Since high complexity and uncertainty is inherent in real-world environments that can influence the strategies choices of agents, we introduce a stochastic perturbation term to characterize the interference caused by uncertain factors on multi-agent...
We investigate a novel nonlinear consensus from the extreme points of doubly stochastic quadratic operators (EDSQO), based on majorization theory and Markov chains for time-varying multi-agent distributed systems. We describe a dynamic system that ha...
This paper investigates the bipartite output feedback tracking control problem for stochastic nonlinear heterogeneous leader-following multi-agent systems under signed communication graphs, where multiplicative measurement noise exists in information...
In this paper, the fixed-time control for high-order nonlinear multi-agent systems under unknown stochastic time delay is investigated via an event-triggered approach. First of all, RBF neural networks are utilized to approximate the system’s u...
Fractional differential equations, which are non-local and can better describe memory and genetic properties, are widely used to describe various physical, chemical, and biological phenomena. Therefore, the multi-agent systems based on discrete-time...
This paper investigates the cluster-delay mean square consensus problem of a class of first-order nonlinear stochastic multi-agent systems with impulse time windows. Specifically, on the one hand, we have applied a discrete control mechanism (i.e., i...
This paper is concerned with the leader-following consensus of time-delay multi-agent systems (MASs) with stochastic perturbation over a directed network. Different from existing literature subject to the conventional Lipschitz condition, the one-sid...
An adaptive neural network output-feedback control strategy is proposed in this paper for the distributed optimization problem (DOP) of high-order nonlinear stochastic multi-agent systems (MASs) driven by Lévy noise. On the basis of the penalt...
This paper investigates the problem of finite-time distributed consensus control for non-triangular stochastic nonlinear multi-agent systems (SNMASs) with input constraints. Fuzzy logical systems are used to identify the unknown nonlinear dynamics of...
The consensus problem in stochastic multi-agent systems (MASs) with Markovian switching is addressed by proposing a novel distributed dynamic event-triggered (DDET) technique based on periodic sampling to reduce information transmission. Unlike tradi...
This paper investigates the event-triggered secure consensus problem for stochastic multi-agent systems (MASs) subject to bilateral false data injection attacks (FDIAs). To achieve reliable secure consensus while reducing resource consumption, an eve...
This paper studies the leaderless consensus of the stochastic multi-agent systems based on partial differential equations–ordinary differential equations (PDE-ODEs). Compared with the traditional state coupling, the most significant difference...
This paper investigates the leader-following mean-square consensus of stochastic linear multi-agent systems (MASs) via distributed impulsive control. A distributed impulsive control law relying on local neighbor information and discrete sampled data...
This article explores nonlinear convergence to limit the effects of the consensus problem that usually occurs in multi-agent systems. Most of the existing research essentially considers the outline of linear protocols, using complex mathematical equa...
This paper presents a two-stage hybrid stochastic–robust coordination of energy management and self-healing in smart distribution networks with multiple microgrids. A multi-agent systems approach is first used for coupling energy management and...
The multi-agent-based supply chain network is a dynamic system consisting of multiple subchains connected by information flows, material flows and capital flow, etc. The consensus of multi-agent systems is often applied to the cooperation between sub...
This paper focuses primarily on the mean square consensus problem of a class of nonlinear multi-agent systems suffering from stochastic impulsive deception attacks. The attacks here are modeled by completely stochastic destabilizing impulses, where t...
A distributed nonfragile controller is developed for stochastic delayed multi-agent systems in which nonlinear terms, plant uncertainties, and gain perturbations are activated randomly. The directed topology is assumed to admit a spanning tree whose...
The article considers the problem of finding the optimal on average control of the trajectories of continuous stochastic systems with incomplete feedback. This class of problems includes control problems in which the initial states are described by a...
This paper proposes the fixed-time prescribed performance optimal consensus control method for stochastic nonlinear multi-agent systems with sensor faults. The consensus error converges to the prescribed performance bounds in fixed-time by an improve...
This paper addresses the communication issue encountered by a hybrid controller when finding consensus in terms of the rendezvous target point in a broadcast and communication environment. This issue may result in a high level of computation and the...
Cyber–Physical Systems (CPS), including smart grids and industrial control networks, must maintain secure and stable operations despite increasingly adaptive cyber threats. Existing moving target defense (MTD) approaches often rely on fixed rec...
Utilizing fully distributed intelligent control algorithms has enabled the gradual adoption of the multiple unmanned aerial vehicles system for executing Target Tracking and Encirclement missions in industrial and civil applications. Restricted by th...
For the multi-agent system with time delay and noise, the adaptive consensus of tracking control problems is discussed by the Lyapunov function. The main purpose of this study is to design an adaptive control protocol for the system, such that even i...
This paper focuses on the development of a multi agent control system (MACS), combined with a stochastic based approach for occupancy estimation. The control framework aims to maintain the comfort levels of a building in high levels and reduce the ov...
The current paper deals with the containment control issue of fractional-order complex networks (FCNs) under communication uncertainties occurring with both multiplicative and additive noises and denial-of-service attacks. The dynamics of the followe...
An algorithm for synchronization of a network composed of interconnected Hindmarsh–Rose neurons is presented. Delays are present in the interconnections of the neurons. Noise is added to the controlled input of the neurons. The synchronization algori...
The paper considers the detection of multiple targets by a group of mobile robots that perform under uncertainty. The agents are equipped with sensors with positive and non-negligible probabilities of detecting the targets at different distances. The...
Decentralized stochastic control (DSC) is a stochastic optimal control problem consisting of multiple controllers. DSC assumes that each controller is unable to accurately observe the target system and the other controllers. This setup results in two...
Due to its significant importance in many disciplines, distributed optimization under uncertainty has become an active research field over the past decade. This paper presents a cross-paradigm review of this development. We organize the literature ar...
Static risk analysis techniques (SRATs) use event graphs and risk analysis assessment models. Those techniques are not time-based techniques and hence are inadequate to model dynamic stochastic systems. This paper proposes a novel dynamic approach to...
The paper presents an
In this paper, the discrete-time version of a continuous-time model with fundamentalists and momentum traders is presented. Our aim consists of studying the impact of cross-sectional momentum traders on the dynamics of the model. To this end, the con...
In this paper, the adaptive consensus problem of unknown non-linear multi-agent systems (MAs) with communication noises under Markov switching topologies is studied. Based on the adaptive control theory, a novel distributed control protocol for non-l...
This paper provides a survey of the literature on the application of Multi-agent Systems (MAS) technology for Smartgrids. Smartgrids represent the next generation electric network, as communities are developing self-sufficient and environmentally fri...
Based on an adaptive neural control scheme, this paper investigates the consensus problem of random Markov jump multi-agent systems with full state constraints. Each agent is described by the fractional-order random nonlinear uncertain system driven...
Coordinating agents in dynamic and uncertain environments remains a fundamental challenge in multi-agent systems (MAS) research, particularly in contexts where the composition of agent organizations directly affects overall system performance. While...
The increasing frequency and intensity of wildfires has created an urgent demand for scalable and autonomous wildfire response systems. While recent advances in multi-agent reinforcement learning (MARL) have demonstrated promise for collaborative unc...
Electric vehicles (EVs) are a sustainable transportation solution with environmental benefits and energy efficiency. However, their popularity has raised challenges in locating appropriate charging stations, especially in cities with limited infrastr...
The increasing penetration of distributed renewable energy sources and electric vehicles (EVs) introduces significant operational challenges for residential energy management systems (HEMS), including stochastic renewable generation, uncertain load d...
Biological systems, ranging from ant colonies to neural ecosystems, exhibit remarkable self-organizing intelligence. Inspired by these phenomena, this study investigates how bio-inspired computing principles can bridge game-theoretic rationality and...
Stochastic dynamic programming (SDP) is a widely-used method for reservoir operations optimization under uncertainty but suffers from the dual curses of dimensionality and modeling. Reinforcement learning (RL), a simulation-based stochastic optimizat...
In this study, we propose an innovative approach to address a chronological planning problem involving the multiple agents required to complete tasks under precedence constraints. We model this problem as a stochastic game and solve it with multi-age...
Device-to-device (D2D) is a pivotal technology in the next generation of communication, allowing for direct task offloading between mobile devices (MDs) to improve the efficient utilization of idle resources. This paper proposes a novel algorithm for...
Multi-population mean-field game is a critical subclass of mean-field games (MFGs). It is a theoretically feasible multi-agent model for simulating and analyzing the game between multiple heterogeneous populations of interacting massive agents. Due t...
This paper presents a solution to the consensus problem for a particular category of uncertain switched multi-agent systems (MASs). In these systems, the communication topologies between agents and the system dynamics are governed by a time-homogeneo...
The paper investigates
Natural disasters cause significant losses. Unmanned aerial vehicles (UAVs) are valuable in rescue missions but need to offload tasks to edge servers due to their limited computing power and battery life. This study proposes a task offloading decisio...
The cooperative control problem of discrete-time multi-agent systems (MASs) is discussed, and bounded uncertain time-delays and directed switching topologies are considered. By applying model transformations and matrix theory, an augmented system met...
The growing complexity of distributed energy systems and the rise of peer-to-peer energy markets demand innovative solutions for efficient, resilient, and sustainable energy management. However, existing research often remains fragmented, with limite...
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