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In this paper we propose a novel distributed model predictive control (DMPC)based algorithm with a trajectory predictor for a scenario of landing ofunmanned aerial vehicles (UAVs) on a moving unmanned surface vehicle (USV). Thealgorithm is executing DMPC with exchange of trajectories between the agents ata sufficient rate. In the case of loss of communication, and given the sensorsetup, agents are predicting the trajectories of other agents based on theavailable measurements and prior information. The predictions are then used asthe reference inputs to DMPC. During the landing, the followers are tasked withavoidance of USV-dependent obstacles and inter-agent collisions. In theproposed distributed algorithm, all agents solve their local optimizationproblem in parallel and we prove the convergence of the proposed algorithm.Finally, the simulation results support the theoretical findings.

Prediction-Based Leader-Follower Rendezvous Model Predictive Control with Robustness to Communication Losses