This study presents distributed event‐based control strategies for a networked dynamical system consisting of N linear time‐invariant interconnected subsystems. Each subsystem broadcasts its state over the network according to certain triggering rules that only depend on local information. The system can converge asymptotically to the equilibrium point under the proposed control design, and the existence of a lower bound for the broadcasting period is guaranteed. A novel model‐based approach is derived to reduce the communication between the agents. Simulation results show the effectiveness of the proposed approaches and illustrate the theoretical results.

This work presents the development of a distributed formation control for multiagent systems (MASs) using a fractional-order proportional–integral (FOPI) structure. The fractional control protocol proposed is evaluated on agents modeled with single- and double-integrator dynamics, in which it enhances the convergence speed of the formation and improves the robustness of the system. In addition, a novel method to study the stability and convergence of the MASs in the frequency domain is designed. This allows deriving constraints on the control parameters to guarantee the stability and ensure the formation when the system topology is modeled by a time-invariant undirected graph. Finally, realistic simulations through MATLAB and a Virtual Robot Experimentation Platform (V-REP) validate the effectiveness of the theoretical results.

Multi-agent system research is a hot topic in different application domains. In robotics, multi-agent robot systems (MRS) can realize complex tasks even if the behavior of each individual agent seems simple thanks to the cooperation between them. Although many control algorithms for MRS are proposed, few experimental results are validated on real data, being essential to building new testbeds to conduct MRS research and teaching. Moreover, most existing platforms for experimentation do not offer an overall solution allowing software and hardware design tools. This paper describes the design and operation of Robotic Park, a new indoor experimental platform for research in multi-agent systems. The heterogeneity and flexibility of its configuration are two of its main features. It supports control strategies design and validation of MRS algorithms. Experiences can be carried out in a virtual environment, in a physical environment, or under a hybrid scheme, as digital twins have been developed in Gazebo and Webots. Currently, two types of aerial vehicles, the Crazyflie 2.X and the DJI Tello, are available. It also includes two types of differential mobile robots, the Turtlebot3 and the Khepera IV. Both internal and external positioning systems using different technologies such as Motion Capture or Ultra-WideBand are also available for experiences. All components are connected through ROS2 (Robot Operating System 2) which enables experiences under a centralized, distributed, or hybrid scheme, and different communication strategies can be implemented. A mixed reality experience that addresses the problem of formation control using event-based control illustrates the platform usage.

An experimental platform to communicate between a set of mobile robots through a wireless network has been developed. The mobile robots get their position through a camera which performs as sensor. The video images are processed in a PC and a Waspmote card sends the corresponding position to each robot using the ZigBee standard. A distributed control algorithm based on event-triggered communications has been designed and implemented to bring the robots into the desired formation. Each robot communicates to its neighbors only at event times. Furthermore, a simulation tool has been developed to design and perform experiments with the system. An example of usage is presented.