A Distributed Model Predictive Control for Multiple Mobile Robots with the Model Uncertainty

In this paper, a distributed predictive control with the model uncertainty which uses the data-driven strategy and robust theory (data-driven RDMPC) is proposed for the formation control of multiple mobile robots. The robust performance objective minimization is applied to replace the quadratic perf...

Full description

Saved in:
Bibliographic Details
Published inDiscrete dynamics in nature and society Vol. 2021; pp. 1 - 22
Main Authors Shang, Wei, Zhu, Hanzong, Pan, Yurong, Li, Xiuhong, Zhang, Daode
Format Journal Article
LanguageEnglish
Published New York Hindawi 21.06.2021
John Wiley & Sons, Inc
Hindawi Limited
Subjects
Analysis
Computer networks
Control algorithms
Controllers
Design
Efficiency
Fault tolerance
Optimization
Predictive control
Robot control
Robotics
Robotics industry
Robots
Robustness
Stability analysis
Uncertainty
Iran
Online AccessGet full text

Cover

More Information
Summary:In this paper, a distributed predictive control with the model uncertainty which uses the data-driven strategy and robust theory (data-driven RDMPC) is proposed for the formation control of multiple mobile robots. The robust performance objective minimization is applied to replace the quadratic performance objective minimization to establish the optimization problem, where the model uncertainty is considered in the distributed system. The control policy is derived by applying the data-driven strategy, and the future predictive value is obtained by employing the linear law in the historical data. Lyapunov theory is referred to analyze the stability of the mobile robot formation system. The effectiveness of the proposed method is proved by a set of simulation experiments.
ISSN:1026-0226
1607-887X
DOI:10.1155/2021/9923496