based on the deterministic learning (DL) theory. One key feature of the proposed scheme is its capability of accurately learning the system's nonlinear uncertain dynamics during real-time tracking control with provable stability and convergence of the overall PDE closed-loop system. Specifically, the Galerkin method is first employed to deal with the infinite dimensionality of the PDE system;a novel DL-based adaptive learning control scheme is then proposed using dual radial basis function neural networks (RBF NNs), in which a pair of RBF NNs are employed to address, respectively, the matched and unmatched components of uncertain nonlinear system dynamics. This control scheme is finally examined on the original PDE system, and it is rigorously proved that: first the PDE system's state tracks the prescribed reference trajectory with guaranteed closed-loop stability and tracking accuracy;and second locally accurate identification of the PDE system's dominant nonlinear uncertain dynamics can be achieved with provable convergence of associated NN weights to their optimal values, thereby the learned knowledge can be ultimately stored and represented by the convergent constant RBF NN models. Based on this, an experience-based control scheme is further proposed, which is capable of recalling the associated learned knowledge in real-time to further improve control performance and reduce computational complexity with maintained provable stabilization. It is worth stressing that although this work is focused particularly on parabolic PDE systems, it is groundbreaking with important technical breakthroughs that would facilitate a more complete extension of the DL theory from traditional ordinary differential equation syste

关键词： Galerkin methods

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：