Model Predictive Control Schemes for Consensus in Multi-Agent Systems with Single- and Double-Integrator Dynamics

被引：206

作者：

Ferrari-Trecate, Giancarlo ^{[1
]}

Galbusera, Luca ^{[2
]}

Marciandi, Marco Pietro Enrico ^{[3
]}

Scattolini, Riccardo ^{[2
]}

机构：

[1] Univ Pavia, Dipartimento Informat & Sistemist, I-27100 Pavia, Italy

[2] Politecn Milan, Dipartimento Elettr & Informaz, I-20133 Milan, Italy

[3] CESI Ric Spa, I-20134 Milan, Italy

来源：

IEEE TRANSACTIONS ON AUTOMATIC CONTROL | 2009年 / 54卷 / 11期

关键词：

Consensus problems; decentralized model predictive control (MPC); networked autonomous agents; MOBILE AUTONOMOUS AGENTS; RECEDING HORIZON CONTROL; COORDINATION; STABILITY; NETWORKS;

D O I：

10.1109/TAC.2009.2031208

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

In this paper, we address the problem of driving a group of agents towards a consensus point when the agents have a discrete-time single- or double-integrator dynamics and the communication network is time-varying. We propose decentralized model predictive control schemes that take into account constraints on the agents' input and show that they guarantee consensus under mild assumptions. Since the global cost does not decrease monotonically, it cannot be used as a Lyapunov function for proving convergence to consensus. For this reason, our proofs exploit geometric properties of the optimal path followed by individual agents.

引用

页码：2560 / 2572

页数：13

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