A robust interpolated model predictive control based on recurrent neural networks for a nonholonomic differential-drive mobile robot with quasi-LPV representation: computational complexity and conservatism-Reference-Cited by-同舟云学术

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A robust interpolated model predictive control based on recurrent neural networks for a nonholonomic differential-drive mobile robot with quasi-LPV representation: computational complexity and conservatism

Published:2024-06-28 Issue: Volume: Page:1-15
ISSN:0020-7721
Container-title:International Journal of Systems Science
language:en
Short-container-title:International Journal of Systems Science

Author:

Hadian Mohsen¹,Zhang W. J.¹²,Etesami Danial³

Affiliation:

1. Division of Biomedical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Canada

2. School of Mechanical Engineering, Donghua University, Shanghai, People’s Republic of China (*on sabbatical leave)

3. Department of Mechanical Engineering, College of Engineering, University of Saskatchewan, Saskatoon, Canada

Funder

Natural Sciences and Engineering Research Council of Canada

Collaborative Research and Training Experience

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/00207721.2024.2367711

Reference52 articles.

1. An improved robust model predictive control for linear parameter-varying input-output models

2. Obstacle Avoidance in Real Time With Nonlinear Model Predictive Control of Autonomous Vehicles

3. Abutaleb, A., Alsabhani, J., Alkinani, S., Alkaydi, S., Alghamdi, S., & Bensenouci, A. (2020, March 10–12). Design and implementation of a nurse robot. In Proceedings of the International Conference on Industrial Engineering and Operations Management, Dubai, UAE.

4. Superiority of Nonlinear and Stable MPC in a Differential Mobile Robot: Accuracy and Solving Speed

5. LPV-MPC Control for Autonomous Vehicles

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