Robust Decentralized Control of Cooperative Multi-robot Systems : An inter-constraint Receding Horizon approach

Abstract: In this work, a robust decentralized model predictive control regime for a team of cooperating robot systems is designed. Their assumed dynamics are in continuous time and non-linear. The problem involves agents whose dynamics are independent of one-another, and its solution couples their constraints as a means of capturing the cooperative behaviour required. Analytical proofs are given to show that, under the proposed control regime: (a) Subject to initial feasibility, the optimization solved at each step by each agent will always be feasible, irrespective of whether or not disturbances affect the agents. In the former case, recursive feasibility is established through successive restriction of each agent's constraints during the periodic solution to its respective optimization problem. (b) Each (sub)system can be stabilized to a desired configuration, either asymptotically when uncertainty is absent, or within a neighbourhood of it, when uncertainty is present, thus attenuating the affecting disturbance. In this context, disturbances are assumed to be additive and bounded. Simulations verify the efficacy of the proposed method over a range of different operating environments.