Dynamics modeling and trajectory optimization for unmanned aerial-aquatic vehicle diving into the water

Unmanned aerial-aquatic vehicle (UAAV) is a new type of aircraft that can navigate both in air and underwater. Considering that the diving motion of UAAV plays an important role in the performance of UAAV and is under exploration, the dynamics modeling and trajectory optimization problem are studied in this paper. The UAAV model used in this study is introduced firstly, and folded wings are adopted to reduce the drag in the diving process. Among the forces imposed on UAAV, fluid force is the most complicated and is calculated by the forces induced by ideal fluid and viscous fluid respectively. Based on the established dynamic model, the diving process is regarded as a free motion to avoid the instability during the control switch between air and water. Therefore, the trajectory of UAAV is determined by the initial states of diving process. To obtain the satisfactory trajectory under certain optimization index, an adaptive and global-best guided CS algorithm, named as improved cuckoo search (ICS) algorithm, is developed to strength the exploitation ability and search efficiency. Simulation results demonstrate that the established dynamical model of UAAV is rational and can reflect the characteristic of the diving motion. The proposed ICS algorithm performs better than the particle swarm optimization (PSO) algorithm and the standard CS algorithm both in optimizing the elapsed time of diving process and the terminal position error.