Large civil aircraft receding horizon control based on Cauthy mutation pigeon inspired optimization

Abstract

Multi-control surfaces controlled by advanced control methods can improve the safety and reliability of large civil aircraft effectively. An on-line optimization algorithm named Cauthy mutation pigeon inspired optimization (CMPIO) is proposed in this paper to solve the receding horizon control (RHC) problem. CMPIO preserves the obvious advantage of pigeon inspired optimization (PIO), which has fast convergence rate. Besides, CMPIO not only reduces the probability of optimization results trapping into local optimum, but enhances the rapidity and reliability of RHC by utilizing the map and compass operator and landmark operator improved by Cauthy mutation. In the simulations of coordinated turn and fault reconstruction in coordinated turn, it is shown that the large civil aircraft reaches reference state quickly and stably in RHC based on CMPIO. Meanwhile, controller completes the control allocation of multiple-control surfaces legitimately.