检索结果-内蒙古大学图书馆

An Improved Fault-Tolerant control and Stabilization for Positive Polynomial Fuzzy Systems

学校读者我要写书评

暂无评论

An Improved Fault-Tolerant Control and Stabilization for Pos...

IEEE International Conference on control Science and Systems engineering (CCSSE)

作者： Ziguang Wang Aiwen Meng Mingxuan Wang Zhiquan Li Key Laboratory of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei China College of Electronic and Information Engineering Hebei University Hebei China

ISBN: (数字)9798331517199

ISBN: (纸本)9798331517205

This paper presents an improved analysis method to design a fault-tolerant controller for positive polynomial fuzzy systems based on static output feedback as well as actuator faults. Firstly, inspired by the property of fault matrix, a new approach of controller design is presented, and some constraint conditions are introduced to guarantee the stability conditions and posi-tivity conditions to be convex simultaneously. Furthermore, by comparing with the existing methods, this method not only can eliminate the binding to the input matrix B, but also is able to provide a wider range of stability region. Besides, to enhance the relaxation of the stability analysis, we introduce the up-to-date Taylor series membership functions (TSMFs) approximation method such that the information embedded in the membership functions and the state boundary information can be taken into the stability conditions. As a result, on the strength of Lyapunov stability theory, the stability analysis is performed via sum-of-squares (SOS) approach. Finally, a simulation example is given to illustrate the effectiveness and reliability of the proposed method.

关键词： Fault tolerant systems Fault tolerant control Reliability theory Taylor series Systems engineering and theory Stability analysis Polynomials Output feedback Fuzzy systems Lyapunov methods

An Improved Artificial Potential Field Method for Formation control and Obstacle Avoidance of the Multi-Agents Systems

学校读者我要写书评

暂无评论

An Improved Artificial Potential Field Method for Formation ...

Chinese Automation Congress (CAC)

作者： Yubiao Yan Jianxiong Li Haibo Dong Chongyi Gao Yiming Fang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao China Department of Electromechanical Engineering Tangshan University Tangshan China

Obstacle avoidance is a significant research content in multi-agents formation control. The obstacle avoidance of multi-agents systems is investigated in this paper, and an improved artificial potential field method (IAPF) is proposed to avoid unknown obstacles in multi-agent formation. Aiming at improving the efficiency of formation avoidance and solving the non-reachable and local minima problems, the dynamic sub-target algorithm is proposed. The proposed method enables the multi-agent system (MASs) to avoid obstacles smoothly and quickly and complete formation tasks in complex environments by tracking dynamic sub-target as well, in which the position and motion direction of adjacent agents are taken into account in the selection of a sub-target for the formation efficiency. In addition, a variable potential field range is defined to ensure the safety of the formation. Finally, several simulation results verify the superiority and effectiveness of the proposed approach.

关键词：

Contextual Multi-Armed Bandit-Based Dynamic Cooperative Link Configuration for AUV in UWASNs With Energy Harvesting

学校读者我要写书评

暂无评论

IEEE Transactions on Cognitive Communications and Networking 2025年

作者： Dai, Jun Li, Xinbin Han, Song Yu, Junzhi Liu, Zhixin Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao066004 China Yanshan University Key Laboratory of Intelligent Rehabilitation and Neuromodulation of Hebei Province Qinhuangdao066004 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics BIC-ESAT College of Engineering Beijing100871 China

This paper investigates the cooperative link configuration problem for Autonomous Underwater Vehicle (AUV) in Underwater Acoustic (UWA) sensor networks with Energy Harvesting (EH), which aims to maximize long-term cumulative capacity by jointly optimizing cooperation relay, AUV transmission power, and relay transmission power. Subject to unknown time-varying Channel State Information (CSI), unpredictable stochastic EH, and variable communication topology caused by AUV mobility, the proposed problem is an unknown dynamic combination decision optimization problem. To resist the change of the dynamic UWA communication topology with unknown time-varying CSI and EH, a novel collaborative contextual multi-armed bandit learning framework is proposed, which allows relay nodes to learn cooperatively and enriches the learning information of relays. Consequently, the proposed learning framework can resist the change of the dynamic UWA communication topology efficiently, thereby achieving the superior link configuration quickly. Besides, a learning-rate adjustment rule for the dynamic UWA communication topology is proposed to adaptively balance the exploration-exploitation, thereby avoiding missing the real superior joint relay-power configuration. Finally, simulation results show the significantly superiority of the proposed scheme. © 2015 IEEE.

关键词： Cooperative communication

Decision Variable Classification-Based Evolutionary Algorithm for Dynamic Multi-Objective Optimization

学校读者我要写书评

暂无评论

SSRN 2023年

作者： Wei, Lixin Yang, Qingshuai Guo, Zeyin Institute of Electrical Engineering Yanshan University Hebei Qinhuangdao066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei Province Qinhuangdao066004 China

There are many dynamic multi-objective optimization problems (DMOPs) in real life, and such problems require the algorithms to converge quickly to a new Pareto Front and maintain the diversity of solution sets after the environment changes. To achieve these objectives, a dynamic multi-objective evolutionary algorithm (DEA) based on decision variable classification is proposed in this paper. First, the decision variables are classified into two categories using the decision variable clustering method: convergence-related variables and diversity-related variables. Then, the convergence optimization strategy and the diversity optimization strategy are used to optimize these two categories of decision variables, so that the algorithm can obtain excellent convergence and good diversity while fast tracking the Pareto front. In addition, a method for calculating the degree of environmental change, which uses the information after environmental change, is proposed to improve the algorithm’s ability to respond to environmental change. The proposed algorithm is compared with three state-of-the-art dynamic multi-objective optimization evolutionary algorithms on 16 benchmark problems. The experimental results show that the algorithm can effectively solve dynamic multi-objective optimization problems. © 2023, The Authors. All rights reserved.

关键词： Evolutionary algorithms

Hopf Bifurcation Hybrid control Strategy for Mill Main Driving System Under Unsteady Lubrication

学校读者我要写书评

暂无评论

SSRN 2022年

作者： Liu, Shuang Meng, Qingfu Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Hebei066004 China Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Mr Hebei066004 China

Aiming at the vibration behavior of the main driving system of rolling mill when the lubrication condition changes, the Hopf bifurcation phenomenon of the system under unsteady lubrication condition is analyzed, and an improved hybrid control strategy is proposed to suppress the vibration of rolling mill. Firstly, according to the variation law of lubrication conditions in rolling process, the dynamic rolling moment of the main drive system under unsteady lubrication was given, and the torsional vibration mechanical model of the main drive system was established, and the Hopf bifurcation behavior of the system under boundary lubrication was analyzed. It is found that when the subcritical Hopf bifurcation occurs in the system, the main transmission system of the linker will experience sudden and destructive instability oscillations. Therefore, this paper proposes an improved hybrid control strategy to control the Hopf bifurcation behavior of the system. The traditional hybrid control strategy uses a single control parameter to control both parameter disturbance and state feedback. Here, two control parameters are used to control parameter disturbance and state feedback respectively. In the state feedback part, nonlinear feedback is used to replace the traditional linear feedback. After the control is added, the critical value of Hopf bifurcation can be changed and the stability region of the system can be increased by adjusting the control parameters of the disturbance part of the parameters. Here, direct Normal form calculation method is introduced to calculate the Hopf bifurcation specification of the system. By adjusting the control parameters of the state feedback part by the canonical coefficient, the system can be changed from subcritical bifurcation to supercritical bifurcation, the phase trajectory of the system can be changed from unstable limit cycle to stable limit cycle, and the amplitude of limit cycle can be controlled. The effectiveness of the proposed

关键词： Lubrication

Optimal Time and Power Allocation in Full-Duplex Wireless-Powered Cognitive Radio Networks

学校读者我要写书评

暂无评论

Optimal Time and Power Allocation in Full-Duplex Wireless-Po...

IEEE International Conference on Cyber Technology in Automation, control, and Intelligent Systems

作者： Zhenyu Feng Ming Su Meihua Zhou Zhixin Liu School of Electrical Engineering Yanshan University Qinhuangdao China Training Center of Liren College Yanshan University Key Lab of Industrial Computer Control Engineering of Hebei Province Qinhuangdao Hebei Province China

In this paper, we integrate wireless powered communication networks (WPCNs) with cognitive radio networks (CRNs) in order to develop wireless powered CRNs (WP-CRNs). The hybrid access point (HAP) is used to broadcast radio-frequency signals to the devices at the downlink stage, and to receive information from these devices. The HAP has two antennas to achieve full-duplex: one is for downlink wireless power transfer and the other is for receiving uplink information transmission from the users simultaneously in the uplink. In the underlay paradigms. The SUs can harvest energy to transmit data when the interference to primary users (PUs) does not exceed a tolerable threshold. To tackle the above network issues, an optimal resource allocation method is proposed to maximize the secondary system uplink throughput. The optimization problem with respect to time and power allocation is formulated including the constraint of energy causality and interference level. The non-convex problem is transformed into an equivalent convex optimization problem, then the joint optimal power and time allocation (JOPTA) algorithm is presented to determine the optimal solutions. The effectiveness of the proposed algorithm is verified in the simulations.

关键词：

MPC-Based Trajectory Tracking control Strategy Incorporating Autonomous Lane-Changing Mechanism for Intelligent Vehicles

学校读者我要写书评

暂无评论

MPC-Based Trajectory Tracking Control Strategy Incorporating...

Conference on Vehicle control and Intelligence (CVCI)

作者： Dongxue Zhang Huiwen Liu Xiaohong Jiao Ting Zhang Hebei Key Laboratory of Industrial Computer Control Engineering Yanshan University Qinhuangdao Hebei Province China School of Vehicle and Mobility Tsinghua University Beijing China

ISBN: (数字)9798331504892

ISBN: (纸本)9798331504908

Navigating the intricate traffic environment, lane-changing has emerged as a frequent and essential driving maneu-ver for intelligent vehicles. However, it is challenging to guarantee the safety of the intelligent vehicle and the trajectory tracking accuracy against the external environment during lane-changing. Considering these challenges to overcome, the model predictive control (MPC)-based trajectory tracking strategy incorporating an autonomous lane-changing mechanism is proposed in this paper. The autonomous lane-changing mechanism considering lane-changing intention is proposed to ensure that the intelligent vehicle generates safe lane-changing decisions and trajectories. Subsequently, the MPC strategy that considers the physical char-acteristics of the intelligent vehicle is proposed to guarantee the accuracy and smoothness of trajectory tracking. The validation of its effectiveness and advantages is established on the PreScan and MATlab/Simulink co-simulation platforms.

关键词： Accuracy Intelligent vehicles Trajectory tracking Navigation Vehicle safety Trajectory MATlab Predictive control

Branch-Yolo：Efficient Object Detector for Thin Structure Objects Like Pantograph

学校读者我要写书评

暂无评论

SSRN 2024年

作者： Li, Yaqian Han, Jiaqi Li, Haibin Zhang, Wenming College of Electrical Engineering Yanshan University Hebei Qinhuangdao066000 China Key Laboratory of Industrial Computer Control Engineering of Hebei Province Hebei Qinhuangdao066000 China

The pantograph is the key structure in the railway Pantograph-OCS system, acting as the switch for the railway traction power supply system. So it’s crucial to detect the pantograph's lifting and lowing states for production efficiently and safely. However, due to the pantograph’s special slender structure and complex application scenarios, it occupies few pixels and is susceptible to background interference, making accurate real-time detection a challenging task. In this work, we aim to propose a generalized model, designed for detecting, branch-like objects with thin structure and multi-scale size such as pantographs. To this end, we propose the Branch-YOLO based on YOLOv8, which is improved in two stages, feature extraction and feature fusion, to simultaneously enhance perception. First, we introduce BrLayer is consist of BranchConv and EFAC(Extend receptive field attention Convolution), BranchConv can adaptively capture features of thin and tortuous local structures,EFAC is able to assist in expanding the effective receptive field. Subsequently, we propose a feature fusion network (BranchNet) to integrate multilevel semantic information and multi-scale features, which significantly reduces background interference in detecting slender structure objects and enhances the ability to perceive changes in object scale. Besides, we propose the Lightweight Cross-Kernel Convolution layer (LckLayer) and introduce the Feature Decomposition module (FdM) in BranchNet for lightweight design, reducing the computational overhead and enhancing model efficiency. Our proposed Branch-YOLO not only achieves the best performance on the multi-scale pantograph datasets but also attains an outstanding 42.9% AP on the COCO val2017 datasets, with 5.9M parameters and 16.8 GFLOPs. © 2024, The Authors. All rights reserved.

关键词： Religious buildings

Distributed Fault-Tolerant Secondary control For Dc Microgrids Against False Data Injection Attacks

学校读者我要写书评

暂无评论

SSRN 2022年

作者： Xie, Zongkui Wu, Zhongqiang Key Lab of Industrial Computer Control Engineering of Hebei Province Yanshan University Qinhuangdao066004 China

This paper focuses on the issue of unknown false data injection attacks (FDIA) of controllers in DC microgrid, and proposes a distributed fault-tolerant secondary controller for DC microgrid to ensure that the control objectives of voltage regulation and current sharing can be achieved when the system is subject to FDIA. Firstly, the secondary control problem in DC microgrid with FDIA is transformed into a first-order leader-following multi-agent system fault-tolerant consensus problem, and the impact of FDIA signals on the microgrid system is analyzed. Then, a distributed extended state observer (DESO) is designed based on the derived multi-agent system, which observes the injected FDIA signals using the relative output error of each distributed generators and its neighbours. Further, based on the observed FDIA signals, a fault-tolerant secondary controller is designed to eliminate the adverse effects of the attack signals on the system. Particularly, the stability analyses for the designed DESO and secondary controller prove that the control system is global asymptotically stable. Finally, the effectiveness and superiority of the proposed fault-tolerant secondary control method for DC microgrids with FDIA are verified by simulation analyses of four cases. © 2022, The Authors. All rights reserved.

关键词： Network security