Asynchronous Communication under Reliable and Unreliable Network Topologies in Distributed Multiagent Systems: A Robust Technique for Computing Average Consensus

Nearly all applications in multiagent systems demand precision, robustness, consistency, and rapid convergence in designing of distributed consensus algorithms. Keeping this thing in our sight, this research suggests a robust consensus protocol for distributed multiagent networks, continuing asynchronous communications, where agent’s states values are updated at diverse interval of time. This paper presents an asynchronous communication for both reliable and unreliable network topologies. The primary goal is to delineate local control inputs to attain time synchronization by processing the update information received by the agents associated in a communication topology. Additionally in order to accomplish the robust convergence, modelling of convergence analysis is conceded by commissioning the basic principles of graph and matrix theory alongside the suitable lemmas. Moreover, statistical examples presenting four diverse scenarios are provided in the end; produced results are the recognisable indicator to authenticate the robust effectiveness of the proposed algorithm. Likewise, a simulation comparison of the projected algorithm with the other existing approaches is conducted, considering different performance parameters are being carried out to support our claim

Beacon-based Distributed Structure Formation in Multi-agent Systems

Autonomous shape and structure formation is an important problem in the domain of large-scale multi-agent systems. In this paper, we propose a 3D structure representation method and a distributed structure formation strategy where settled agents guide free moving agents to a prescribed location to settle in the structure. Agents at the structure formation frontier looking for neighbors to settle act as beacons, generating a surface gradient throughout the formed structure propagated by settled agents. Free-moving agents follow the surface gradient along the formed structure surface to the formation frontier, where they eventually reach the closest beacon and settle to continue the structure formation following a local bidding process. Agent behavior is governed by a finite state machine implementation, along with potential field-based motion control laws. We also discuss appropriate rules for recovering from stagnation points. Simulation experiments are presented to show planar and 3D structure formations with continuous and discontinuous boundary/surfaces, which validate the proposed strategy, followed by a scalability analysis.Comment: 8 pages, 6 figures, accepted for publication in IROS 2023. A link to the simulation videos is provided under the Validation sectio

Computationally efficient robust model predictive control strategies for linear constrained systems

This thesis deals with control problem of designing low computationally demanding robust model predictive controllers (MPC) for constrained systems subject to states/input limitations and bounded disturbances. In particular, the proposed solutions are based on a dual-mode control paradigm known as Set-Theoretic MPC (ST-MPC). This control schemes are particularly appealing for their capability of reducing the typical computation burden of robust MPC controllers. The latter is obtained by moving most of the required computations into an off-line phase, while leaving a simple and real-time affordable computational algorithm in the on-line phase. In this work, such a paradigm has been properly extended to deal with regulation and tracking problems appearing in two different control applications, namely transient stability regulation in smart grid and reference tracking in multi autonomous vehicles. In the transient stability control problem, we consider an operative scenario where a physical fault or a cyber-attack produces an impulsive state perturbation, and a controller must be designed to robustly recover, in a finite-time, transient stability despite initial perturbation and uncertainties. In such scenario, first we have used the standard feedback linearizion technicalities to linearize the smart grid model, then, we have applied a set-theoretic MPC scheme to robustly regulate the state trajectory towards the transient stability region. Moreover, to validate the proposed theory, a simulation campaign has been performed to contrast the proposed solution with a state-of-the-art competitor. Simulation results has shown that the proposed strategy outperforms the competitor scheme both in terms of settling time and robustness. In the multi-vehicle control problem, we exploit set-theoretic arguments to solve the reference tracking problem when the vehicles have different dynamics and/or constraints and/or disturbance, and each vehicle must follow uncoordinated reference trajectories. More in specific, we propose a novel control architecture where robust collision-free reference tracking is ensured by jointly using the set-theoretic control scheme and graph theory. To better clarify the potential and effectiveness of the proposed architecture, a simulation example involving 5 heterogeneous vehicles has been conducted