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第41届中国控制会议

作者： Jiahao Zhang Chengda Lu Hengyu Huang Jun Gao Min Wu School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education CCTEG Xi'an Research Institute

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

Drill-string vibration has a great negative influence on the safety and efficiency of geological *** that the influence of drill-string inclination is not well considered in the literature,this paper develops a novel drill-string vibration model for geological drilling with inclined ***,the correlation between the inclination angle of borehole and the axial and torsional forces on the drill-string is *** on this,a drill-string motion model with the parameters of inclination angle is ***,the bit-rock interaction is considered as two processes,axial cutting and torsional friction,and an axial-torsional coupled bit-rock interaction model with state-dependent time delay is *** combining the established drill-string motion model and bit-rock interaction model,a coupled axial-torsional vibration model of drill-string in inclined borehole is obtained with the effect of borehole wall friction taken into *** drill-string vibration model proposed in this paper is more general,and includes the existing coupled drill-string vibration model of vertical borehole,which is closer to the actual situation.

关键词： drill-string vibration drill-string inclination bit-rock interaction

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EFEAR-4D: Ego-Velocity Filtering for Efficient and Accurate 4D radar Odometry

arXiv

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arXiv 2024年

作者： Wu, Xiaoyi Chen, Yushuai Li, Zhan Hong, Ziyang Hu, Liang The Department of Automation School of Mechanical Engineering and Automation Harbin Institute of Technology Shenzhen518055 China Research Institute of Intelligent Control and Systems Harbin Institute of Technology Harbin150001 China

Odometry is a crucial component for successfully implementing autonomous navigation, relying on sensors such as cameras, LiDARs and IMUs. However, these sensors may encounter challenges in extreme weather conditions, such as snowfall and fog. The emergence of FMCW radar technology offers the potential for robust perception in adverse conditions. As the latest generation of FWCW radars, the 4D mmWave radar provides point cloud with range, azimuth, elevation, and Doppler velocity information, despite inherent sparsity and noises in the point cloud. In this paper, we propose EFEAR-4D, an accurate, highly efficient, and learning-free method for large-scale 4D radar odometry estimation. EFEAR-4D exploits Doppler velocity information delicately for robust ego-velocity estimation, resulting in a highly accurate prior guess. EFEAR-4D maintains robustness against point-cloud sparsity and noises across diverse environments through dynamic object removal and effective region-wise feature extraction. Extensive experiments on two publicly available 4D radar datasets demonstrate state-of-the-art reliability and localization accuracy of EFEAR-4D under various conditions. Furthermore, we have collected a dataset following the same route but varying installation heights of the 4D radar, emphasizing the significant impact of radar height on point cloud quality - a crucial consideration for real-world deployments. Our algorithm and dataset will be available soon at https://***/CLASS-Lab/EFEAR-4D. © 2024, CC BY-NC-SA.

关键词： Millimeter waves

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Fuzzy cascade control of heating furnace outlet temperature based on improved particle swarm optimization 10

Fuzzy cascade control of heating furnace outlet temperature ...

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10th International Conference on Mechanical engineering, Materials, and automation Technology, MMEAT 2024

作者： Qi, Jiaxin Hu, Shaolin He, Hongli Zhang, Sai College of Electronic Information Engineering Xi’an Technological University Xi’an710000 China Automation School Guangdong University of Petrochemical Technology Guangdong Maoming525000 China Institute of China Academy of Flight Test and Research Xi'an Xi’an710000 China School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132000 China

ISBN: (纸本)9781510682634

To address the nonlinearities and multiple disturbances encountered in the outlet temperature control system of the heating furnace, a fuzzy cascade control system is devised. This system integrates the strengths of both cascade control and fuzzy control, aiming to effectively regulate the outlet temperature of the heating furnace. To enhance the system's control effectiveness, an Improved Particle Swarm Optimization algorithm is introduced for optimizing the fuzzy PID cascade control method. The method optimizes the parameters of the outer loop controller (i.e., fuzzy PID controller) in the fuzzy cascade control system, by introducing a nonlinear decreasing function to enhance the weights, utilizing Tent mapping to improve the random number r, and employing a logarithmic function to construct a nonlinear asynchronous learning factor. The simulation results indicate that when compared to three other control methods—conventional cascade PID, fuzzy cascade PID, and particle swarm-optimized fuzzy cascade PID—the proposed control method in this paper exhibits reduced overshoot by 16.9%, 10.5%, and 3.1%, respectively. Additionally, the regulation time is shortened by 36s, 16s, and 12s, respectively. thereby significantly enhancing the system's control performance. © 2024 SPIE.

关键词： Particle swarm optimization (PSO)

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An Obstacle Avoidance control Strategy for DELTA Parallel Manipulator via Improved Genetic Algorithm 37

An Obstacle Avoidance Control Strategy for DELTA Parallel Ma...

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Zheng, Hao Xu, Yihang Li, Yuantao Ran, Guangtao Liu, Jian Southeast University School of Automation Nanjing210018 China Harbin Institute of Technology Department of Control Science and Engineering Harbin150001 China

ISBN: (纸本)9781665465366

Aiming at the requirement of the DELTA parallel manipulator for performing grasping operations, a method for obstacle avoidance based on a genetic algorithm is proposed. Firstly, the classical DELTA parallel manipulator is analyzed mathematically, and its model is simplified. Then, the motion space and inverse kinematics solutions of the DELTA parallel manipulator are solved by using the spatial geometry method. Secondly, a cylindrical envelope surface is added to the manipulator's end for distance calculation. This envelope surface ensures that obstacles do not collide with the manipulator during obstacle avoidance. Thirdly, an improved genetic algorithm is proposed for obstacle avoidance. Finally, the simulation results are given to verify the effectiveness and reliability of the proposed algorithm. © 2022 IEEE.

关键词： Genetic algorithms

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Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

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IEEE/CAA Journal of Automatica Sinica 2023年第4期10卷 839-858页

作者： Zhaojian Wang Wei Wei John Zhen Fu Pang Feng Liu Bo Yang Xinping Guan Shengwei Mei Key Laboratory of System Control and Information Processing Ministry of Education of ChinaDepartment of AutomationShanghai Jiao Tong UniversityShanghai 200240China State Key Laboratory of Power System and the Department of Electrical Engineering Tsinghua UniversityBeijing 100084China Institute of High Performance Computing(IHPC) Agency for Science Technology and Research(A*STAR)Singapore 138632Singapore

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable *** increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization ***,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical *** paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques *** particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period ***,we recommend some potential future directions for online optimization in the power systems domain.

关键词： optimization Lyapunov optimization online convex optimization online optimization optimization-guided control

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An aircraft brake control algorithm with torque compensation based on RBF neural network

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Chinese Journal of Aeronautics 2024年第1期37卷 438-450页

作者： Ning BAI Xiaochao LIU Juefei LI Zhuangzhuang WANG Pengyuan QI Yaoxing SHANG Zongxia JIAO School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China Science and Technology on Aircraft Control Laboratory Beihang UniversityBeijing 100191China Key Laboratory of Advanced Aircraft Systems(Beihang University) Ministry of Industry and Information TechnologyBeijing 100091China Research Institute for Frontier Science Beihang UniversityBeijing 100191China Ningbo Institute of Technology of Beihang University Ningbo 315800China Tianmushan Laboratory Xixi Octagon CityYuhang DistrictHangzhou 310023China

The wheel brake system of an aircraft is the key to ensure its safe landing and rejected takeoff.A wheel’s slip state is determined by the brake torque and ground adhesion torque,both of which have a large degree of *** is this nature that brings upon the challenge of obtaining high deceleration rate for aircraft brake *** overcome the disturbances caused by the above uncertainties,a braking control law is designed,which consists of two parts:runway surface recognition and wheel’s slip state *** runway surface recognition,the identification rules balancing safety and braking efficiency are defined,and the actual identification process is realized through recursive least square method with forgetting *** slip state tracking,the LuGre model with parameter adaptation and a brake torque compensation method based on RBF neural network are proposed,and their convergence are *** effectiveness of our control law is verified through simulation and ground *** in the experiments on the ground inertial test bench,compared to the improved pressure-biased-modulation(PBM)anti-skid algorithm,fewer wheel slips occur,and the average deceleration rate is increased by 5.78%,which makes it a control strategy with potential for engineering applications.

关键词： Aircraft landing Brakes Disturbance observer Neural networks Runway identification

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Dynamic Object Tracking Based on Triplet Relationship Guided Sampling Consensus Algorithm 3

Dynamic Object Tracking Based on Triplet Relationship Guided...

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2023 3rd International Conference on Computer, Remote Sensing and Aerospace, CRSA 2023

作者： Zhou, Jiaxing Yao, Youxin Chen, Xiang Guo, Hanlin Huang, Qixuan School of Electrical Engineering and Automation Xiamen University of Technology Xiamen361024 China Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control Xiamen361000 China Shanghai Satellite Engineering Institute Shanghai201109 China

Compared with the traditional methods based on the prediction of moving object trajectory, the method based on image registration has the advantage of not relying on the object motion equation to track the object. However, in the case of a large number of outliers, the image matching method has the defects of inadequate filtering of outliers or erroneous filtering of incomers due to the limitations of spatial constraints of feature matching pairs, which will make the tracking of flying objects inaccurate or impossible. During the flight, the object may be in a similar background and the image shooting angle is different, which makes the object imaging angle change, resulting in a large number of outlier interference. Because of the above situation, this paper adopted an improved TRESAC algorithm based on RANSAC, which used a feature matching method based on a triplet relationship to effectively filter outliers and then adopted an initial data subset selection strategy to increase its robustness. Experimental results show that the TRESAC algorithm can filter outliers quickly and accurately, and the object is still tracked effectively under the condition of similar background and pose change. © Published under licence by IOP Publishing Ltd.

关键词： Statistics

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Sliding Mode control for Recurrent Neural Networks With Time-Varying Delays and Impulsive Effects

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IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1319-1321页

作者： Lanfeng Hua Kaibo Shi Zheng-Guang Wu Soohee Han Shouming Zhong the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China the School of Electronic Information and Electrical Engineering Chengdu UniversityChengdu 610106China the Institute of Cyber-Systems and Control Zhejiang UniversityHangzhou 310027China the Department of Electrical Engineering and Convergence IT Engineering Pohang University of Science and TechnologyPohang 37673South Korea the School of Mathematics Sciences University of Electronic Science and Technology of ChinaChengdu 611731China

Dear Editor,This letter studies the problem of sliding mode control(SMC)design for recurrent neural networks(RNNs)with impulsive disturbances and time-varying transmission *** this end,an appropriate integral sliding ... 详细信息

关键词： impulsive letter delays

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Multi-sphere and Multi-kernel Fuzzy Support Vector Data Description for One-class Classification 7

Multi-sphere and Multi-kernel Fuzzy Support Vector Data Desc...

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7th International Conference on Intelligent Computing and Signal Processing, ICSP 2022

作者： Jin, Yang Lin, Ruishi Cui, Langfu Wang, Mingxian Xiang, Gang Zhang, Qingzhen Zhang, Chaoqi Zhang, Ru Beihang University School of Automation Science and Electrical Engineering Beijing China Beijing Aerospace Automatic Control Institute National Key Lab on Aerospace Intelligent Control Beijing China

ISBN: (纸本)9781665478571

Support vector data description (SVDD) is a machine learning method for one-class classification (OCC), which is widely used in anomaly detection. However, when faced with the problem of data nonlinearity, the kernel method has difficulty in kernel parameter selection, and the lack of non-target samples completely in strict OCC tasks makes the generalization ability of the model uncertain. In addition, the nonlinearity of the data is often manifested as multi-distribution in many applications, and the data set is also at risk of being mixed with noise. Aiming at the problems above, a three-stage learning multi-sphere and multi-kernel fuzzy support vector data description (MS-MK-FSVDD) is proposed. The main idea of the method is to replace the original single spherical boundary with a set of ellipsoid boundaries that can adapt to the distribution of the data. The method first clusters the data according to the maximum posterior probability in a Gaussian mixture model (GMM). Then, for the data in each cluster, centered kernel alignment (CKA) is used to calculate the combination coefficients of the multi-kernel functions. Finally, the joint probability density function in GMM is used for weights assigning. The experiments show that MS-MK-FSVDD not only overcomes the difficulty of kernel parameter selection and enhances the anti-noise ability of the model but also improves the classification performance, especially when the data has a specific distribution. © 2022 IEEE.

关键词： Gaussian distribution

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Event-triggered Output Consensus control of the Disturbed Heterogeneous MASs with Sliding-mode Observer 37

Event-triggered Output Consensus Control of the Disturbed He...

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37th Youth Academic Annual Conference of Chinese Association of automation, YAC 2022

作者： Liu, Haikuo Du, Changkun Li, Nannan Sun, Zhongqi Beijing Institute of Technology School of Mechatronical Engineering Beijing China Beijing Institute of Control and Electronics Technology Beijing China Beijing Institute of Technology School of Automation Beijing China

ISBN: (纸本)9781665465366

The individual behavior and dynamics are core factors for the cooperation performance of multi-agent systems(MASs). In practical application, the perfect identical system is difficult to guarantee. Considering the individual differences in MASs, which is called as heterogeneous MASs, this paper studies the distributed output consensus problem with event-triggered scheme. Taking the external disturbance into consideration, a novel distributed sliding-mode output consensus control protocol is designed, which composed of a state-dependent event-triggered strategy and a sliding-mode observer. Under the developed strategy, the individual agents will achieve consensus with zero final consensus error. Moreover, the Zeno behavior is excluded and the fully intermittent communication among agents is realized, that is, the continuous information exchange among agents is neither required for the controller updating or triggering condition monitoring. © 2022 IEEE.

关键词： Multi agent systems

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