A Multi-Mechanism Pigeon-Inspired Optimization Algorithm for Aircraft Longitudinal Control Augmentation System Design

In this paper, a bionic heuristic approach for control augmentation system (CAS) design is proposed to attain better handling qualities in longitudinal channel. Since manual parameter tuning for control parameters is regarded as a time-consuming task, the CAS design procedure can be converted to an optimization problem. A novel algorithm for searching optimal controlling parameters is presented on the basis of pigeon-inspired optimization (PIO) algorithm, through introducing three mechanisms, including self-learning strategy, competitive exploration behavior, and Cauchy mutation. In addition, two typical optimization algorithms are implemented on designing the CAS for comparison. The experiments are carried out on the longitudinal CAS design for F-16 aircraft. Series of comparative results demonstrate that the proposed algorithm can guarantee desirable handling quality.