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

TL;DR

This paper introduces a distributed model predictive control algorithm with trajectory prediction for UAVs landing on a moving USV, ensuring robustness to communication failures and collision avoidance.

Contribution

It presents a novel DMPC algorithm with trajectory prediction that maintains coordination during communication losses and proves its convergence.

Findings

Algorithm successfully predicts trajectories during communication loss.

Simulation results confirm the convergence and effectiveness of the control strategy.

The method enhances UAV-USV landing safety and robustness.

Abstract

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