This paper investigates a class of multi-agent systems (MASs) governed by nonlinear fractional-order space-varying partial integro-differential equations (SVPIDEs), which incorporate both nonlinear state terms and integro terms. Firstly, a distributed adaptive control protocol is developed for leaderless fractional-order SVPIDE-based MASs, aiming t...
Analyzing IoT data is an important challenge in the smart cities domain due to the complexity of network traffic generated by a large number of interconnected devices: smart cameras, light bulbs, motion sensors, voice assistants, and so on. To overcome this issue, a multi-agent system is proposed to deal with all machine learning steps, from prepro...
Unmanned aerial vehicles (UAVs), commonly known as drones, are being seen as the most promising type of autonomous vehicles in the context of intelligent transportation system (ITS) technology. A key enabling factor for the current development of ITS technology based on autonomous vehicles is the task allocation architecture. This approach allows t...
The logistics and transportation sectors are struggling to manage empty containers (ECs), resulting in unused resources, inefficiencies, and increased CO2 emissions. The Physical Internet (PI) concept provides an opportunity to improve container sharing and transportation by intelligently organising logistics resources. This paper shows how PI prin...
Given the accelerating global movement towards decarbonization, the importance of promoting renewable energy (RE) adoption and ensuring efficient transactions in energy markets is increasing worldwide. However, renewable energy sources, including photovoltaic (PV) systems, are subject to output fluctuations due to weather conditions, requiring larg...
Accurately predicting the long-term trajectories of agents in complex traffic environments is crucial for the safety and effectiveness of autonomous driving systems. This paper introduces DBN-MACTraj, a probabilistic model that takes historical trajectories and surrounding lane information as inputs to generate a distribution of predicted trajector...
In recent years, agent-based simulations have become increasingly popular in geography, with various platforms available to build spatially focused multi-agent models. Each platform has its own way of integrating geographical data and dealing with geographical phenomena but GAMA is particularly well-suited for the management of data from the Geogra...
Control in multi-agent decision-making systems is an important issue with a wide variety of existing approaches. In this work, we offer a new comprehensive framework for distributed control. The main contributions of this paper are summarized as follows. First, we propose PHIMEC (physics-informed meta control)—an architecture for learning optimal c...
The Internet of Things (IoT) enables smart devices to connect, share and exchange data with each other through the internet. Since an IoT environment is open and dynamic, IoT participants may need to collaborate with unknown entities with no proven track record. To ensure successful collaboration among these entities, it is important to establish a...
Finite-time consensus problem of hybrid-order heterogeneous multi-agent systems under a signed digraph topology is investigated in this paper. For heterogeneous multi-agent systems composed of first-order and second-order agents, a novel pinning event-triggered control protocol is devised to facilitate the attainment of the desired consensus state ...
