Lateral automatic carrier landing control based on expanded pigeon inspired optimization

Carrier landing of unmanned aerial vehicles (UAV) can be disturbed by carrier air wake and deck motion. To improve the response speed and disturbance rejection ability of UAV carrier landing, this paper proposes an explicit model predictive control method based on expanded pigeon inspired optimization (EPIO), and apply it in the design of carrier attitude controler to solve parameter optimization problem of the designed controler. Simulations and comparative experiments are conducted on the proposed basic pigeon inspired optimization algorithm and the particle swarm optimization algorithm, which show quicker rate of convergence, stronger universality and stability of EPIO. The designed control method is verified to be faster and more robust after compared with the proportional-integral-derivative control method.