Estimator-Based Dual-Model Predictive Control for Multi-AAVs With Connectivity-Preserving

This paper investigates a distributed control problem for maintaining connectivity and avoiding collisions among multiple autonomous aerial vehicles (AAVs). A novel distributed estimator is proposed for AAVs. The following AAVs utilize information from their neighbors to estimate the output information of all AAVs. By incorporating a connectivity maintenance function and a collision-free potential field function, the following AAVs avoid collisions with each other and obstacles while maintaining network connectivity. A dual-model predictive control (dual-MPC) algorithm for AAVs, referred to as outer-loop and inner-loop model predictive control optimization, is designed to quickly track the leading AAV. Stability and feasibility of the dual-MPC algorithm can be ensured by uniting rolling optimization with fuzzy logic systems. Finally, the simulation results confirm the effectiveness of the proposed controller.