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Dynamic Route Optimization for Multi-Vehicle systems with Diverse Needs in Road Networks Based on Preference Games

Computers, Materials and Continua 2025年第3期83卷 4167-4192页

作者： Wang, Jixiang Wei, Jing Chen, Siqi Yu, Haiyang Ren, Yilong School of Transportation Science and Engineering Beihang University Beijing 100191 China School of Electrical and Control Engineering North China University of Technology Beijing 100144 China Hangzhou Innovation Institute Beihang University Hangzhou 310023 China The State Key Lab of Intelligent Transportation System Beijing 100191 China

The real-time path optimization for heterogeneous vehicle fleets in large-scale road networks presents significant challenges due to conflicting traffic demands and imbalanced resource allocation. While existing vehicle-to-infrastructure coordination frameworks partially address congestion mitigation, they often neglect priority-aware optimization and exhibit algorithmic bias toward dominant vehicle classes—critical limitations in mixed-priority scenarios involving emergency vehicles. To bridge this gap, this study proposes a preference game-theoretic coordination framework with adaptive strategy transfer protocol, explicitly balancing system-wide efficiency (measured by network throughput) with priority vehicle rights protection (quantified via time-sensitive utility functions). The approach innovatively combines (1) a multi-vehicle dynamic routing model with quantifiable preference weights, and (2) a distributed Nash equilibrium solver updated using replicator sub-dynamic models. The framework was evaluated on an urban road network containing 25 intersections with mixed priority ratios (10%–30% of vehicles with priority access demand), and the framework showed consistent benefits on four benchmarks (Social routing algorithm, Shortest path algorithm, The comprehensive path optimisation model, The emergency vehicle timing collaborative evolution path optimization method) showed consistent benefits. Results show that across different traffic demand configurations, the proposed method reduces the average vehicle traveling time by at least 365 s, increases the road network throughput by 48.61%, and effectively balances the road loads. This approach successfully meets the diverse traffic demands of various vehicle types while optimizing road resource allocations. The proposed coordination paradigm advances theoretical foundations for fairness-aware traffic optimization while offering implementable strategies for next-generation cooperative vehicle-road systems, particul

关键词： different needs dynamic route selection large-scale road network Preference game vehicle road coordination

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Deep Learning and Projection Neural Network With Finite-Time Convergence for Energy Management of Multi-Energy system

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IEEE Transactions on Smart Grid 2025年第3期16卷 2156-2168页

作者： Liu, Xueying He, Xing Li, Chaojie Huang, Tingwen Southwest University Chongqing Key Laboratory of Nonlinear Circuits and Intelligent Information Processing College of Electronic and Information Engineering Chongqing400715 China North China Electric Power University State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources Beijing102206 China Shenzhen University of Advanced Technology Faculty of Computer Science and Control Engineering Shenzhen518055 China

In this paper, an approach based on projection neural network (PNN), sliding mode control technique, and deep learning is proposed to solve the energy management problem of multi-energy systems (MES) containing dynamic parameters. First, the sliding mode technique is introduced in the PNN to design a finite-time PNN (FTPNN). The stability and finite-time convergence of the proposed FTPNN are proved by the Lyapunov method and the setting time bound is given. Then, the deep FTPNN (DFTPNN) is designed by combining deep learning with the proposed FTPNN. The dynamic parameters in the MES that change over time are used as input variables for the DFTPNN, allowing the trained DFTPNN to respond immediately to changes in the dynamic parameters and to predict the solutions of the FTPNN with different parameters directly. Simulation experiments show that FTPNN has faster convergence compared to PNN. DFTPNN significantly reduces the computation time compared to FTPNN. DFTPNN provides predicted solutions to FTPNN. Since DFTPNN can respond immediately to changes in dynamic parameters and directly provide energy management strategies under different parameters, it can adapt to changing environments and promote the economic and stable operation of MES. © 2010-2012 IEEE.

关键词： Cogeneration Heuristic algorithms Convergence Deep learning Prediction algorithms Optimization Heating systems Energy management Approximation algorithms Power system stability

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Improved Extrinsic Calibration of Acoustic Cameras via Batch Optimization

Improved Extrinsic Calibration of Acoustic Cameras via Batch...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Zhi Li Jiang Wang Xiaoyang Li He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems and the Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Acoustic cameras have found many applications in practice. Accurate and reliable extrinsic calibration of the microphone array and visual sensors within acoustic cameras is crucial for fusing visual and auditory measurements. Existing calibration methods either require prior knowledge of the microphone array geometry or rely on grid search which suffers from slow iteration speed or poor convergence. To overcome these limitations, in this paper, we propose an automatic calibration technique using a calibration board with both visual and acoustic markers to identify each microphone position in the camera frame. We formulate the extrinsic calibration problem (between microphones and the visual sensor) as a nonlinear least squares problem and employ a batch optimization strategy to solve the associated problem. Extensive numerical simulations and real-world experiments show that the proposed method improves both the accuracy and robustness of extrinsic parameter calibration for acoustic cameras, in comparison to existing methods. To benefit the community, we open-source all the codes and data at https://***/AISLAB-sustech/AcousticCamera.

关键词： Visualization Accuracy Cameras Numerical simulation Acoustics Robustness Microphone arrays Calibration Optimization Sensor arrays

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Calibration of Multiple Asynchronous Microphone Arrays using Hybrid TDOA

Calibration of Multiple Asynchronous Microphone Arrays using...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Chengjie Zhang Wenda Pan Xinyang Han He Kong Shenzhen Key Laboratory of Control Theory and Intelligent Systems and the Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Southern University of Science and Technology Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Accurate calibration of acoustic sensing systems made of multiple asynchronous microphone arrays is essential for satisfactory performance in sound sour ce localization and tracking. State-of-the-art calibration methods for this type of system rely on the time difference of arrival and direction of arrival measurements among the microphone arrays (denoted as TDOA-M and DOA, respectively). In this paper, to enhance calibration accuracy, we propose to incorporate the time difference of arrival measurements between adjacent sound events (TDOA-S) with respect to the microphone arrays. More specifically, we propose a two-stage calibration approach, including an initial value estimation (IVE) procedure and the final joint optimization step. The IVE stage first initializes all parameters except for microphone array orientations, using hybrid TDOA (i.e., TDOA-M and TDOA-S), odometer data from a moving robot carrying a speaker, and DOA. Subsequently, microphone orientations are estimated through the iterative closest point method. The final joint optimization step estimates multiple microphone array locations, orientations, time offsets, clock drift rates, and sound source locations simultaneously. Both simulation and experiment results show that for scenarios with low or moderate TDOA noise levels, our approach outperforms existing methods in terms of accuracy. All code and data are available at https://***/AISLAB-sustech/Hybrid-TDOA-Multi-Calib.

关键词： Direction-of-arrival estimation Accuracy Time difference of arrival Position measurement Odometers Microphone arrays Calibration Arrays Optimization Noise level

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Calibration of Multiple Asynchronous Microphone Arrays using Hybrid TDOA

arXiv

引用

arXiv 2025年

作者： Zhang, Chengjie Pan, Wenda Han, Xinyang Kong, He Shenzhen Key Laboratory of Control Theory and Intelligent Systems The Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology The Southern University of Science and Technology Shenzhen518055 China

Accurate calibration of acoustic sensing systems made of multiple asynchronous microphone arrays is essential for satisfactory performance in sound source localization and tracking. State-of-the-art calibration methods for this type of system rely on the time difference of arrival and direction of arrival measurements among the microphone arrays (denoted as TDOA-M and DOA, respectively). In this paper, to enhance calibration accuracy, we propose to incorporate the time difference of arrival measurements between adjacent sound events (TDOA-S) with respect to the microphone arrays. More specifically, we propose a two-stage calibration approach, including an initial value estimation (IVE) procedure and the final joint optimization step. The IVE stage first initializes all parameters except for microphone array orientations, using hybrid TDOA (i.e., TDOA-M and TDOA-S), odometer data from a moving robot carrying a speaker, and DOA. Subsequently, microphone orientations are estimated through the iterative closest point method. The final joint optimization step estimates multiple microphone array locations, orientations, time offsets, clock drift rates, and sound source locations simultaneously. Both simulation and experiment results show that for scenarios with low or moderate TDOA noise levels, our approach outperforms existing methods in terms of accuracy. All code and data are available at https://***/AISLABsustech/Hybrid-TDOA-Multi-Calib. © 2025, CC BY.

关键词： Microphone array

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Safe RL-based Adaptive Cooperative Game control of Wing Deformation and Flight State Tracking for Morphing Hypersonic Vehicles

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Wang, Jun-Wei Wang, Feng Wu, Huai-Ning Liu, Zhou-Yang University of Science and Technology Beijing School of Intelligence Science and Technology Beijing100083 China Beihang University School of Automation Science and Electrical Engineering Beijing100191 China Beihang University Hangzhou International Innovation Institute Hangzhou311115 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Beijing100074 China

This study addresses the issue of adaptive cooperative game control (ACGC) design for wing deformation and flight state tracking of morphing hypersonic vehicles (MHVs) with variable wing shapes, input constraints and state constraints. To access a better flight control performance, the wing deformation parameter is extended in this work as an auxiliary control input. An oriented-coordinated-control nonlinear differential equation model is first established to describe the complicated longitudinal flight state tracking error dynamics of the MHV. Then, a control barrier function (CBF) is introduced and incorporated into the value function as a risk penalty term of state security constraint. Based on the differential game (DG) theory, the optimal coordinated control problem for the MHV with input constraints and state constraints is treated as a constrained cooperative DG that is further formulated as a Hamilton-Jacobi-Bellman (HJB) equation with barrier and hyperbolic functions. A safe RL algorithm is proposed to solve the above HJB equation and an online Pareto joint control strategy is achieved thereby. Hereafter the stability analysis of the closed-loop state tracking error system is done by the Lyapunov technique. Meanwhile, both state and input constraints are met during the the parameter learning regulation process. At last, a simulation study is performed to support the proposed safe RL-ACGC algorithm. © 2025 IEEE.

关键词： Hyperbolic functions

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Dual and reduced-order observer based attack-free protocols for consensus of multi-agent systems with Markovian switching topologies

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systems and control Letters 2025年 202卷

作者： Gao, Tian-Yu Li, Zhao-Yan Zhou, Bin Center for Control Theory and Guidance Technology Harbin Institute of Technology Harbin150001 China National Key Laboratory of Complex System Control and Intelligent Agent Cooperation Harbin150001 China School of Mathematics Harbin Institute of Technology Harbin150001 China Zhengzhou Research Institute of HIT Zhengzhou450000 China

This paper studies the output feedback consensus problem of linear multi-agent systems with Markovian switching topologies. To avoid reconstructing the Markovian switching topologies during designing the observers or adding the state of the observers to the information exchange loop, dual and reduced-order observer based attack-free consensus protocols are proposed, which only utilizes the relative outputs of neighboring agents. It is shown that, under certain mild conditions, a necessary and sufficient condition for the solvability of the mean square consensus problem is that the union of switching topologies has a spanning tree. Finally, numerical examples are given to illustrate the effectiveness of the proposed approaches. © 2025 Elsevier B.V.

关键词： Markov processes

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State-Dependent Switching control for Nonlinear Impulsive Switched systems With Dwell Time

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IEEE Transactions on Automation science and Engineering 2025年 22卷 12093-12101页

作者： Yang, Dan Li, Xiaodi Zhang, Guofeng Lee, Heung Wing Joseph Shandong Normal University School of Mathematics and Statistics Jinan250014 China Yantai University School of Mathematics and Information Science Yantai264005 China Shandong Normal University Shandong Provincial Engineering Research Center of System Control and Intelligent Technology Jinan250358 China The Hong Kong Polytechnic University Department of Applied Mathematics Hong Kong Hong Kong Polytechnic University Shenzhen Research Institute Shenzhen518057 China

This paper investigates the problem of globally exponential stability (GES) for impulsive switched systems via a hybrid switching strategy. First, a switching law combining state-dependent and time-dependent (dwell time) switching strategies is presented in the framework of impulse action. On the basis of the switching law, some GES criteria are proposed by using multiple Lyapunov function technique. A potential relationship among system parameters, impulse action including impulse amplitude and impulse frequency, and the combined switching law is established, which is of vital importance to achieving GES. In addition, when the impulse action involved in switched system is given in terms of stabilizing impulse, the impulsive controller including impulsive gains and impulsive frequency can be designed with the help of the proposed switching law to guarantee the stability of the addressed system. Finally, a simulation example is demonstrated to verify the validity of the proposed switching law and corresponding results. © 2004-2012 IEEE.

关键词： Switches Switched systems control systems Stability criteria Symmetric matrices Automation Lyapunov methods Germanium Electronic mail Trajectory

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Object Detection and Multiple Objective Optimization Manipulation Planning for Underwater Autonomous Capture in Oceanic Natural Aquatic Farm

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Journal of Field Robotics 2025年第0期

作者： Hai, Huang Tao, Jiang Xinyu, Bian Hao, Zhou Xu, Yang Gang, Wang Hongde, Qin Xinyue, Han National Key Laboratory of Science and Technology on Underwater Vehicle Harbin Engineering University Harbin China State Key Laboratory of Management and Control for Complex System Institute of Automation Chinese Academy of Science Bei Jing China

Underwater autonomous capture operations offer significant potential for reducing labor and health risks in sea organism industries. This study presents a comprehensive solution for cross-domain underwater object detection and autonomous capture. A novel unsupervised domain adaptive learning method is proposed, integrating multiscale domain adaptive modules and attention mechanisms into a Faster Region-Convolutional Neural Network framework. This approach enhances feature alignment across diverse aquatic domains without parameter tuning. Additionally, an efficient, parameterless constrained multiobjective optimization algorithm is introduced for underwater autonomous mobile capture, integrating parameterized trajectory planning with innovative features, such as adaptive mutation strategies and constraint violation tolerance. The proposed approaches are extensively validated through simulations, tank experiments, and real-world oceanic trials in the Natural Aquatic Farm of Zhangzidao Island. Results demonstrate the system's robustness in complex underwater environments with varying currents, with experimental outcomes validating the accuracy and reliability of detection and capture capabilities. This research significantly advances autonomous underwater systems' capabilities in object detection and capture tasks, addressing complex challenges in realistic organism capture applications across diverse aquatic environments. © 2025 Wiley Periodicals LLC.

关键词： Health risks

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Optimal Sensor Placement for Full-Set TDOA Localization Accounting for Sensor Location Errors

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Zhang, Chengjie Han, Xinyang Kong, He Ho, K.C. Southern University of Science and Technology Shenzhen Key Laboratory of Control Theory and Intelligent Systems Guangdong Provincial Key Laboratory of Fully Actuated System Control Theory and Technology Shenzhen518055 China University of Missouri Electrical Engineering and Computer Science Department ColumbiaMO65211 United States

The positioning accuracy of a signal source is influenced by where the sensors are deployed. Studies in the literature for the optimal sensor placement (OSP) of localization often ignore the presence of sensor position errors. In practice, however, it is impossible to place the sensors precisely at the desired locations. This work designs OSP by accounting for the presence of Gaussian sensor position errors that are independent and identically distributed (IID), with the full set of Time Difference of Arrival measurements corrupted by Gaussian IID noise. The criterion is the A-optimality equal to the trace of the source position Cramer-Rao Bound (CRB). We show that the presence of sensor position errors introduces a multiplication factor to the same criterion for the case without sensor position errors. The latter factor is dependent on the ratio of the sensor position error power to the range difference noise power but independent of the sensor positions, implying that the A-optimality OSP in the presence of sensor position errors is the same as in the absence. To our knowledge, this is the first time such results have been derived. Simulation studies validate the derived OSP, show the minimal OSP performance gap with sensor positioning error and without, and illustrate the better source localization accuracy by OSP. © 1965-2011 IEEE.

关键词： Cramer-Rao bounds

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