Non-linear dual-mode receding horizon control for multiple unmanned air vehicles formation flight based on chaotic particle swarm optimisation

This study presents a non-linear dual-mode receding horizon control (RHC) approach to investigate the formation flight problem for multiple unmanned air vehicles (UAVs) under complicated environments. A chaotic particle swarm optimisation (PSO)-based non-linear dual-mode RHC method is proposed for solving the constrained non-linear systems. The presented chaotic PSO derives both formation model and its parameter values, and the control sequence is predicted in this way, which can also guarantee the global convergence speed. A dual-model control strategy is used to improve the stability and feasibility for multiple UAVs formation flight controller, and the state-feedback control is also adopted, where the model is based on the invariant set theory. Series experimental results show the feasibility and validity of the proposed control algorithm over other algorithms. The proposed approach is also a promising control strategy in solving other complicated real-world problems.

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