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2021 IEEE Sustainable Power and Energy Conference, iSPEC 2021

作者： Cui, Liu Peng, Guangqiang He, Jingsong Wu, Jiyang Mao, Chizu Jiao, Ning Electric Power Research Institute China Southern Power Grid State Key Laboratory of Hvdc GuangZhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System GuangZhou China Csg Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid GuangZhou China Maintenance Test Center Ehv Power Transmission Company Guangzhou China Csg Key Laboratory for Dc Transmission Equipment State Evaluation and Fault Diagnosis GuangZhou China Sichuan University College of Electrical Engineering and Information Technology Chengdu China

ISBN: (纸本)9781665414395

Modular multilevel converter (MMC) is currently the most concerned voltage source converter topology in the field of flexible direct current transmission (VSC-HVDC). Due to its non-linear characteristics, harmonic components will inevitably be generated in AC and DC systems, which may affect the operation of equipment and system, cause protection equipment to malfunction, and cause interference to neighboring communications. The MMC converter is a non-linear device, which can be considered as an amplifying modulator with voltage and current conversion functions. The AC and DC networks are coupled to each other through the MMC converter to generate dynamic harmonic interaction. In recent years, harmonic instability problems have appeared in many VSC-HVDC projects. Compared with other converter topologies, the transfer relationship of harmonics on the AC and DC sides of MMC converters has not been studied in depth. In this paper, by studying the AC/DC harmonic conversion characteristics of MMC converters, it reveals the conversion law of MMC converters between AC/DC harmonics;through theoretical derivation, the quantitative calculation method of MMC harmonic transmission process is given. PSCAD simulation results prove the correctness of the above results. © 2021 IEEE.

关键词： Transmissions

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Local Path Planning Algorithm for UGV Based on Improved Covariance Matrix Adaptive Evolution Strategy

Local Path Planning Algorithm for UGV Based on Improved Cova...

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第33届中国控制与决策会议

作者： Jiangbo Zhao Jiaquan Zhang Junzheng Wang Xin Zhang Yanlong Wang Key Laboratory of Complex System Intelligent Control and Decision School of AutomationBeijing Institute of Technology Key Laboratory of Servo Motion System Drive and Control Ministry of Industry and Information TechnologySchool of AutomationBeijing Institute of Technology Technical center Xinxing Cathay International Group Co.Ltd. Techenology Center of Special Vehicle Manufacture and Evaluation Engineering of Beijing Beijing North Vehicle Group Co.Ltd.

Local path planning algorithm is one of the key technologies for unmanned ground vehicle(UGV).In order to reduce the computational complexity of the local path planning algorithm and ensure the real-time performance of the algorithm,a non-uniform column grid lines modeling method is introduced,and on this basis,a modeling method for planning paths is *** at the path planning problem in a multi-obstacle environment,the evaluation function of the path is constructed from four aspects,and the covariance matrix adaptive evolution strategy(CMA-ES)is used to solve the nonlinear optimization *** order to further reduce the amount of calculation,the CMA-ES algorithm is improved by the dynamic adjustment strategy of population *** results show that the path planning algorithm can effectively realize the local path planning in complex environment.

关键词： Local path planning CMA-ES Unmanned ground vehicle

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Distributed urban freeway traffic optimization considering congestion propagation

arXiv

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arXiv 2021年

作者： Gao, Fengkun Yang, Bo Chen, Cailian Guan, Xinping Zhang, Yang Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Industrial Intelligent Control and Management Shanghai200240 China Shanghai Municipal Urban-Rural Construction and Transportation Development Institute China

Traffic optimization strategies are imperative for improving the performance of transportation networks. Most traffic optimization strategies only depend on traffic states of congested road segments, where congestion propagation is neglected. Therefore, we propose a distributed traffic optimization strategy for urban freeways considering the potential congested road segments caused by congestion propagation, called potential-homogeneous-area (PHA). Utilizing the historical traffic density data, we firstly quantify the effect of congestion propagation and identify PHA by applying the proposed spatio-temporal lambda-connectedness method. Meanwhile, dynamic capacity constraints of PHA are determined and are integrated with cell transmission model (CTM) in a centralized traffic optimization problem. To reduce computational complexity and improve scalability, we then propose a doubleconsensus- based alternating direction method of multipliers algorithm (DC-ADMM) to handle the neighbor coupling constraints and global coupling constraints for solving the problem in a fully distributed way. We prove that the proposed DC-ADMM algorithm converges to the optimal solution in the condition of convex objective function. Finally, simulations based on real traffic density data, collected in Inner Ring Road, Shanghai, China, reveal the effectiveness of our proposed strategy. © 2021, CC BY.

关键词： Roads and streets

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Distributed Neighbor Selection in Multi-agent Networks

arXiv

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arXiv 2021年

作者： Shao, Haibin Pan, Lulu Mesbahi, Mehran Xi, Yugeng Li, Dewei Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China William E. Boeing Department of Aeronautics and Astronautics University of Washington SeattleWA98195-2400 United States

Achieving consensus via nearest neighbor rules is an important prerequisite for multi-agent networks to accomplish collective tasks. A common assumption in consensus setup is that each agent interacts with all its neighbors. This paper examines whether network functionality and performance can be maintained-and even enhanced-when agents interact only with a subset of their respective (available) neighbors. As shown in the paper, the answer to this inquiry is affirmative. In this direction, we show that by exploring the monotonicity property of the Laplacian eigenvectors, a neighbor selection rule with guaranteed performance enhancements, can be realized for consensus-type networks. For distributed implementation, a quantitative connection between entries of Laplacian eigenvectors and the "relative rate of change" in the state between neighboring agents is further established;this connection facilitates a distributed algorithm for each agent to identify "favorable" neighbors to interact with. Multi-agent networks with and without external influence are examined, as well as extensions to signed networks. This paper underscores the utility of Laplacian eigenvectors in the context of distributed neighbor selection, providing novel insights into distributed data-driven control of multi-agent systems. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

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Asynchronous Algorithm for Distributed Multi-agent Convex Optimization

Asynchronous Algorithm for Distributed Multi-agent Convex Op...

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第三十九届中国控制会议

作者： Duqiao Zhao Ding Liu Xia Zhang National & Local Joint Engineering Research Center of Crystal Growth Equipment and System Integration Xi'an University of Technology Shaanxi Key Laboratory of Complex System Control and Intelligent Information Processing

This paper proposes an asynchronous algorithm for distributed optimization problem(Asy-DOP) in multi-agent network with gradient *** algorithm can be implemented in an asynchronous distributed *** objective function of the algorithm is the sum of the local functions of multiple nodes in the network,each node only knows its own local objective function and can exchange information with its *** addition,the algorithm is based on the undirected connected graph and requires the objective function is Lipschitz *** step-size of the proposed algorithm is homogeneous and when the step-size is in a suitable range,it is proved that the convergence rate of the proposed algorithm is O(1/(?)),where the k is the number of iterations.

关键词： asynchronous algorithm distributed optimization multi-agent gradient method

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Opponent Strategy Recognition In Real Time Strategy Game Using Deep Feature Fusion Neural Network

Opponent Strategy Recognition In Real Time Strategy Game Usi...

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International Conference on Computers, Communications, and systems (ICCCS)

作者： Wei Cheng Qiyue Yin Junge Zhang School of Control and Computer Engineering North China Electric Power University Beijing China Beijing China Center for Research on Intelligent System and Engineering CASIA Beijing China

ISBN: (数字)9781728161365

ISBN: (纸本)9781728161372

This paper focuses on the task of opponent strategies recognition in Real-time Strategy (RTS) Game, which aims to predict opponent strategies by modeling the observable environmental information. It is a very challenging task due to two folds. (1) In RTS game, the information is imperfect due to the fog of war; and (2) the action and environment spaces of RTS game are too vast and complex to be modeled. This task is also significative since opponent strategies recognition is a crucial component of creating high-level AI system that can defeat high-level human players in RTS game. Most previous approaches focus on predicting tech tree, building order and strategies through game logs, where perfect information is utilized. Accordingly, these prediction methods cannot be applied to real AI systems confronting the fog of war. Furthermore, conventional approaches use machine learning techniques such as Hidden Markov Model (HMM) and Bayesian network, which is difficult to deal with higher-dimensional state spaces. Besides, the hand-crafted features are commonly used instead of high-dimensional feature of the complex environment, which leads to loss of information of the environment. To address these problems, we propose a deep feature fusion neural network to handle the above imperfect and complex information of the environment for opponent strategies recognition in RTS game. We test our method on the canonical RTS game, i.e., Starcraft II, and promising performance has been obtained.

关键词： Hidden Markov models Games Feature extraction Predictive models Bayes methods Decoding Neural networks

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Inverse linear-quadratic discrete-time finite-horizon optimal control for indistinguishable homogeneous agents: a convex optimization approach

arXiv

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arXiv 2021年

作者： Zhang, Han Ringh, Axel Department of Automation School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University Shanghai China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China Department of Mathematical Sciences Chalmers University of Technology University of Gothenburg Gothenburg41296 Sweden

The inverse linear-quadratic optimal control problem is a system identification problem whose aim is to recover the quadratic cost function and hence the closed-loop system matrices based on observations of optimal trajectories. In this paper, the discrete-time, finite-horizon case is considered, where the agents are also assumed to be homogeneous and indistinguishable. The latter means that the agents all have the same dynamics and objective functions and the observations are in terms of "snap shots" of all agents at different time instants, but what is not known is "which agent moved where" for consecutive observations. This absence of linked optimal trajectories makes the problem challenging. We first show that this problem is globally identifiable. Then, for the case of noiseless observations, we show that the true cost matrix, and hence the closed-loop system matrices, can be recovered as the unique global optimal solution to a convex optimization problem. Next, for the case of noisy observations, we formulate an estimator as the unique global optimal solution to a modified convex optimization problem. Moreover, the statistical consistency of this estimator is shown. Finally, the performance of the proposed method is demonstrated by a number of numerical examples. Copyright © 2021, The Authors. All rights reserved.

关键词： Convex optimization

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Local Partial Zero-Forcing Combining for Cell-Free Massive MIMO systems

arXiv

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arXiv 2022年

作者： Zhang, Jiayi Zhang, Jing Björnson, Emil Ai, Bo The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Beijing Jiaotong University Beijing100044 China The Department of Electrical Engineering Linköping University Linköping Sweden The Department of Computer Science KTH Royal Institute of Technology Kista Sweden The State Key Laboratory of Rail Traffic Control and Safety Beijing Jiaotong University Beijing100044 China The Frontiers Science Center for Smart High-Speed Railway System Henan Joint International Research Laboratory of Intelligent Networking and Data Analysis Zhengzhou University Zhengzhou450001 China Research Center of Networks and Communications Peng Cheng Laboratory Shenzhen China

Cell-free massive multiple-input multiple-output (MIMO) provides more uniform spectral efficiency (SE) for users (UEs) than cellular technology. The main challenge to achieve the benefits of cell-free massive MIMO is to realize signal processing in a scalable way. In this paper, we consider scalable full-pilot zero-forcing (FZF), partial FZF (PFZF), protective weak PFZF (PWPFZF), and local regularized ZF (LRZF) combining by exploiting channel statistics. We derive closed-form expressions of the uplink SE for FZF, PFZF, and PWPFZF combining with large-scale fading decoding over independent Rayleigh fading channels, taking channel estimation errors and pilot contamination into account. Moreover, we investigate the impact of the number of pilot sequences, antennas per AP, and APs on the performance. Numerical results show that LRZF provides the highest SE. However, PWPFZF is preferable when the number of pilot sequences is large and the number of antennas per AP is small. The reason is that PWPFZF has lower computational complexity and the SE expression can be computed in closed-form. Furthermore, we investigate the performance of PWPFZF combining with fractional power control and the numerical results show that it improves the performance of weak UEs and realizes uniformly good service for all UEs in a scalable fashion. Copyright © 2022, The Authors. All rights reserved.

关键词： Power control

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Non-reciprocity of energy transfer derived from cubic stiffness-induced nonlinear phenomena

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Results in Physics 2025年 73卷

作者： Kong, Na Sun, Min Chen, Jianen Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin 300384 China National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin 300384 China School of Science Tianjin Chengjian University Tianjin 300384 China

Introducing purely nonlinear elastic elements can induce rich dynamic behaviors, such as bifurcations, jumps and isolated resonance curves, to linear systems. Therefore, these elements are suitable for constructing strong non-reciprocity of vibration energy transfer. First, the energy transfer along reciprocal directions in a three-degree-of-freedom system is investigated, where three oscillators are connected by cubic springs. The semi-analytical solutions of the system are obtained using the complexification-averaging method and the least squares method. The results are compared against numerical solutions obtained by the Runge-Kutta method. The excitation amplitude range that produces strong non-reciprocity of vibration energy is analyzed. The jump phenomenon under combined excitation is investigated, and a trigger method for constructing non-reciprocity using an impulse is proposed. Then, an oscillator chain with cubic stiffness and scaling parameters is embedded into a multi-degree-of-freedom linear oscillator system to further explore the effect of cubic stiffness. Energy transfer along two directions is compared by exciting the leftmost oscillator and the rightmost oscillator. Moreover, the trigger effect of the impulse on non-reciprocity is demonstrated. The results show significant differences in vibration energy transfer within three distinct frequency bands. The critical points between reciprocal and non-reciprocal states are obtained, and the three stages of reciprocity related to excitation amplitude are analyzed. Lastly, the modulation effect of the cubic stiffness on non-reciprocity is conducted by comparing the energy of the output oscillator. © 2025 The Authors

关键词： Cubic stiffness Energy transfer Jump phenomenon Non-reciprocity

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Self-Tuning Clamping Force control with Optimal Trajectory Tracking for Autonomous Pipe Inspection Robots

SSRN

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SSRN 2025年

作者： Sun, Guoxin Xia, Longfei Du, Xinpeng Yu, Qihui Zhang, Jianlong Qin, Ripeng School of Mechanical Engineering Inner Mongolia University of Science and Technology Inner Mongolia Autonomous Region Baotou014010 China Inner Mongolia Engineering Technology Research Center of Mechatronics System Intelligent Diagnosis & Control Engineering 014010 China Inner Mongolia Ming yang North Smart Energy Research and Development Center Co LTD China Department of Mechanical Engineering Denmark Inner Mongolia University of Science and Technology China

In response to the limitations of existing external pipe-crawling robots, which are unable to automatically adjust clamping force during operation, a novel external pipe-crawling robot has been designed. To enable adaptive clamping based on varying pipeline conditions, an adaptive clamping force control method based on optimal speed curve tracking is proposed. First, the target clamping force is calculated according to pipeline conditions, and it is then converted into a target speed signal through optimal speed curve planning. Subsequently, the motor precisely tracks the speed signal to achieve accurate clamping force control. Experimental results from the robot prototype demonstrate that the proposed algorithm maintains a clamping force control error rate of less than 8.0% under pipelines with different diameters, inclination angles, and surface roughness, ensuring stable operation across various pipeline conditions. © 2025, The Authors. All rights reserved.

关键词： Clamping devices

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