Real-time Distributed MPC for Multiple Underwater Vehicles with Limited Communication Data-rates
Yujia Yang, Ye Wang, Chris G. Manzie, Ye Pu · 2021
Controlling a fleet of autonomous underwater vehicles can be challenging due to low data-rate communication between agents. This paper proposes a real-time framework with an optimally designed progressive quantization scheme to addresses this challenge. The proposed framework consists of two stages: an off-line stage where the optimal quantization design is obtained considering the limited data-rate, i.e., a limited number of bits transmitted per time step; and an on-line stage based on a distributed model predictive control formulation and a distributed optimization algorithm with progressive quantization. Recursive feasibility and stability of the closed-loop systems are analyzed, and simulations are used to demonstrate the proposed approach, as well as the theoretical findings.