Amirkabir University of Technology AUT Journal of Modeling and Simulation 2588-2953 55 1 2023 06 01 Robust Distributed ℒasso-Model Predictive Control Design: A Case Study on Large-Scale Multi-Robot Systems 127 138 5251 10.22060/miscj.2023.22087.5312 EN Hossein Ahmadian Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran 0000-0001-6094-8838 Iman Sharifi Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran 0000-0001-7201-9913 Heidar Ali Talebi Department of Electrical Engineering, Amirkabir University of Technology, Tehran, Iran 0000-0001-6038-2109 Journal Article 2023 01 11 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}. https://miscj.aut.ac.ir/article_5251_6fe43269967adbb64ec6149852b5cc3e.pdf