Laguerre Function-Based Robust Model Predictive Control With Shrinking Horizon for Cooperative Rendezvous

Abstract Cooperative rendezvous of a fixed-wing unmanned aerial vehicle (UAV) and a moving platform is a challenging and significant issue, where environmental disturbances, computational load, and time-varying rendezvous points remain the prevalent challenges. Aiming at the stabilizing control of the fixed-wing UAV under the disturbed environment, a Gaussian process (GP)-based robust model predictive control with Laguerre functions and shrinking horizon strategy is proposed. Firstly, a new online Gaussian process prediction method is developed to predict the future trajectory of the moving platform. Then, a robust control scheme is designed to compensate for the effect of bounded disturbances on the UAV. Furthermore, to decrease the computational load of solving the optimization problem in real-time, a novel prediction horizon update strategy and Laguerre functions are developed. Finally, the reliability and effectiveness of the proposed algorithm are verified by the joint experiment results. Compared with the existing approaches, the proposed method achieves a 30.33% reduction in computational load.