Adaptive Differential Evolution-Based Distributed Model Predictive Control for Multi-UAV Formation Flight

The complicated formation flight for multi-unmanned aerial vehicles is a challenge, especially when multi-mission requirements are taken into account. This paper studies the adaptive differential evolution-based distributed model predictive control approach to deal with the multi-unmanned aerial vehicle flight achieving obstacle/collision avoidance and formation keeping simultaneously in the complex environment. Specifically, the distributed model predictive controller is designed to achieve stable flight for each unmanned aerial vehicle as well as taking the state and input saturation into account, where the local optimization problem is solved by the adaptive differential evolution algorithm. Besides, the adaptive adjustment to the prediction horizon for the model predictive controller is introduced, while the asymptotic convergence of the rolling optimization is analyzed as well. Finally, simulation examples are provided to illustrate the validity of the proposed control structure.