Robust Distributed ℒasso-Model Predictive Control Design: A Case Study on Large-Scale Multi-Robot Systems

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}.