Distributed Real-Time Non-Linear Receding Horizon Control Methodology for Multi-Agent Consensus Problems
For researchers in multi-agent systems, this provides a non-iterative, linearization-free approach to nonlinear consensus, but the novelty is incremental as it adapts existing control techniques.
This work develops a distributed real-time nonlinear receding horizon control method for multi-agent consensus problems, converting consensus into an optimization problem solved by a non-iterative backwards sweep Riccati method, with stability guarantees and leader-following extension. Examples validate the scheme's effectiveness.
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.