Distributed Real-Time Non-Linear Receding Horizon Control Methodology for Multi-Agent Consensus Problems

TL;DR

This paper introduces a distributed real-time nonlinear receding horizon control approach for multi-agent systems that achieves consensus without linearization, using a non-iterative optimization method with proven stability.

Contribution

It presents a novel non-linear receding horizon control scheme for multi-agent consensus that avoids linearization and guarantees convergence through stability analysis.

Findings

Successfully achieves consensus in nonlinear multi-agent systems.

Provides a non-iterative control algorithm based on Riccati equations.

Validates effectiveness through multiple simulation examples.

Abstract

This work investigates the consensus problem for multi-agent nonlinear systems through the distributed real-time nonlinear receding horizon control methodology. With this work, we develop a scheme to reach the consensus for nonlinear multi agent systems under fixed directed/undirected graph(s) without the need of any linearization techniques. For this purpose, the problem of consensus is converted into an optimization problem and is directly solved by the backwards sweep Riccati method to generate the control protocol which results in a non-iterative algorithm. Stability analysis is conducted to provide convergence guarantees of proposed scheme. In addition, an extension to the leader-following consensus of nonlinear multi-agent systems is presented. Several examples are provided to validate and demonstrate the effectiveness of the presented scheme and the corresponding theoretical results.