Distributed model predictive control for consensus of sampled-data multi-agent systems with double-integrator dynamics

作者：Zhou, Lifeng; Li, Shaoyuan^*

来源：IET Control Theory and Applications, 2015, 9(12): 1774-1780.

DOI：10.1049/iet-cta.2014.1357

• Consensus strategy
• Distributed Model predictive Control
• Distributed MPC
• Double-integrator dynamics
• Iterative algorithm
• Optimisations
• Receding horizon
• Sampling period

This study proposes a distributed model predictive control (MPC) strategy to achieve consensus of sampled-data multi-agent systems with double-integrator dynamics. On the basis of the error of state between each agent and the centre of its subsystem, a novel distributed MPC strategy (Algorithm 1) is obtained with the exchange of current states only. Then, a reverse iterative algorithm (Algorithm 2) is specially designed for the receding horizon optimisation of sampled-data double-integrator dynamics. Illustrative examples are finally displayed to verify the effectiveness and advantage of the distributed MPC consensus strategy and the impact of sampling period on consensus.

• 出版日期2015-8-6
• 单位上海交通大学