Robust Distributed ℒasso-Model Predictive Control Design: A Case Study on Large-Scale Multi-Robot Systems | ||
| AUT Journal of Modeling and Simulation | ||
| دوره 55، شماره 1، شهریور 2023، صفحه 127-138 اصل مقاله (1.08 M) | ||
| نوع مقاله: Research Article | ||
| شناسه دیجیتال (DOI): 10.22060/miscj.2023.22087.5312 | ||
| نویسندگان | ||
| Hossein Ahmadian؛ Iman Sharifi* ؛ Heidar Ali Talebi | ||
| Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran | ||
| چکیده | ||
| The complexity and dynamic order of large-scale systems is continuously increasing. Considering the many challenges that exist for these systems, it is very important to provide a robust distributed controller that performs well against uncertainties, computation volume, and interaction between subsystems. A robust-distributed ℒasso-MPC (RD-LMPC) approach is suggested in this study for multi-robot systems in the presence of polytopic uncertainty. In addition, a distributed Kalman filter is used to capture interactions between subsystems. To evaluate and perform the effectiveness of the suggested approach, the results obtained on the multi-robot system are compared with the results of the predictive control methods of the centralized, distributed model, and L1 adaptive control}. | ||
| کلیدواژهها | ||
| Distributed MPC؛ Large Scale Multi-Robot Systems؛ ℒasso Regression؛ ℒasso- MPC؛ Model Predictive Control (MPC)؛ Robust MPC | ||
| مراجع | ||
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