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Chinese control Conference (CCC)

作者： Yuhuan Ran Ke Yi Zixuan Liang School of Aerospace Engineering Beijing Institute of Technology Beijing China Key Laboratory of Autonomous Navigation and Control for Deep Space Exploration (Beijing Institute of Technology) Ministry of Industry and Information Technology Beijing China CSSC System Engineering Research Institute Beijing

A dual-level trajectory planning method is proposed for the trajectory planning of hypersonic vehicles with no-fly zone constraint. To improve the efficiency of the trajectory planning, the method is designed in two levels: the first level is the heading planning, and the second level is the trajectory planning. For the first level, a rapid heading planning method is proposed based on the graphical model of no-fly zones, and the evaluation of the avoidance heading is based on the simplified lateral dynamics equation. The second level introduces the avoidance heading constraint and the fitness with self-seeking, and thus the trajectory planning model can quickly generate a trajectory that satisfies the constraints. Finally, the proposed dual-level planning method is validated by simulations of hypersonic flight with multiple no-fly zones. The results show that the proposed method is capable to generate flight trajectories in high efficiency.

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Erratum to “Opinion dynamics of modified Hegselmann–Krause model in a group-based population with heterogeneous bounded confidence” [Physica A 419 (2015) 558–565]

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Physica A: Statistical Mechanics and its Applications 2015年 425卷 90-90页

作者： Guiyuan Fu Department of Automation Shanghai Jiaotong University and Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai 200240 China

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MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial Odometry

MUP-LIO: Mapping Uncertainty-aware Point-wise Lidar Inertial...

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

作者： Hekai Yao Xuetao Zhang Gang Sun Yisha Liu Xuebo Zhang Yan Zhuang Intelligent Robotic Laboratory School of Artificial Intelligence School of Control Science and Engineering Dalian University of Technology Dalian China School of Information Science and Technology Dalian Maritime University Dalian China College of Artificial Intelligence The Institute of Robotics and Automatic Information System (IRAIS) Tianjin Key Laboratory of Intelligent Robotics Nankai University Tianjin China

ISBN: (数字)9798350377705

ISBN: (纸本)9798350377712

This paper proposes a mapping uncertainty-aware point-wise Lidar Inertial Odometry (LIO), which synthesizes the point-wise point-to-plane match and map refreshment into a probabilistic model. As a result, it can address the issue of mismatching during point registration and remove in-frame motion distortion of Lidar sensors. Specifically, the uncertainty-aware map is designed to embody the uncertainty of map geometric features (points and planes), which comes from the Lidar point measurement and pose estimation. Then the map can be modeled in a probabilistic form. In addition, the proposed framework refreshes map at each Lidar point measurement to timely revise geometric features and provide non-delayed map. On the basis, the probabilistic point-to-plane match method is designed to seek a corresponding plane for each Lidar point in point registration, which can enhance the effectiveness of match and provide adaptive observation noises for more accurate state estimation. Comparative experiments on various public datasets are conducted to demonstrate the superior performance of the proposed framework in terms of higher accuracy and better robustness.

关键词： Laser radar Accuracy Uncertainty Probabilistic logic Distortion Robustness Sensors Odometry Distortion measurement State estimation

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Modeling and Parameter Identification of Constant-Speed Centrifugal Chiller Based on Experiments

Modeling and Parameter Identification of Constant-Speed Cent...

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International Conference on Power system Technology (POWERCON)

作者： Xinchan Han Wen Zhang Dingyi Cheng Tingting Zhang Meng Liu Yuxin Xie Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Shandong Electric Power Research Institute Jinan China JinXianDai Information Industry Co. Ltd. Jinan China

The expanding penetration of intermittent renewable energy resources is motivating the development of demand response (DR) services for balancing generation and load. Central air conditionings (CACs) are potential candidates due to their thermal energy storage capability. A suitable load model is the foundation for DR services. However, CACs contain multiple control subsystems whose parameters are difficult to obtain because of trade secrets. This paper focuses on the modeling and parameter identification of the constant-speed centrifugal chiller, which accounts for 60-70% of the power of CAC. A thermal-electrical model of a constant-speed centrifugal chiller is established to describe the dynamic operation process. In addition, the critical control parameters and the delay time of control systems are identified based on experimental data for a practical building chiller. The experimental results verified the effectiveness of the proposed model.

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Fully Decentralized DC Optimal Power Flow Model And Its Solution 6

Fully Decentralized DC Optimal Power Flow Model And Its Solu...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Hao, Guangtao Han, Xueshan Chen, XueJun Luo, Sibei Han, Shifeng Ye, Pingfeng School of Mechanical Electrical & Information Engineering Putian University Putian351100 China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan250061 China New Engineering and Industry College Putian University Putian351100 China Intelligent Manufacturing of Huzhou College Huzhou313000 China School of Management of Putian University Putian351100 China College of Energy Storage Technology Shandong University of Science and Technology Qingdao266590 China

ISBN: (纸本)9798350346671

In view of the fact that renewable energy power generations such as wind and solar energy have been integrated into the power system in a high proportion in a distributed manner, driven by factors such as privacy and security of various power supply stakeholders, the power supply of the power system presents a decentralized management and control situation, making the traditional centralized DC optimal power flow difficult to achieve. In this paper, a fully decentralized DC optimal power flow model, its solution method and application are proposed. Firstly, based on the economic dispatch model of the traditional consensus algorithm, the node phase decentralized calculation method is established and the active power flow decentralized calculation method of the transmission line is given to determine the system overload line. Secondly, the improved Lagrangian optimal model of the centralized DC optimal power flow is proposed and the optimization equations are derived. Thirdly, on this basis, combined with the improved traditional consensus algorithm, the fully distributed DC optimal power flow model and its solution method are realized. Finally, a real system is taken as an example to demonstrate the effectiveness of the proposed method. © 2023 IEEE.

关键词： Solar energy

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Utility-Oriented Underwater Image Quality Assessment Based on Transfer Learning

arXiv

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arXiv 2022年

作者： Chen, Weiling Lin, Rongfu Liao, Honggang Zhao, Tiesong Gu, Ke Le Callet, Patrick Fujian Key Lab for Intelligent Processing and Wireless Transmission of Media Information Fuzhou University Fuzhou350108 China Peng Cheng Laboratory Shenzhen518000 China The Faculty of Information Technology Beijing University of Technology Engineering Research Center of Intelligent Perception and Autonomous Control Ministry of Education Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Équipe Image Perception et Interaction Laboratoire des Sciences du Numérique de Nantes Université de Nantes France

The widespread image applications have greatly promoted the vision-based tasks, in which the Image Quality Assessment (IQA) technique has become an increasingly significant issue. For user enjoyment in multimedia systems, the IQA exploits image fidelity and aesthetics to characterize user experience;while for other tasks such as popular object recognition, there exists a low correlation between utilities and perceptions. In such cases, the fidelity-based and aesthetics-based IQA methods cannot be directly applied. To address this issue, this paper proposes a utility-oriented IQA in object recognition. In particular, we initialize our research in the scenario of underwater fish detection, which is a critical task that has not yet been perfectly addressed. Based on this task, we build an Underwater Image Utility Database (UIUD) and a learning-based Underwater Image Utility Measure (UIUM). Inspired by the top-down design of fidelity-based IQA, we exploit the deep models of object recognition and transfer their features to our UIUM. Experiments validate that the proposed transfer-learning-based UIUM achieves promising performance in the recognition task. We envision our research provides insights to bridge the researches of IQA and computer vision. Copyright © 2022, The Authors. All rights reserved.

关键词： Multimedia systems

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A multi-class pattern recognition method for motor imagery EEG data

A multi-class pattern recognition method for motor imagery E...

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IEEE International Conference on systems, Man and Cybernetics

作者： Yonghui Fang Minyou Chen Robert F Harrison State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University Chongqing China School of Electronic and Information Engineering Southwest University Chongqing China Department of Automatic Control & Systems Engineering University of Sheffield Sheffield UK

The Common Spatial Patterns (CSP) algorithm is useful for calculating spatial filters for detecting event-related desynchronization (ERD) for use in ERD-based brain-computer interfaces (BCIs). However, basic CSP is a supervised algorithm suited only to two-class discrimination; it is unable to solve multiclass discrimination problems. This paper proposes a new method named the binary common spatial patterns (BCSP) algorithm to extend the basic CSP method to multi-class recognition. Our method arranges the spatial filters and Fisher classifiers in the form of a binary tree whereby N - 1 spatial filters and N - 1 Fisher classifiers are calculated for N class recognition. This is fewer than must be calculated in other methods (e.g. one-versus-rest, OVR). This makes the overall classification procedure less redundant. Simulation results show that BCSP has better performance than the OVR scheme and outperforms the three best teams in the 2008 BCI-competition.

关键词： Spatial filters Arrays Feature extraction Electroencephalography Band pass filters Covariance matrix Filtering algorithms

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Optimal Sensor Placement for Health Monitoring of Large Space Structures in Harsh Environment: A GA-EfI Approach 1

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8th Asia International Symposium on Mechatronics, AISM 2021

作者： Xu, Pengying Wang, Yan Xu, Xiaoxian Teng, Yucheng Ge, Dongming Leng, Guojun Wu, Yang Wang, Xuezi Hu, Xinlan Wang, Congsi Key Laboratory of Electronic Equipment Structure Design Ministry of Education Xidian University Xi’an710071 China School of Information and Control Engineering Xi’an University of Architecture and Technology Xi’an710055 China Beijing Institute of Spacecraft System Engineering Beijing100094 China The 29th Research Institute of China Electronics Technology Group Corporation Chengdu610036 China The 54th Research Institute of China Electronics Technology Group Corporation Shijiazhuang050081 China

ISBN: (数字)9789811913099

ISBN: (纸本)9789811913082

Considering the problems of information redundancy, incomplete information perception and space structure limitation in the sensor layout of large and complex structures, a sensor layout algorithm for structural health monitoring based on electromechanical coupling idea, a GA-EfI, is proposed. The proposed method overcomes the limitations of a single method, combines the powerful parallel search ability of genetic algorithm and the characteristics of effective independent method to eliminate redundant information, so as to ensure a very comprehensive perception of structural information with the least number of sensors. Finally, taking a vehicle-borne active phased array antenna as an example, the advantages of the proposed algorithm in antenna array reconstruction accuracy and calculation efficiency are verified by comparing with the other four algorithms which have been widely used. The method proposed in this paper can provide a new idea to solve the problem for the optimal layout of sensors in the fields of aerospace and large-scale structural monitoring. © 2022, Science Press.

关键词： Genetic algorithms

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A Mixed Gaussian Membership Function Fuzzy CMAC for a Three-Link Robot

A Mixed Gaussian Membership Function Fuzzy CMAC for a Three-...

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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Tuan-Tu Huynh Chih-Min Lin Tien-Loc Le Zhixiong Zhong Department of Electrical Engineering Yuan Ze University Taoyuan Taiwan R.O.C. Department of Electrical Electronic and Mechanical Engineering Lac Hong University Bien Hoa Vietnam Key Laboratory of Information Processing and Intelligent Control Minjiang University Fuzhou China

ISBN: (数字)9781728169323

ISBN: (纸本)9781728169330

This research produces a mixed Gaussian membership function (GMF) fuzzy cerebellar model articulation controller (CMAC) for a three-link robot. A mixed GMF is created using the current and the previous GMFs on each layer of CMAC to detect errors efficiently, so a mixed GMF fuzzy CMAC (MGMFFC) is able to train parameters efficiently and constructs the MGMFFC structure automatically. A Lyapunov cost function and the gradient descent techniques are utilized to get the adaptive with guaranteed system's stable. Simulation studies for a three-link robot show that the MGMFFC attains favorable tracking performance.

关键词： Two dimensional displays Robots Hypercubes Robustness Fuzzy logic Nonlinear systems Electronic mail

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Bearing Fault Diagnosis Based on Optimized Deep Hybrid Kernel Extreme Learning Machine

Bearing Fault Diagnosis Based on Optimized Deep Hybrid Kerne...

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第35届中国控制与决策会议

作者： Zhenyu Qi Liling Ma Junzheng Wang Shanhao Feng School of Automation Beijing Institute of Technology School of Automation Beijing Institute of Technology Key Laboratory of Drive and Control of Servo Motion SystemMinistry of Industry and Information Technology China Aerospace Science and Industry Corporation China Nanjing Chenguang Machinery Manufacturer

Bearings are important components in mechanical *** diagnosis of bearings is of great *** accuracy and strong adaptability are necessary for a bearing fault diagnosis *** this paper,a fault diagnosis method based on an optimized deep hybrid kernel extreme learning machine is *** method adds the idea of deep learning to the traditional machine learning method,and has the characteristics of simple implementation and strong feature extraction *** addition,the sparrow search optimization algorithm is used to optimize the parameters of the diagnostic model,so that the model can achieve the best *** show that our proposed method can achieve satisfying performance on the same working condition,different working conditions and imbalanced datasets.

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