Distributed fault tolerant control and estimation for leader-follower consensus of multi-agent systems with actuator faults

Khodabandeh, Sepehr; Shishavan, Hamed Kharrati; Hashemzadeh, Farzad

doi:10.1109/kbei.2017.8324920

Cited by 2 publications

(1 citation statement)

References 7 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…e multiple mobile robots also enhance the fault tolerance and robustness of the system and strengthen the ability of robots' environment recognition. Comparing with the leader-follower method [5][6][7][8], behavior-based method [9][10][11],and virtual structure method [12,13], the model predictive control (MPC) has attracted attention because of its ability of improving the robustness of the system and having better dynamic control performance in solving the problem of consensus protocol in distributed formation control of multiple mobile robots. Also, MPC is convenient to establish the system model.…”

Section: Introductionmentioning

confidence: 99%

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

Shang

Zhu

Pan

et al. 2021

Discrete Dynamics in Nature and Society

View full text Add to dashboard Cite

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.

show abstract