Formation and Trajectory Tracking of Mobile Robots with Uncertainties and Disturbances Using an Adaptive Immune Fuzzy Quasi-Sliding Mode Control-Reference-Cited by-同舟云学术

Formation and Trajectory Tracking of Mobile Robots with Uncertainties and Disturbances Using an Adaptive Immune Fuzzy Quasi-Sliding Mode Control

Published:2024-05-01 Issue:3 Volume:35 Page:440-460
ISSN:2195-3880
Container-title:Journal of Control, Automation and Electrical Systems
language:en
Short-container-title:J Control Autom Electr Syst

Author:

Goto Willy John Nakamura,Bertol Douglas Wildgrube,Martins Nardênio Almeida^ORCID

Funder

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s40313-024-01089-7.pdf

Reference66 articles.

1. Andaluz, G. M., Leica, P., Herrera, M., et al. (2022). Hybrid controller based on null space and consensus algorithms for mobile robot formation. Emerging Science Journal, 6(3), 429–447.

2. Azar, A. T., & Zhu, Q. (2015). Advances and applications in sliding mode control systems. Springer. https://doi.org/10.1007/978-3-319-11173-5

3. Begnini, M., Bertol, D. W., & Martins, N. A. (2017). A robust adaptive fuzzy variable structure tracking control for the wheeled mobile robot: Simulation and experimental results. Control Engineering Practice, 64, 27–43. https://doi.org/10.1016/j.conengprac.2017.04.006

4. Bouchebbat, R. (2014). Design and application of fuzzy immune PID control based on genetic optimization. In International workshop on advanced control IWAC (pp. 10–14).

5. Bouchebbat, R., & Gherbi, S. (2017). Design and application of fuzzy immune PID adaptive control based on particle swarm optimization in thermal power plants. In 2017 6th international conference on systems and control (ICSC) (pp. 33–38). IEEE. https://doi.org/10.1109/ICoSC.2017.7958656