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}.