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2024 Conference on Spectral Technology and Applications, CSTA 2024

作者： Zhao, Yonghong Liu, Jisong Wang, Junlong Dong, Shuxin Shannxi Key Laboratory of Complex System Control and Intelligent Information Processing Department of Automation and Information Engineering Xi'an University of Technology Shaanxi Xi'an710048 China

ISBN: (纸本)9781510683082

Wideband direction of arrival (DOA) estimation using sensor array is a noteworthy problem frequently occurring in many applications involving radar, sonar, and communication. We present a wideband DOA method based on a sparse Bayesian learning of multiple sub-bands jointly with the redundant dictionary matrix at the reference frequency. Explicitly enforcing the focusing operation and the singular value decomposition (SVD) to sensor measurements is motivated by a desire to decrease the computational complexity and storage capacity. A joint sparse Bayesian learning framework is proposed to deal with multiple sub-bands under one segment to obtain the DOA information. Moreover, the proposed method can be directly extended to multiple segments. Comparing to other wideband DOA estimation methods, the proposed method has the advantages of increased resolution, higher accuracy, and correlation of the sources, as well as not requiring the initial angles for the focusing matrix. Simulations are provided to show the effectiveness and improved performance of the proposed method. © 2024 SPIE.

关键词： Direction of arrival

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Cognitive Navigation for intelligent Mobile Robots:A Learning-Based Approach With Topological Memory Configuration

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IEEE/CAA Journal of Automatica Sinica 2024年第9期11卷 1933-1943页

作者： Qiming Liu Xinru Cui Zhe Liu Hesheng Wang Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China MoE Key Laboratory of Artificial Intelligence AI InstituteShanghai Jiao Tong UniversityShanghai 200240China Department of Automation Key Laboratory of System Control and Information Processing of Ministry of EducationKey Laboratory of Marine Intelligent Equipment and System of Ministry of EducationShanghai Engineering Research Center of Intelligent Control and ManagementShanghai Jiao Tong UniversityShanghai 200240China

Autonomous navigation for intelligent mobile robots has gained significant attention,with a focus on enabling robots to generate reliable policies based on maintenance of spatial *** this paper,we propose a learning-based visual navigation pipeline that uses topological maps as memory *** introduce a unique online topology construction approach that fuses odometry pose estimation and perceptual similarity *** tackles the issues of topological node redundancy and incorrect edge connections,which stem from the distribution gap between the spatial and perceptual ***,we propose a differentiable graph extraction structure,the topology multi-factor transformer(TMFT).This structure utilizes graph neural networks to integrate global memory and incorporates a multi-factor attention mechanism to underscore elements closely related to relevant target cues for policy *** from photorealistic simulations on image-goal navigation tasks highlight the superior navigation performance of our proposed pipeline compared to existing memory *** validation through behavior visualization,interpretability tests,and real-world deployment further underscore the adapt-ability and efficacy of our method.

关键词： Graph neural networks(GNNs) spatial memory topological map visual navigation

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Motion Blurred Star Image Centroid Optimized Extraction Based on Prior Gaussian Distribution 29

Motion Blurred Star Image Centroid Optimized Extraction Base...

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第29届中国控制与决策会议

作者： Peng Dingbang Chen Hao Sang Xiaochong Li Jianxun School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Institute of Spaceflight Control Technology Shanghai Key Laboratory of Aerospace Intelligent Control Technology

ISBN: (纸本)9781509046584

Star centroid extraction is the precondition of star recognition in star navigation *** image will be motion blurred under high dynamic *** methods such as Wiener filter method,restore the blurred star image with an estimated PSF to calculate the star *** unique characteristic of star images different from general images is ignored in conventional *** addition,the error of motion blur parameters estimation and the approximate linear motion model can decrease the accuracy of star centroids *** paper proposes a method utilizing the prior Gaussian distribution information of star energy to deal with the motion blurred star *** experimental results demonstrate that the proposed method gets smaller error in star centroids calculation compared with the conventional estimation method.

关键词： Motion blur Star image restoration Centroid extraction Gaussian distribution Optimize

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ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

ORB-Based Fast Anti-Viewing Image Feature Matching Algorithm

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2018 Chinese Automation Congress, CAC 2018

作者： Oi, Liangliang Liu, Wei Liu, Ding Crystal Growth Equipment and System Integration Engineering Research Center Laboratory for Complex System Control and Intelligent of Information Processing Xi'An University of Technology Xi'an710048 China

ISBN: (纸本)9781728113128

Aiming at the problem that the original ORB algorithm is difficult to solve the effective matching problem under large angle of view transformation. This paper proposes an image feature matching algorithm based on ORB to resist the change of view according to the principle of ASIFT. The basic idea of the algorithm is as follows, Firstly, the longitude angle and latitude angle caused by the rotation of the camera are simulated, and the simulated image sequence set which is deformed by the change of the optical axis direction of the camera is accurately simulated. Then the feature points are extracted and mapped them into the original image by combining the FAST feature point detection method with the BRISK feature descriptors. Finally, the Brute-Force Matcher and the Random Sampling Consistency (RANSAC) method were used for feature matching and optimization. The experimental results show that the proposed algorithm can solve the problem that the image features cannot be matched under the large change of viewing angle (greater than 60°), and it has a significant improvement in real-time performance compared with ASIFT. © 2018 IEEE.

关键词： Cameras

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Brain Storming Optimization Algorithm for Heating Dispatch Scheduling of Thermal Power Plant 29

Brain Storming Optimization Algorithm for Heating Dispatch S...

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第29届中国控制与决策会议

作者： Lu Kang Yali Wu Xinrui Wang Xiaohua Feng School of Automation and Information Engineering Xi'an University of Technology Shannxi Province Key Laboratory of Complex System Control and Intelligent Information Processing School of Marine Science and Technology Northwestern Polytechnical University

ISBN: (纸本)9781509046584

In the traditional scheduling mode of the current thermal power plants,only the power load distribution of the unit was *** there was no enough guidance to the heat source *** can not meet the current energy-saving and emission-reduction *** this paper,an optimal heat load dispatching model is set up under the premise of power load distribution of thermal power *** kinds of heat loads including to high-pressure,medium-pressure and low-pressure are taken into account in the scheduling *** to the characteristics of the problem,Brain Storming Optimization(BSO) algorithm is used to get the optimal distribution *** comparison with the original scheme shows the correctness of the model and the optimization ***,the optimization ability and effectiveness of brain storming optimization algorithm in solving complex optimization problems are verified by comparing the proposed algorithm with the other different optimization algorithms,such as Particle Swarm Optimization(PSO) and Differential Evolution(DE) algorithm.

关键词： Heating Dispatching Brain Storming Optimization Algorithm Load Distribution

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Scheduling optimization of silicon single crystal production process based on adaptive improved particle swarm optimization

Scheduling optimization of silicon single crystal production...

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2021 China Automation Congress, CAC 2021

作者： Kang, Lu Liu, Ding Wu, Yali Ping, Guozheng School of Automation and Information Engineering Xi'an University of Technology National and Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China School of Automation and Information Engineering Xi'an University of Technology National and Local Joint Engineering Research Center of Crystal Growth Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China School of Automation and Information Engineering Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing Xi'an710048 China

ISBN: (纸本)9781665426473

Aiming at the potential safety hazards of silicon single crystal production enterprises in the process of multi-furnace silicon single crystal production, and considering the maximum power load requirements in actual enterprises, a silicon single crystal production process scheduling model with the goal of minimizing the maximum completion time was established. Based on this model, an adaptive improved particle swarm optimization algorithm (Adaptive GPSO) is proposed to solve it. The algorithm retains the individual optimal value and global optimal value of the particle swarm algorithm, and introduces the crossover operation and mutation operation in the genetic algorithm to improve the new individual generation mechanism. At the same time, it performs dynamic iterative calculations on the mutation probability and crossover probability to avoid the algorithm fall into the local optimum, and improve the diversity and convergence of the algorithm. By solving different scales scheduling problems of silicon single crystal production process, the experiments on real-world data shows that the feasibility and effectiveness of the proposed algorithm. © 2021 IEEE

关键词： Genetic algorithms

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Layout Optimization of Large-scale Urban Water Supply Network Pressure Measuring Point Distribution Using Genetic Algorithm 36

Layout Optimization of Large-scale Urban Water Supply Networ...

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第36届中国控制会议

作者： Huayi Luo Jingcheng Wang Xiaocheng Li Jiayu Zhu Department of Automation Shanghai JiaoTong Universityand Key Laboratory of System Control and Information ProcessingMinistry of Education of China Autonomous Systems and Intelligent Control International Joint Research Center Xi'an Technological University

ISBN: (纸本)9781538629185

In the urban water supply system, the location and quantity of the pressure monitoring nodes play a significant role for the monitoring effect and the response warning of the pipe burst. However, most installation of pressure monitoring nodes are based on human experience, which cannot totally present the whole water supply system condition. In view of the unreasonable layout of pressure monitoring nodes, this paper presents a solution Integrating sensitivity analysis, genetic algorithm, hydraulic model calculation and pipe network topology. Then optimize the number of pressure monitoring nodes by considering the amount of water covered and the number of associated nodes. This solution offers a relatively accurate and reasonable way to optimize the layout of pressure monitoring nodes in large-scale site selection, presenting better comprehensive effect compared with previous layout. To a certain extent, this optimized layout of pressure monitoring nodes reduce the impact of human factors and improve the monitoring of water supply network operation results.

关键词： pressure measuring point layout optimization genetic algorithm urban water supply network

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AIoT for Aircraft Final Assembly:An intelligent and Collaborative Framework

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Journal of Communications and information Networks 2024年第3期9卷 262-276页

作者： Cheng Ren Xiaojing Wen Xinping Guan Cailian Chen Yehan Ma Department of Automation Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing Ministry of Education of ChinaShanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong UniversityShanghai 200240China

Aircraft final assembly line(AFAL)involves thousands of processes that must be completed before ***,the heavy reliance on manual labor in most assembly processes affects the quality and prolongs the delivery *** the advent of artificial intelligence of things(AIoT)technologies has introduced advancements in certain AFAL scenarios,systematically enhancing the intelligence level of the AFAL and promoting the widespread deployment of artificial intelligence(AI)technologies remain significant *** address these challenges,we propose the intelligent and collaborative aircraft assembly(ICAA)framework,which integrates AI technologies within a cloud-edge-terminal *** ICAA framework is designed to support AI-enabled applications in the AFAL,with the goal of improving assembly efficiency at both individual and multiple process *** analyze specific demands across various assembly scenarios and introduce corresponding AI technologies to meet these *** three-tier ICAA framework consists of the assembly field,edge data platform,and assembly cloud platform,facilitating the collection of heterogeneous terminal data and the deployment of AI *** framework enhances assembly efficiency by reducing reliance on manual labor for individual processes and fostering collaboration across multiple *** provide detailed descriptions of how AI functions at each level of the ***,we apply the ICAA framework to a real AFAL,focusing explicitly on the flight control system testing *** practical implementation demonstrates the effectiveness of the framework in improving assembly efficiency and promoting the adoption of AIoT technologies.

关键词： intelligent aircraft final assembly line AIoT cloud-edge-terminal framework design

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Lidar-Visual-Inertial Odometry with Online Extrinsic Calibration

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Journal of Shanghai Jiaotong university(Science) 2023年第1期28卷 70-76页

作者：茅天阳赵文韬王景川陈卫东 Department of Automation Institute of Medical RoboticsShanghai Jiao Tong UniversityShanghai 200240China Key Laboratory of System Control and Information Processing of Ministry of Education Shanghai 200240China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai 200240China

To achieve precise localization,autonomous vehicles usually rely on a multi-sensor perception system surrounding the mobile *** is a time-consuming process,and mechanical distortion will cause extrinsic calibration ***,we propose a lidar-visual-inertial odometry,which is combined with an adapted sliding window mechanism and allows for online nonlinear optimization and extrinsic *** the adapted sliding window mechanism,spatial-temporal alignment is performed to manage measurements arriving at different *** nonlinear optimization with online calibration,visual features,cloud features,and inertial measurement unit(IMU)measurements are used to estimate the ego-motion and perform extrinsic *** experiments were carried out on both public datasets and real-world *** indicate that the proposed system outperforms state-of-the-art open-source methods when facing challenging sensor-degenerating conditions.

关键词： autonomous vehicles multi-sensor fusion online calibration

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Building Temperature and Humidity Adaptive control for a Multi-Zone HVAC system Using Hybrid Modeling Method

Building Temperature and Humidity Adaptive Control for a Mul...

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2022 IEEE International Conference on Industrial Technology, ICIT 2022

作者： Jiang, Yuliang Zhu, Shanying Xu, Qimin Yang, Bo Guan, Xinping Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China 200240 Shanghai Engineering Research Center of Intelligent Control and Management Shanghai China 200240

ISBN: (纸本)9781728119489

In this paper, the heating, ventilation and air conditioning (HVAC) system as the contributor of building climate management is studied on multi-zone climate dynamics modelling and control for occupancy comfort. The first-principles model together with data-driven model as the hybrid model is proposed for comprehensive multi-zone hygro-thermal dynamics. The unmodeled climate dynamics such as unknown nonlinearity and uncertainty is modeled in a linear form based on the compact form dynamic linearization (CFDL) method. Then model free adaptive control (MFAC) scheme including controller design and parameter estimation is proposed to realize multi-zone climate control and occupancy comfort. The dynamic response performance of the hybrid model-based adaptive control and the first-principles model-based adaptive control has been tested in a multi-zone building with four different zones. The results show that the proposed hybrid model-based adaptive control scheme can achieve obvious performance improvement in minimizing steady-state error. © 2022 IEEE.

关键词： controllers

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