Article
Automation & Control Systems
Shuyuan Zhang, Lei Wang, Bai Xue, Chanying Li, Qing-Guo Wang
Summary: This article focuses on the consensus verification of heterogeneous polynomial networked systems (HPNSs) using a distributed nonlinear control protocol. The necessary condition for achieving consensus for HPNSs is presented, and multiple consensus criteria are proposed using polynomial Lyapunov functions under undirected and directed graphs. Compared to existing criteria based on quadratic Lyapunov functions, the results are less conservative and more general. The consensus verification problem is then transformed into a sum-of-squares optimization problem for finding polynomial Lyapunov functions. The theoretical and algorithmic developments are demonstrated through numerical examples, showing the effectiveness of the proposed method for fully automatic consensus verification of HPNSs.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Jason J. R. Liu, Nachuan Yang, Ka-Wai Kwok, James Lam
Summary: This paper investigates the positive consensus problem of multiagent systems with directed communication topologies. Several necessary and sufficient conditions for positive consensus are derived using linear matrix inequality techniques, and a computational algorithm for finding solutions is developed. Numerical simulations are provided to validate the effectiveness of the proposed theoretical results.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2022)
Article
Automation & Control Systems
Xianwei Li, Zhiyong Sun, Yang Tang, Hamid Reza Karimi
Summary: This article systematically investigates consensus of linear multiagent systems on directed graphs through adaptive event-triggered control, proposing innovative protocols with novel composite event-triggering conditions and verifying their effectiveness with numerical examples.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Junkang Ni, Ling Liu, Yang Tang, Chongxin Liu
Summary: This paper investigates the predefined-time consensus tracking problem of second-order multiagent systems, proposing a distributed observer and a novel sliding surface to achieve leader-following consensus within predefined time. Mathematical proof is provided that the followers can track the leader's trajectory within predefined time by adjusting tunable parameters for desired convergence time. The proposed method is verified effective in consensus tracking control for networked single-link robotic manipulators.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Automation & Control Systems
Junkang Ni, Yang Tang, Peng Shi
Summary: This paper introduces a novel distributed observer and consensus protocol for fixed-time consensus tracking of multiagent systems. The results demonstrate that each follower can track the leader's trajectory within a fixed time, with the gain directly related to the prescribed time.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Peng Shi, Jiafeng Yu
Summary: In this article, a novel polynomial fuzzy modeling approach is proposed to address the dissipativity-based consensus problem for polynomial fuzzy multiagent systems with switching directed topologies. A consensus control protocol is designed to ensure that the MASs under switching topologies can reach agreement, with conditions presented for exponential consensus with a strictly dissipative performance. The effectiveness of the new design scheme is demonstrated through an illustrative example.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Automation & Control Systems
Junyan Yu, Feng Xiao, Mengtao Cao
Summary: This article examines the lag group consensus problems of multiagent systems with directed information transformations. The agents in the network are divided into finite groups and modeled using high-order systems. Distributed consensus protocols with constant lags are proposed to achieve lag group consensus: the states of agents in a group asymptotically approach a consensus value, while maintaining given ratios between the final values of different groups. Necessary and sufficient criteria for lag group consensus are obtained through Laplace transformation. Finally, the theoretical results are validated through several simulation results.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Kuo Li, Chang-Chun Hua, Xiu You, Xin-Ping Guan
Summary: This article focuses on distributed consensus control for nonlinear multiagent systems under directed graphs of dynamic frequency switches. A novel distributed switched observer is constructed for each follower, accurately estimating the state information of the leader. A unified distributed controller is designed for each follower with the observer, and based on Lyapunov stability theory, it is proved that all agents can achieve consensus. The proposed algorithm can greatly reduce the conservativeness on graph switches and has wide application prospect in cooperative control.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Automation & Control Systems
Yafeng Li, Steven X. Ding, Changchun Hua, Guopin Liu
Summary: This article investigates the distributed dynamic output-feedback bipartite consensus for a class of stochastic nonlinear multiagent systems with time delays and actuators faults under directed switching graphs. The proposed compensator not only saves the network bandwidth but also compensates for the actuators' faults. The scheme can achieve bipartite consensus even under directed switching graphs and disconnected graphs over some time intervals.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Chengjie Huang, Zhi Liu, C. L. Philip Chen, Yun Zhang
Summary: This literature focuses on fast finite-time adaptive consensus control for nonlinear nontriangular structured (NTS) multiagent systems (MASs) with uncertainty. The consensus control for NTS MASs has two design difficulties, which are the nonaffine characteristics of the control input and the algebraic loop from the direct backstepping. Furthermore, the traditional adaptive framework is unable to achieve the desired finite-time asymptotic consensus due to the repeated utilization of necessary inequalities, only satisfying the practical finite-time stability. To tackle these obstacles, a novel adaptive neural algorithm is discussed in this work, utilizing a modified tuning function and projection operator. Under the constructed fast finite-time stabilizer, the error of the NTS MASs asymptotically converges to a preset range within finite time. The flexibility of the algorithm is demonstrated through a simulation example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Qingling Wang, Changyin Sun
Summary: This paper addresses the distributed asymptotic consensus problem for high-order nonaffine agents with uncertain dynamics, nonvanishing disturbances and unknown control directions under directed networks. A new DRISE design combined with Nussbaum-type function is proposed for achieving the desired consensus and boundedness of closed-loop variables. Simulation results with Duffing-Holmes chaotic systems verify the theoretical analysis.
IEEE-CAA JOURNAL OF AUTOMATICA SINICA
(2021)
Article
Computer Science, Artificial Intelligence
Jason J. R. Liu, James Lam, Ka-Wai Kwok
Summary: This article investigates the positive consensus problem of a special kind of interconnected positive systems over directed graphs. Based on the results in spectral graph theory, fractional-order systems (FOSs) theory, and positive systems theory, several necessary and/or sufficient conditions on the positive consensus of fractional-order multiagent systems (PCFMAS) are derived. A comprehensive comparison study shows that the proposed approaches have advantages over the existing ones.
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS
(2023)
Article
Automation & Control Systems
Jie Mei, Kaixin Tian, Guangfu Ma
Summary: We investigate the scaled position consensus problem of high-order multiagent systems with parametric uncertainties over switching directed graphs. We propose a distributed adaptive algorithm based on the MRACon scheme to achieve the scaled position consensus and validate its efficacy through numerical simulations.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Engineering, Multidisciplinary
Guanglei Zhao, Changchun Hua
Summary: This work investigates the leaderless and leader-following consensus problems for multiagent systems with asynchronous sampling mechanism and nonidentical packet losses. By proposing distributed sampled-data control protocols and a unified hybrid model, the issues of leaderless and leader-following consensus for MAS are addressed in a unified framework.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Automation & Control Systems
Chenliang Wang, Changyun Wen, Lei Guo
Summary: An adaptive consensus tracking control scheme is proposed for high-order nonlinear multiagent systems with unknown control directions, addressing unknown time-varying actuator faults. Novel Nussbaum functions and a monotonously increasing sequence are designed to reinforce effects rather than counteract each other. By introducing integrable auxiliary signals and a novel contradiction argument, the proposed scheme successfully achieves global stability and asymptotic convergence to zero of tracking errors, as demonstrated in simulation results.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2021)
Article
Engineering, Electrical & Electronic
Yanni Wan, Jiahu Qin, Yang Shi, Weiming Fu, Dunfeng Zhang
Summary: This paper investigates the privacy-preserving operation management problem of battery swapping and charging system (BSCS) and proposes a novel dual-based Benders decomposition algorithm to address the challenges of privacy protection and scheduling efficiency.
IEEE TRANSACTIONS ON SMART GRID
(2023)
Article
Automation & Control Systems
Peng Yi, Jinlong Lei, Jie Chen, Yiguang Hong, Guodong Shi
Summary: In this article, the authors studied the convergence and convergence rate of distributed linear equation protocols over a *-mixing random network. They proposed a distributed projection consensus algorithm and proved its exponential convergence rate in the mean-squared sense for networks with exact solutions. Additionally, they proposed a distributed randomized projection consensus algorithm and established an exponential rate of convergence. Moreover, they proved that a distributed gradient-descent-like algorithm with diminishing step-sizes can drive all nodes' states to a least-squares solution at a sublinear rate for networks without exact solutions.
IEEE TRANSACTIONS ON AUTOMATIC CONTROL
(2023)
Article
Automation & Control Systems
Lei Yu, Jiahu Qin, Shuai Wang, Yaonan Wang, Shi Wang
Summary: This article presents a novel feature-based visual-inertial odometry method called FSVIO, which utilizes both visual and inertial information in both the front and the back end. It introduces an IMU-aided feature-based method in the front-end visual processing part to build robust descriptors for image perspective deformation caused by camera motion. It also applies a fast-tracking method to improve feature matching efficiency and reduces outliers caused by dynamic environment or nonconvexity of the image.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Automation & Control Systems
Tongyu Wang, Peng Yi
Summary: In this paper, a distributed Frank-Wolfe algorithm based on gradient tracking is proposed to solve a distributed convex aggregative optimization problem in a network. The algorithm minimizes the sum of cost functions by maintaining two estimates at each node. The proposed algorithm is projection-free and only involves solving a linear optimization problem at each step. Convergence and computational efficiency of the algorithm are demonstrated through numerical simulations.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Automation & Control Systems
Yue Chen, Peng Yi
Summary: This study focuses on the decision making and management of engineering networks that involve conflicting interests among multiple parties, treated as a multi-cluster game. Each cluster is a self-interested player in a non-cooperative game, optimizing the cost function of the cluster. Challenges arise in large-scale networks where agent information is not immediately available beyond the cluster, challenging existing Nash equilibrium seeking algorithms. A distributed generalized Nash equilibrium seeking algorithm is proposed, allowing agents to estimate strategies of other clusters via communication with neighbors using an undirected network. The algorithm is proven to converge.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Zhijian Cheng, Hongru Ren, Jiahu Qin, Renquan Lu
Summary: This article focuses on the cybersecurity research of dynamic state estimation for power systems with measurement delays. A delayed measurement model is constructed based on mixed measurements from PMUs and RTUs. A modified state estimator using the Kalman filter is designed, and a chi-square-based attack detection method is proposed.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Baijia Ye, Jiahu Qin, Weiming Fu, Yingda Zhu, Yaonan Wang, Yu Kang
Summary: In this article, two novel distributed variational Bayesian algorithms are proposed for a general class of conjugate-exponential models over synchronous and asynchronous sensor networks. The PB-DVB algorithm is designed for synchronous networks, introducing a penalty function based on KL divergence to penalize the difference of posterior distributions between nodes. The TPB-DVB algorithm is developed for asynchronous networks by borrowing the token-passing approach and stochastic variational inference. Applications of the proposed algorithm on the GMM are exhibited, showing good performance in estimation/inference ability, robustness against initialization, and convergence speed for PB-DVB algorithm and superiority over existing token-passing-based distributed clustering algorithms for TPB-DVB algorithm.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Yutao Tang, Peng Yi
Summary: In this article, a Nash equilibrium seeking problem for a class of high-order multiagent systems with unknown dynamics is considered. The objective is to steer the outputs of these uncertain high-order agents to the Nash equilibrium of some noncooperative game in a distributed manner. To overcome the difficulties brought by the high-order structure, unknown nonlinearities, and the regulation requirement, a virtual player is introduced for each agent and an auxiliary noncooperative game is solved. A distributed adaptive protocol is developed by embedding this auxiliary game dynamics into some proper tracking controller for the original agent to resolve this problem. The parameter convergence issue is also discussed under certain persistence of excitation conditions. The efficacy of the algorithms is verified by numerical examples.
IEEE TRANSACTIONS ON CONTROL OF NETWORK SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Zheng Shi, Yingjun Zhang, Jingping Wang, Jiahu Qin, Xiaoqian Liu, Hui Yin, Hua Huang
Summary: Accurate and real-time traffic forecasting is crucial for urban traffic planning, control, and management. However, considering the time-varying dynamic spatial relations and complex spatial-temporal dependencies remains an open problem. To address this, we propose DAGCRN, a graph convolutional recurrent network that incorporates a dynamic adjacency matrix and an encoder-decoder framework for traffic forecasting. DAGCRN includes modules for relation extraction, adjacency matrix update, dynamic graph convolution, and global temporal attention. Experimental results on real-world traffic speed datasets demonstrate that DAGCRN consistently outperforms several representative baselines.
EXPERT SYSTEMS WITH APPLICATIONS
(2023)
Article
Engineering, Electrical & Electronic
Jiehan Liu, Peng Yi
Summary: This paper investigates a predefined-time distributed Nash equilibrium seeking problem for a class of noncooperative games under an event-triggered scenario. A novel approach is proposed to achieve fast convergence while reducing communication and computation costs by using gradient play, consensus-based estimator, and a time base generator (TBG).
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2023)
Article
Automation & Control Systems
Chengzhen Yan, Jiahu Qin, Qingchen Liu, Qichao Ma, Yu Kang
Summary: This article presents a method for safely training a mapless navigation policy using imitation learning with 2-D LiDAR inputs. The proposed training scheme includes controlled exploration strategy, safety-enhanced loss function, and a data augmentation technique. The method demonstrates remarkable performance in terms of training safety and navigation success rate.
IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS
(2023)
Article
Engineering, Civil
Lili Ran, Yanni Wan, Jiahu Qin, Weiming Fu, Dunfeng Zhang, Yu Kang
Summary: It is important to develop a coordinated battery swapping station (BSS) recommendation method to reduce the cost of electric vehicles (EVs) and optimize the operation of BSS system. This paper proposes a game theory-based approach to recommend suitable BSSs for EVs by considering the battery swapping cost, diversity of BSS capacities, and differentiated demands of EVs. A price function is designed to regulate the swapping price of each BSS, and an iterative algorithm is employed to seek the Nash equilibrium. The proposed approach effectively reduces the average cost of EVs, improves the success rate of battery swapping, and balances the utilization ratio of BSSs compared to the shortest distance approach.
IEEE TRANSACTIONS ON INTELLIGENT TRANSPORTATION SYSTEMS
(2023)
Article
Computer Science, Artificial Intelligence
Heng Li, Jiahu Qin, Qingchen Liu, Chengzhen Yan
Summary: In this paper, a gap-guided controller switching strategy is proposed to improve the training efficiency of deep reinforcement learning. By incorporating prior knowledge into network training through the combination of an online-mapless planner and expert demonstration, random exploration and sparse rewards in complex scenarios are avoided.
JOURNAL OF INTELLIGENT & ROBOTIC SYSTEMS
(2023)
Article
Automation & Control Systems
Xiaozheng Jin, Shaoyu Lu, Jiahu Qin, Wei Xing Zheng, Qingchen Liu
Summary: This article focuses on the output feedback security control of high-order nonlinear-interconnected systems with denial-of-service attacks, nonlinear dynamics, and exogenous disturbances. It adopts extreme learning machine (ELM) and adaptive techniques for nonlinear approximation and develops novel adaptive ELM-based nonlinear state observers to estimate unmeasurable states during DoS attacks under the influence of disturbances. Additionally, adaptive ELM-based controllers are proposed to achieve uniformly ultimately bounded results by combining with backstepping control and filtering techniques under the influence of DoS attacks, nonlinear dynamics, and exogenous disturbances. Comparative studies validate the effectiveness of the developed ELM-based adaptive observation and control strategies for two interconnected power systems.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
Article
Automation & Control Systems
Guanpu Chen, Peng Yi, Yiguang Hong, Jie Chen
Summary: In this article, we focus on solving distributed constrained optimization problems. We propose a distributed projection-free dynamics based on the Frank-Wolfe method to avoid projection operations caused by constraints. The approach finds a feasible descent direction through solving an alternative linear suboptimization problem. We also analyze the convergence of the continuous-time dynamical systems and derive a discrete-time scheme with a proved convergence rate of $O(1/k)$. Moreover, we compare our proposed dynamics with existing distributed projection-based dynamics and other distributed Frank-Wolfe algorithms to demonstrate its advantage.
IEEE TRANSACTIONS ON CYBERNETICS
(2023)
