Article
Automation & Control Systems
Shihao Wang, Shiqi Zheng, Choon Ki Ahn, Peng Shi, Xiaowei Jiang
Summary: This paper investigates the event-triggered cooperative output regulation problem for uncertain multi-agent systems and demonstrates the convergence of the output regulation error. The proposed method deals with unknown parameter systems and allows for heterogeneous follower systems. It is a fully distributed controller that only requires relative outputs and incorporates a reduced-order observer and adaptive event-triggered mechanisms. The approach is validated through simulations and experiments on a multi-joint robot manipulator.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Lianghao Ji, Shuo Tong, Huaqing Li
Summary: This paper investigates the dynamic group consensus for a class of heterogeneous multi-agent systems under the influence of input time delays, proposing a novel protocol and establishing sufficient conditions for achieving consensus in the systems. The results reveal the relationship between systems' control parameters, in-degree and input time delays of the agents, and the achievement of dynamic group consensus. The effectiveness of the theoretical results is verified through numerical simulations.
Article
Engineering, Mechanical
Shuai Cheng, Bin Xin, Qing Wang, Minggang Gan, Bin He, Yulong Ding
Summary: This article investigates the cooperative control of nonlinear multi-agent systems subject to non-affine faults under directed graphs. A new distributed fixed-time event-triggered control protocol is proposed, along with a dynamic switching event-triggered mechanism and a dynamic internal trigger variable to reduce the number of system triggers. The article also presents a proof that guarantees the boundedness of all signals in the closed-loop system and the convergence of consensus tracking errors within a fixed time.
NONLINEAR DYNAMICS
(2023)
Article
Automation & Control Systems
Dianqiang Li, Tao Li
Summary: We study the cooperative output feedback tracking control of a stochastic nonlinear heterogeneous leader-following multi-agent system. Each agent has continuous-time stochastic nonlinear dynamics with an unmeasurable state, and there are additive and multiplicative noises along with information exchange among the agents. We propose admissible distributed observation strategies and cooperative output feedback control strategies based on the certainty equivalence principle. By using output regulation theory and stochastic analysis, we prove the existence of admissible distributed observation and cooperative control strategies to ensure mean square bounded output tracking, under certain conditions on the system dynamics and noise intensity.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Computer Science, Artificial Intelligence
Dong Liang, Yi Dong
Summary: This paper proposes a distributed state and output feedback control law based on the dynamic event-triggered mechanism to solve the robust cooperative output regulation problem for a class of general linear uncertain multi-agent systems (MASs) subject to external disturbances. The proposed control law is directly implementable in the digital platform and can handle parametric uncertainties, reject external disturbances, and track a dynamic leader, while avoiding the Zeno phenomenon.
Article
Engineering, Multidisciplinary
Guanglei Zhao, Changchun Hua, Shuang Liu
Summary: This paper investigates the consensus problem in multi-agent systems using sampled-data dynamic output feedback control. A distributed control law is designed based on sampled relative output information between neighboring agents. A closed-loop system model with hybrid dynamics is constructed for consensus analysis and choice of sampling period. Lyapunov-based analysis is presented to develop stability conditions. Compared to existing works, observer design is not required, and only sampled relative output information is used, with the ability to explicitly compute the maximum allowable sampling period.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Information Systems
Lijing Dong, Kaige Liu, Shengli Du, Hao Yan, Haikuo Shen
Summary: This paper studies the problem of tracking a non-cooperative target by heterogeneous multi-agent systems (MASs) with actuator faults. Due to the non-cooperative nature of the target, the system matrix of the target is unavailable. Therefore, the existing results for consensus problem of heterogeneous multi-agent based on known exosystem matrix are not applicable. A neural-network-based adaptive observer is designed to estimate the output of the non-cooperative target. Then, a finite-time adaptive fault tolerant controller is developed to address the heterogeneous target tracking problem in the presence of actuator faults. The proposed controller achieves finite-time convergence of tracking errors and is fully distributed, eliminating the need for the system matrix of the target and actuator fault rates of the tracking agents. The effectiveness of the developed strategies and the correctness of achieved stability conditions are verified through numerical examples.
INFORMATION SCIENCES
(2023)
Article
Automation & Control Systems
Wen Li, Yugang Niu, Xinyu Lv
Summary: This paper investigates the consensus problem of a multi-agent system (MAS) under stochastic DoS attacks using a sliding mode control mechanism. A distributed dynamic event-triggered strategy is implemented on the communication path among agents, with dynamic parameters adjusting the event-triggered condition threshold. A distributed sliding mode controller is proposed to ensure the stochastic consensus of the MAS, and a minimization problem is solved to obtain the correct controller gain matrix. The presented results are demonstrated through a numerical example.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2023)
Article
Automation & Control Systems
Jieshuai Wu, Maobin Lu, Fang Deng, Jie Chen
Summary: This article investigates the cooperative robust output regulation problem of multi-agent systems with general linear uncertain dynamics using event-triggered control. In comparison to the practical solution achieved by a distributed event-triggered control law, this study proposes a distributed event-triggered output feedback control law and a class of dynamic event-triggered mechanisms to solve the problem accurately.
INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR CONTROL
(2023)
Article
Mathematics, Applied
Weixun Li, Xiangyang Du, Jingyu Xiao, Limin Zhang
Summary: This paper studies the problem of bipartite hybrid formation tracking for multi-agent systems with heterogeneous groups. The network structure problem of a cluster of agents with both group relationship and cooperation-competition relationship is discussed. A new control protocol based on neighbor information and leader dynamics is designed to solve the problem.
APPLIED MATHEMATICS AND COMPUTATION
(2023)
Article
Engineering, Marine
Kai Xue, Tingyi Wu
Summary: This paper discusses the formation motion control of heterogeneous multi-agent unmanned systems using a distributed consensus approach, considering unmanned aerial vehicles (UAVs) and unmanned surface vehicles (USVs). A fuzzy-based sliding mode control approach is proposed to ensure finite-time formation assembly, with finite-time stability proven by Lyapunov stability theorem. A novel vision-based path re-planning approach is introduced to highlight cooperation within heterogeneous systems like UAVs and USVs.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Jiantao Shi
Summary: This paper investigates the cooperative control problem for a nonlinear leader-follower multi-agent system based on a novel event-triggered scheme to minimize communication between neighboring agents. A Lyapunov-based analysis confirms the bounded convergence of the proposed control algorithm.
IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS II-EXPRESS BRIEFS
(2021)
Article
Automation & Control Systems
Yujie Tang, Zhaolin Ren, Na Li
Summary: We study a class of cooperative multi-agent optimization problems, where the goal is to cooperatively find the joint action profile that minimizes the average of the local costs. We propose a zeroth-order feedback optimization scheme and provide explicit complexity bounds for different scenarios. The algorithm's performance is justified by a numerical example.
Article
Mathematics, Applied
Xi Wang, Yamei Ju, Derui Ding, Hongjian Liu
Summary: This article investigates the cooperative fault-tolerant tracking control for discrete time multi-agent systems with time-varying delays under multiple description encoding schemes. A uniform channel model is proposed to describe the employed encoding scheme subject to packet dropouts. A novel intermediate estimator is designed to estimate system states and a fictitious intermediate variable. Lyapunov stability theory is used to derive sufficient conditions for exponential ultimate boundedness. The gain matrices are obtained using graph feature and singular value decomposition. The effectiveness and superiority of the proposed protocol are demonstrated through simulation examples.
APPLIED MATHEMATICS AND COMPUTATION
(2024)
Article
Automation & Control Systems
Ivica Nakic, Domagoj Tolic, Zoran Tomljanovic, Ivana Palunko
Summary: This article proposes a numerically efficient approach for computing the maximal (or minimal) impact one agent has on the cooperative system it belongs to. It quantifies the agent-to-system impact using H infinity norm and output synchronization as the cooperative control scheme. The approach allows for quick identification of bottlenecks and weak/strong spots in multi-agent systems without intense computations, providing directions for improving communication graph design and selecting cooperative control mechanisms.
JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS
(2022)
Article
Computer Science, Artificial Intelligence
Marina Torres, David A. Pelta, Jose L. Verdegay, Carlos Cruz
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2019)
Article
Green & Sustainable Science & Technology
Gurupada Maity, Sankar Kumar Roy, Jose Luis Verdegay
Article
Computer Science, Artificial Intelligence
Bapi Dutta, Tanima Singha, Mark Goh, Maria Teresa Lamata, Jose-Luis Verdegay
EXPERT SYSTEMS WITH APPLICATIONS
(2019)
Article
Nuclear Science & Technology
Jose-Luis Montes-Tadeo, Raul Perusquia-del-Cueto, David A. Pelta, Juan-Luis Francois, Juan-Jose Ortiz-Servin, Cecilia Martin-del-Campo, Alejandro Castillo
PROGRESS IN NUCLEAR ENERGY
(2020)
Article
Computer Science, Artificial Intelligence
Marina Torres, David A. Pelta, Maria T. Lamata, Ronald R. Yager
Summary: The focus is on selecting a set of interesting solutions based on decision maker's preferences, rather than relying on geometrical features. The proposed a posteriori approach assigns potential score intervals to each solution based on decision maker's preferences, and filters solutions using a possibility degree formula. Three examples with different numbers of objectives showcase the benefits of the proposal.
NEURAL COMPUTING & APPLICATIONS
(2021)
Review
Mathematics
Boris Perez-Canedo, Jose Luis Verdegay, Eduardo Rene Concepcion-Morales, Alejandro Rosete
Article
Computer Science, Artificial Intelligence
Ali Abbaszadeh Sori, Ali Ebrahimnejad, Homayun Motameni, Jose Luis Verdegay
Summary: The important issue of improving transportation in connection with traffic is discussed, focusing on the constrained shortest path (CSP) problem and an efficient algorithm designed to find the optimal path.
INTERNATIONAL JOURNAL OF UNCERTAINTY FUZZINESS AND KNOWLEDGE-BASED SYSTEMS
(2021)
Article
Computer Science, Information Systems
Hanane El Raoui, Mustapha Oudani, David A. Pelta, Ahmed El Hilali Alaoui
Summary: The study introduces a many-objective Customer-centric Perishable Food Distribution Problem and proposes a GVNS-based approach to efficiently solve subproblems and obtain a set of solutions. These solutions are evaluated over non-optimized criteria and ranked using an a posteriori approach, allowing for easy generation of different decision maker profiles and rankings of solutions.
Article
Multidisciplinary Sciences
Hanane El Raoui, Marcelino Cabrera-Cuevas, David A. Pelta
Summary: Optimization problems are prevalent in today's society, often requiring consideration of various characteristics and features of the real world. This paper discusses the important role of metaheuristics as solution generators in a problem-solving framework, as well as how to obtain high-quality solutions.
Article
Computer Science, Information Systems
Cynthia Porras, Boris Perez-Canedo, David A. Pelta, Jose L. Verdegay
Summary: This paper investigates the tourism trip design problem with time-dependent recommendation factors. By solving 27 real-world instances, it is found that including waiting times has little impact on the quality of solutions, and it leads to longer solving times. This highlights the importance of properly evaluating the benefits of making the problem model more complex.
Article
Business
Jose Luis Verdegay, Ma Teresa Lamata, David Pelta, Carlos Cruz
Summary: Computers process information and make decisions, with AI systems achieving levels of decision-making comparable to or exceeding humans. While these Autonomous Decision Systems can enhance efficiency, the potential for replacing humans raises concerns, making avoiding system malfunctions a top priority.
Article
Computer Science, Artificial Intelligence
Boris Perez-Canedo, Cynthia Porras, David A. Pelta, Jose Luis Verdegay
Summary: Decisions made in various fields such as economics, engineering, industry, and medical sciences rely on finding and interpreting solutions to optimization problems. It is important to consider the decision-making context as a filter, along with the natural constraints of the problem, to avoid obtaining optimal but irrelevant solutions. This article proposes a method of modeling contexts using fuzzy propositions and introduces two approaches (a priori and a posteriori) for solving optimization problems under their influence. The results provide researchers and practitioners with a methodology for more effective optimization and decision making.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)