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Cooperative Hierarchical Coverage control of Multi-Agent systems with Non-holonomic Constraints in Poriferous Environments

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IEEE Transactions on control of Network systems 2025年

作者： Zou, Jiayu Zhang, Hai-Tao Zhai, Chao Xing, Ning Ma, Yong Liu, Xingjian Huazhong University of Science and Technology School of Artificial Intelligence and Automation The MOE Engineering Research Center of Autonomous Intelligent Unmanned Systems The State Key Laboratory of Digital Manufacturing Equipment and Technology Wuhan430074 China China University of Geosciences School of Automation China The MOE Engineering Research Center of Intelligent Technology for Geo-Exploration Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China Academician Workstation of China COSCO Shipping Corporation Ltd. Shanghai200120 China Wuhan University of Technology Sanya Science and Education Innovation Park Sanya572000 China Wuhan University of Technology Chongqing Research Institute Chongqing401120 China

It has long posed a challenging task to optimally deploy multi-agent systems (MASs) to cooperatively coverage poriferous environments in real cooperative detection applications. In response to this challenge, this paper proposes a hierarchical coverage control (HCC) protocol for MASs to perform sector-based coverage operations. First, a distributed Voronoi partition-based sweep-and-assign protocol, combined with a sectorial partition method, is developed, enabling the segmentation of a whole poriferous region into multiple sectorial sub-subregions. Following this procedure, an extreme search scheme is developed to determine the optimal amount of agents for each subregion. After this allocation, a distributed controller is proposed to deploy the agents, considering non-holonomic constraints, into designated niche positions. Additionally, sufficient conditions are derived to guarantee the asymptotical stability of the present HCC. The analytical challenge of the present study stems from the non-convex characteristics inherent in the loss function induced by porous environments. This non-convexity renders the task of globally optimizing the assignment of MASs intractable. Finally, numerical simulations are conducted to validate the effectiveness of the present coverage control approach. © 2014 IEEE.

关键词： Nonlinear control systems

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Application of fuzzy cognitive map in information intelligent push

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Journal of Beijing Institute of Technology 2015年第4期24卷 553-557页

作者：张佳徐胜利邓方 School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems

Since computer system functions are becoming increasingly complex, the user has to spend much more time on the process of seeking information, instead of utilizing the required infor- mation. Information intelligent push technology could replace the traditional method to speed up the information retrieval process. The fuzzy cognitive map has strong knowledge representation ability and reasoning capability. Information intelligent push with the basis on fuzzy cognitive map could ab- stract the computer user＇ s operations to a fuzzy cognitive map, and infer the user＇ s operating inten- tions. The reasoning results will be translated into operational events, and drive the computer system to push appropriate information to the user.

关键词： fuzzy cognitive map artificial intelligence information intelligent push

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Cycle-slip Detection of GPS Carrier Phase with Methodology of SA4 Multi-wavelet Transform

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Chinese Journal of Aeronautics 2012年第2期25卷 227-235页

作者： HUO Guoping MIAO Lingjuan School of Automation Beijing Institute of Technology Beijing 100081 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

That cycle-slips remain undetected will significantly degrade the accuracy of the navigation solution when using carrier phase measurements in global positioning system （GPS）. In this paper, an algorithm based on length-4 symmetric/anti-symmetric （SA4） orthogonal multi-wavelet is presented to detect and identify cycle-slips in the context of the feature of the GPS zero-differential carrier phase measurements. Associated with the local singularity detection principle, cycle-slips can be detected and located precisely through the modulus maxima of the coefficients achieved by the multi-wavelet transform. Firstly, studies are focused on the feasibility of the algorithm employing the orthogonal multi-wavelet system such as Geronimo-Hardin-Massopust （GHM）, Chui-Lian （CL） and SA4. Moreover, the mathematical characterization of singularities with Lipschitz exponents is explained, the modulus maxima from wavelet to multi-wavelet domain is extended and a localization formula is provided from the modulus maxima of the coefficients to the original observation. Finally, field experiments with real receiver are presented to demonstrate the effectiveness of the proposed algorithm. Because SA4 possesses the specific nature of good multi-filter properties （GMPs）, it is superior to scalar wavelet and other orthogonal multi-wavelet candidates distinctly, and for the half-cycle slip, it also remains better detection, location ability and the equal complexity of wavelet transform.

关键词： satellite navigation cycle-slip detection orthogonal multi-wavelet good multi-filter properties singularity detection

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Sequential fusion estimation for multisensor systems with non-Gaussian noises

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Science China(Information Sciences) 2020年第12期63卷 153-165页

作者： Liping YAN Chenying DI Q.M.Jonathan WU Yuanqing XIA Key Laboratory of Intelligent Control and Decision of Complex Systems School of AutomationBeijing Institute of Technology Department of Electrical and Computer Engineering University of Windsor

The sequential fusion estimation for multisensor systems disturbed by non-Gaussian but heavytailed noises is studied in this paper. Based on multivariate t-distribution and the approximate t-filter,the sequential fusion algorithm is presented. The performance of the proposed algorithm is analyzed and compared with the t-filter-based centralized batch fusion and the Gaussian Kalman filter-based optimal centralized fusion. Theoretical analysis and exhaustive experimental analysis show that the proposed algorithm is effective. As the generalization of the classical Gaussian Kalman filter-based optimal sequential fusion algorithm, the presented algorithm is shown to be superior to the Gaussian Kalman filter-based optimal centralized batch fusion and the optimal sequential fusion in estimation of dynamic systems with non-Gaussian noises.

关键词： state estimation sequential fusion non-Gaussian disturbance heavy-tailed noise multivariate t-distribution

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Distributed Constrained Online Nonconvex Optimization with Compressed Communication

arXiv

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arXiv 2025年

作者： Zhang, Kunpeng Xu, Lei Yi, Xinlei Cao, Ming Johansson, Karl H. Chai, Tianyou Yang, Tao State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China Department of Mechanical Engineering University of Victoria VictoriaBCV8W 2Y2 Canada Shanghai Institute of Intelligent Science and Technology National Key Laboratory of Autonomous Intelligent Unmanned Systems Frontiers Science Center for Intelligent Autonomous Systems Ministry of Education Shanghai201210 China Engineering and Technology Institute Groningen Faculty of Science and Engineering University of Groningen GroningenAG 9747 Netherlands Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Sweden Digital Futures Stockholm10044 Sweden

This paper considers distributed online nonconvex optimization with time-varying inequality constraints over a network of agents. For a time-varying graph, we propose a distributed online primal–dual algorithm with compressed communication to efficiently utilize communication resources. We show that the proposed algorithm establishes an O(T max{1−θ1,θ1}) network regret bound and an O(T 1−θ1/2) network cumulative constraint violation bound, where T is the number of iterations and θ1 ∈ (0, 1) is a user-defined trade-off parameter. When Slater’s condition holds (i.e, there is a point that strictly satisfies the inequality constraints at all iterations), the network cumulative constraint violation bound is reduced to O(T 1−θ1). These bounds are comparable to the state-of-the-art results established by existing distributed online algorithms with perfect communication for distributed online convex optimization with (time-varying) inequality constraints. Finally, a simulation example is presented to validate the theoretical results. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

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Learning to Win in Evolutionary Two-person Boolean Game with Fixed Strategy Updating Rule

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IFAC-PapersOnLine 2015年第28期48卷 520-525页

作者： WANG, Dong Hongbin, M.A. Beijing Institute of Technology Beijing China State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institution of Technology Canada

This paper introduces an algorithm to learn the strategy updating rule for a two- person Boolean game using the records of the history strategies and game results. The two-person game in this paper is introduced as a zero-sum game along with a Boolean strategy set, and the strategies are governed by fixed Boolean functions whose arguments are the history strategies and game results with additive binary noise, which can be modeled as a stochastic Boolean dynamic system. However, for this easy-to-play game, there is no effective convenient methods to win more often. To achieve this goal, a learning algorithm based on Boolean regression and maximum-likelihood estimation is put forward to learn the strategy updating rule and the noise property using the records of the history strategies and game results. In addition, extensive simulations via actual examples have illustrated the effectiveness of the proposed learning algorithm. © 2015

关键词： Learning algorithms Identification (control systems) Maximum likelihood estimation Parameter estimation Stochastic systems Boolean dynamics Boolean games Extensive simulations Fixed strategy Learning Noise properties Strategy updating Two person game

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Short-term wind power forecast with turning weather based on DBSCAN-RFE-LightGBM

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Renewable Energy 2025年 251卷

作者： Wu, Zhenlong Fan, Xinyu Bian, Guibin Liu, Yanhong Zhang, Xiaoke Chen, YangQuan School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Zhengzhou University Luoyang471000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Electric Power Research Institute of State Grid Henan Electric Power Company Zhengzhou450052 China Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

At present, the wind power prediction technology is becoming more and more mature, however, the turning weather brings a decrease in prediction accuracy due to its suddenness and instability. In this paper, a wind power prediction method considering the turning period and non-turning period respectively is proposed to weaken the adverse effects caused by turning weather. Firstly, the prediction effects of multiple models are compared, density-based spatial clustering of applications with noise (DBSCAN) is selected as the outlier processing method, recursive feature elimination (RFE) is used as the feature selection method, and Light gradient boosting machine (LightGBM) is used for prediction. The combined prediction method based on DBSCAN-RFE-LightGBM can reduce the influence of abnormal data and redundant features and improve the prediction effect. Then, the sliding window is set to detect the turning period. Considering that the turning weather is an emergency and does not happen frequently, the amount of data is small, which leads to the inability to train the model well. Generative adversarial networks (GAN) are applied to expand the turning period data. The LightGBM is trained and predicted by using the expended turning period data. Finally, the time-division prediction results are merged. Using the data collected from wind farms for short-term power prediction experiments, the time-segment prediction method proposed in this paper with GAN reduces MAE by 1.913 and RMSE by 3.351 on a single unit compared with the non-differentiated period. © 2025 Elsevier Ltd

关键词： Merging

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Identification for Switched systems

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IFAC-PapersOnLine 2015年第28期48卷 514-519页

作者： Hu, Qiong Fei, Qing Ma, Hongbin Wu, Qinghe Geng, Qingbo State Key Lab of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology Beijing100081 China

For a class of unstable discrete-time multi-variable switched systems with parametric uncertainty, an identification scheme is developed in this paper. Specifically, the identification algorithm is derived to identify the parameter vectors of potential subsystems based on the idea of least geometric mean squares. Furthermore, an neural network classifier is put forward for partition of the identified subsystems. Finally, feasibility and effectiveness of the proposed identification scheme are verified by numerical simulations, which show that the desirable identification performance is guaranteed with the proposed scheme. © 2015

关键词： Parameter estimation Computational fluid dynamics Geometric mean Identification algorithms Identification scheme Multi variables Neural network classifier Parameter vectors Parametric uncertainties Switched system

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Optimal FPGA Implementation of High Speed Scale Space Generator 34

Optimal FPGA Implementation of High Speed Scale Space Genera...

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第三十四届中国控制会议

作者： LI Nan WANG Junzheng Key laboratory of intelligent control and decision of complex systems Beijing Institute of Technology

ISBN: (纸本)9781467374439

Scale space generation is a fundamental problem in almost all feature extraction algorithms. Often, it is a critical prior step of most image/video analytic applications that are based on the invariance or co-invariance of local features, such as SIFT based recognition, matching, and tracking applications. However, it is still quite a challenging problem to enable real-time applications of the extraction of local features due to the fact that scale space generation has a rather large computational complexity. This paper proposes the optimal FPGA design for acceleration of scale space generation. First, in order to derive the mathematical model for scale space generation that fits best in with the FPGA, we have discarded the conventional template convolution based Gaussian filtering scheme and adopted a novel IIR filter based recursive Gaussian blurring algorithm. Then, an approach based on the Retiming technique, which could find the minimal operational period for any given IIR filter, is used to finalize the overall design. For 1024×768 video, the proposed design is able to generate scale spaces at almost 400 fps, which is fast enough to support most real-time applications like object recognition, object matching, and 3D reconstruction.

关键词： Feature Extraction,Scale Space Generation,Recursive Gaussian Blurring,Retiming,FPGA Implementation

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Fast Adaptive Robust control of Electro-hydraulic Servo System

Fast Adaptive Robust Control of Electro-hydraulic Servo Syst...

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第三十二届中国控制会议

作者： HE Yudong WANG Junzheng HAO Renjian Key laboratory of intelligent control and decision of complex systems Beijing Institute of Technology

ISBN: (纸本)9781479900305

Electro-hydraulic servo systems(EHSSs) have been widely used in industrial and military applications for their high power-to-size ratio and the ability to supply huge ***,precise control of EHSSs cannot be easily obtained due to their inner nonlinearity and parameter *** load is another factor to decrease the tracking performance of *** adaptive robust control(IARC) was proposed to improve the tracking performance of EHSS,but due to the poor parameter adapting speed,IARC can be further improved to have better *** projection type parameter estimation algorithm is redesigned to increase the adapting speed when parameter is changed.A fast adaptive robust control (FARC) is then proposed to speed up the parameter adapting speed,so that a better tracking performance of FARC is maintained. Simulation results show that the proposed FARC gives an improved tracking performance and a faster parameter adaptation.

关键词： Electric-Hydraulic Servo System Fast Adaptive Robust control

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