Article
Physics, Multidisciplinary
Sergei Sidorov, Sergei Mironov
Summary: This study compares the structural properties of networks generated by growth models with random number of attached links to those with constant number of attached links. The research focuses on analyzing the differences in degree distributions of the networks generated by these models. By extending the classical models to allow for randomness in the number of attached links, the study shows that the 'random' versions of models have the capability to create new nodes with high degree at any iteration, which is a distinguishing feature from the classical models.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Engineering, Electrical & Electronic
Eneko Olea-Oregi, Pablo Eguia-Lopez, Alain Sanchez-Ruiz, Isabel Loureiro-Gonzalez
Summary: This paper provides an overview of the Back-to-Back-VSC type power links, which are a promising but underutilized technology for enhancing the operational flexibility of medium voltage (MV) distribution networks. It outlines four key aspects that Distribution System Operators should consider in their planning: power electronics, backhaul network characteristics, dispatching control strategies, and protection requirements. The paper offers detailed insights into power electronics and protections, focusing on an industrial approach rather than academic works and generic reviews. The study presents figures of high-capacity converters and uses a real distribution network model to evaluate converter capacity selection and protection requirements. It also introduces various control strategies for Back-to-Back VSC power links, highlighting the impact of the backhaul network. From a dispatching perspective, the paper provides an overview of different control strategies available for MV grids with varying levels of digitalization. Overall, this paper offers a comprehensive understanding of the technology readiness, integration requirements, and technical limitations of Back-to-Back VSC power links for deployment in MV distribution networks.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Physics, Multidisciplinary
Muhammad Asif, Zawar Hussain, Zahid Asghar, Muhammad Irfan Hussain, Mariya Raftab, Said Farooq Shah, Akbar Ali Khan
Summary: This study investigates the tail behavior of wealth data among world billionaires, finding that the upper tail of wealth data follows a Power Law distribution with exponents ranging from 1.306 to 1.571. Both Power Law and Lognormal distributions are found to be equally adequate for modeling the upper tail of wealth data. The estimate of Power Law exponent is significantly higher than unity, implying a more even distribution of wealth among billionaires compared to Zipf's Law.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Thomas J. Sargent, Neng Wang, Jinqiang Yang
Summary: According to the study, wealth is distributed more unequally than labor earnings, influenced by luck, attitudes towards saving decisions, and growth rates of labor earnings. Strong motives for people to save and firms to demand capital raise the equilibrium interest rate, causing wealth to grow faster than labor earnings and resulting in a more uneven distribution of wealth compared to labor earnings.
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
(2021)
Article
Green & Sustainable Science & Technology
Lishi Zhang, Yibin Liu, Deliang Liang, Peng Kou, Yuheng Wang, Yachen Gao, Dawei Li, Hua Liu
Summary: This paper proposes a hybrid distribution transformer integrating photovoltaics (HDT-PV) with local and remote cooperative control in an active distribution network (ADN). The HDT-PV can maximize the utilization of distributed solar energy and solve power quality problems. Remote cooperative control of multiple HDT-PVs optimizes the reactive power flow in the network. Even in case of device failures, the system can still operate stably.
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
(2022)
Article
Physics, Multidisciplinary
Jiang-Hai Qian, Song-Tao Zhao, Jing Xu
Summary: Recent empirical studies have found the wide existence of double power-law distribution in complex systems, which can be explained by controlling the parameters of the BA model. The control parameter p(c) plays a critical role in determining the shape of the degree distribution, leading to different distributions for different values of p. This model can provide possible explanations for real systems and demonstrate its validity.
PHYSICA A-STATISTICAL MECHANICS AND ITS APPLICATIONS
(2021)
Article
Mathematics, Interdisciplinary Applications
Xiangyi Meng, Bin Zhou
Summary: Complex networks are often considered to be scale-free, characterized by a power-law distribution of the nodes' degree. However, in real-world networks, the distribution of the degree-degree distance, a metric similar to degree, shows a stronger power-law distribution. We investigate the relationship between the two distributions and introduce network models that have a power-law distribution of degree-degree distance but not degree. Our findings suggest that degree-degree distance is a more suitable indicator of scale-freeness.
CHAOS SOLITONS & FRACTALS
(2023)
Article
Engineering, Electrical & Electronic
Andre Eggli, Stavros Karagiannopoulos, Saverio Bolognani, Gabriela Hug
Summary: This paper investigates the impact of local feedback control schemes on system stability when distributed energy resources (DERs) are connected to distribution grids, and explores solutions to the interference issues among multiple DERs. Using low-pass filters on DER set-points achieves closed-loop stability, preventing grid destabilization even with high-gain local control laws.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2021)
Article
Multidisciplinary Sciences
Haroldo Ribeiro, Milena Oehlers, Ana Moreno-Monroy, Jurgen P. Kropp, Diego Rybski
Summary: The research found a connection between urban scaling and Zipf's law, where the scale returns of urban GDP are related to the distribution of cities within a country.
Article
Optics
Tongyang Xu, Tianhua Xu, Izzat Darwazeh
Summary: A unique automatic signal distribution strategy based on the concept of non-orthogonality is proposed for private optical networks. Non-orthogonal signal waveforms compress spectral bandwidth, enabling fast signal identification and distribution in the network.
Article
Engineering, Electrical & Electronic
Xiaoyuan Xu, Yunhong Li, Zheng Yan, Hongyan Ma, Mohammad Shahidehpour
Summary: This paper proposes a hierarchical distribution network voltage control method considering active and reactive power coordination of PV units in both central and local control stages. The method defines the admissible range (AR) of PV power via centralized optimization and uses the affine decision rule (ADR) to control the reactive power. A two-stage optimization problem is proposed and transformed into tractable formulas. The results show that the hierarchical inverter control with AR can reduce PV power curtailment and ensure nodal voltages within limits.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Automation & Control Systems
Xinyang Zhou, Masoud Farivar, Zhiyuan Liu, Lijun Chen, Steven H. Low
Summary: The article investigates the impact of renewable and distributed energy resources on distribution networks, proposes two local voltage control schemes to solve an optimization problem, and highlights the limitations of nonincremental local voltage control.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Physics, Multidisciplinary
Sheng Zhang, Wenxiang Lan, Weikai Dai, Feng Wu, Caisen Chen
Summary: The paper extends the correlation dimension to weighted networks and uses edge-weights accumulation to obtain scale distances. The method was validated for the fractal scaling analysis of weighted complex networks and demonstrated to be more suitable for the quantitative analysis of small-world effects when compared to other fractal dimensions.
Article
Multidisciplinary Sciences
Takaaki Aoki, Naoya Fujiwara, Mark Fricker, Toshiyuki Nakagaki
Summary: The emergence of cities and road networks is influenced by the natural landscape, but the precise impact is still unresolved. This study incorporates high-resolution topographic maps into a pattern forming system and shows that the natural landscape may play a dominant role in establishing the baseline macro-scale population pattern.
SCIENTIFIC REPORTS
(2022)
Article
Physics, Multidisciplinary
L. Padilla, J. L. Iguain
Summary: We study the properties of random walks and electrical resistance in fractals obtained as the limit of a sequence of periodic structures. In the long-scale regime, power laws describe the mean-square displacement of a random walk with time and the electrical resistance with length. We provide analytical derivations and numerical simulations to show that the power-law exponents satisfy the Einstein relation, and we also find a local generalization of the Einstein relation at shorter scales.
Article
Automation & Control Systems
Guanghui Wen, Peijun Wang, Yuezu Lv, Guanrong Chen, Jialing Zhou
Summary: This paper studies the problem of secure consensus for multiple-input-multiple-output (MIMO) linear multi-agent systems (MASs) under denial-of-service (DoS) attacks and proposes corresponding control schemes and conditions. By designing an unknown input observer and using multiple Lyapunov functions, it is shown that secure consensus can be achieved under certain threshold conditions.
ASIAN JOURNAL OF CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Chengfang Hu, Guanghui Wen, Shuai Wang, Junjie Fu, Wenwu Yu
Summary: This article proposes a new class of distributed multiagent reinforcement learning (MARL) algorithm for addressing the dynamic economic dispatch problem (DEDP) in smart grids with coupling constraints. The algorithm utilizes a quadratic function to approximate the state-action value function and solves a convex optimization problem to obtain the approximate optimal solution. Furthermore, an improved experience replay mechanism is introduced to enhance the stability of the training process. The effectiveness and robustness of the proposed MARL algorithm are verified through simulations.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Chengxin Xian, Yu Zhao, Zheng-Guang Wu, Guanghui Wen, Ji-An Pan
Summary: This article investigates the event-triggered distributed average tracking (ETDAT) control problems for Lipschitz-type nonlinear multiagent systems with bounded time-varying reference signals. Two types of ETDAT algorithms, static and adaptive-gain, are developed using the state-dependent gain design approach and event-triggered mechanism. The study introduces the event-triggered strategy into DAT control algorithms for the first time and explores the ETDAT problem for multiagent systems with Lipschitz nonlinearities, which is more practical for real physical systems and meets the needs of practical engineering applications.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Dan Zhao, Xinghuo Yu, Guanghui Wen, Yifan Hu, Tingwen Huang
Summary: This article addresses the problem of dynamic task allocation with limited communication and velocity. The main challenge lies in selecting suitable winner participants and dealing with participant contention. By considering both the distance between the targets and participants and the motion direction of the targets, an improved evaluation index is proposed to avoid futile selection. An additional evaluation index is also presented to resolve participant contention. Control protocols for targets interception are developed and their stability is proven using the Lyapunov theory. Simulation examples are provided to demonstrate the effectiveness and advantages of the proposed algorithms.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Yifan Hu, Junjie Fu, Guanghui Wen
Summary: In this paper, a novel safe model-based RL algorithm is proposed to solve the collision-free model-reference trajectory tracking problem of uncertain autonomous vehicles (AVs). A new type of robust control barrier function (CBF) condition for collision-avoidance is derived by incorporating the estimation of the system uncertainty with Gaussian process (GP) regression. A robust CBF-based RL control structure is proposed, and within this structure, a Dyna-style safe model-based RL algorithm is developed to achieve safe exploration and improve sample efficiency.
IEEE TRANSACTIONS ON INTELLIGENT VEHICLES
(2023)
Article
Automation & Control Systems
Han Shen, Guanghui Wen, Yuezu Lv, Jun Zhou, Linan Wang
Summary: In this article, a new adaptive unscented Kalman filter is proposed for parameter estimation of nonlinear unmanned surface vessel (USV) models with unknown statistical characteristics of process noises. The parameter estimation problem is transformed into a state estimation problem by extending parameters and unknown inputs into augmented states. An adaptive law is designed to estimate the high-dimensional covariance matrix of the process noise. The proposed estimation approach is verified through practical experiments and numerical simulations.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2023)
Article
Automation & Control Systems
Jialing Zhou, Yuezu Lv, Guanghui Wen, Jinhu Lu, Dezhi Zheng
Summary: This article investigates the distributed Nash equilibrium seeking problem in multicoalition games, considering the agreement demand within coalitions. The proposed algorithm achieves linear convergence and unifies networked games among individual players and distributed optimization in a consistent-constrained multicoalition game framework.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Hong-Xiang Hu, Guanghui Wen, Guang Chen, Yun Chen, Xinghuo Yu
Summary: This article studies the output bipartite consensus problem of heterogeneous uncertain agents in state-dependent cooperation-competition networks. The agents are described by second-order continuous-time nonlinear systems with different intrinsic dynamics, and their uncertainties are characterized by unknown parameters. The edge evolution rules with hysteresis coefficients are proposed, and a distributed Lyapunov-based redesign method is applied to solve this problem. The explicit expressions of the distributed controllers and the unknown parameter estimators are obtained, and it is shown that the network remains connected and structurally balanced if the initial network topology is balanced and connected. Output bipartite consensus can be achieved asymptotically based on the total Lyapunov function. A numerical simulation is provided to validate the structural balance of state-dependent networks and output bipartite consensus of heterogeneous uncertain agents.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Automation & Control Systems
Yifan Hu, Junjie Fu, Guanghui Wen
Summary: Data-based machine learning methods have been used in control system design, but safety is a challenge due to uncertainties. This study proposes a barrier-function-based robust cooperative collision-avoidance control framework for heterogeneous multirobot systems. A new control barrier function design is proposed for less conservative feasible control actions. Decentralized robust conditions are derived, incorporating individual model uncertainty estimation to ensure safety. The proposed control framework is demonstrated effective through simulation examples.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Automation & Control Systems
Xinli Shi, Guanghui Wen, Jinde Cao, Xinghuo Yu
Summary: In distributed optimization, algorithms need to converge quickly and have low computation cost. Boundedness of control inputs is required for practical networking agent systems. Based on the finite-time distributed average tracking (FTDAT) problem, three types of discontinuous dynamics with bounded inputs are designed for solving unconstrained and constrained DO problems. The algorithms successfully find optimal solutions and achieve consensus in finite time.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Guanghui Wen, Wei Xing Zheng, Ying Wan
Summary: This article investigates the distributed robust optimization problem for a class of networked agent systems under stochastically switching communication graphs. By using a neuro-adaptive optimization protocol and a signum function-based feedback law, the problem is successfully resolved.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Peijun Wang, Guanghui Wen, Tingwen Huang, Wenwu Yu, Yuezu Lv
Summary: This paper investigates the asymptotical consensus problem for multi-agent systems (MASs) with unknown nonlinear dynamics under directed switching topology using a neural network (NN) adaptive control approach. It designs an observer for each follower to reconstruct the states of the leader, and proposes a discontinuous consensus controller and an NN adaptive law based on the idea of discontinuous control. The paper proves theoretically that asymptotical neuroadaptive consensus can be achieved in the considered MAS if the average dwell time (ADT) is larger than a positive threshold.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Qing Wang, Xiwang Dong, Guanghui Wen, Jinhu Lu, Zhang Ren
Summary: This article investigates the practical output containment problem for heterogeneous nonlinear multiagent systems under external disturbances and proposes a distributed observer-based control protocol to overcome the challenges of coupling, nonlinearities, and state dimensions. By constructing adaptive state observers and utilizing neural network approximation to compensate for unknown nonlinearities, a practical output containment control protocol is generated. The derived practical output containment criteria for the closed-loop system are derived based on the Lyapunov stability theory and the output regulation method.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Qiang Chen, Yu Zhao, Guanghui Wen, Guoqing Shi, Xinghuo Yu
Summary: This article studies the fixed-time distributed consensus tracking and fixed-time distributed average tracking problems for double-integrator-type multiagent systems with bounded input disturbances. A practical robust fixed-time sliding-mode control method based on the time-based generator is proposed. Various observers are designed to estimate state disagreement and measure the average value of reference signals.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Peijun Wang, Guanghui Wen, Wenwu Yu, Tingwen Huang, Xinghuo Yu
Summary: This article investigates the asymptotical consensus tracking problems for multiple-input-multiple-output linear multiagent systems with directed switching topology and a nonautonomous leader subject to nonzero unknown inputs. It proposes the design of a full-order and a reduced-order unknown input observer (UIO) to estimate the relative full states. Based on this UIO, a continuous consensus controller is designed by introducing a decay function. The effectiveness of the theoretical results is verified through the analysis of multiple Lyapunov functions and examples of unmanned aerial vehicles.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
