Wenyang Gan, Daqi Zhu, and Simon X. Yang
Unmanned underwater vehicle, trajectory tracking, quantum-behaved particle swarm optimization, model predictive control, speed jump phenomenon, trajectory planner
To solve the speed jump problem of trajectory tracking for the unmanned underwater vehicle (UUV), a novel controller based on the model predictive control (MPC) algorithm combined with quantum-behaved particle swarm optimization (QPSO) is presented for a three-dimensional underwater environment in this paper. First, the kinematic model of UUV is applied to build the linear error model. Then, the trajectory tracking controller based on model prediction, rolling optimization and feedback correction is discussed. The control sequence can be obtained by QPSO, which is under the circumstance of satisfying speed constraints. Moreover, based on QPSO–MPC, a trajectory planner is designed for generating the unknown reference trajectory. The simulation cases demonstrate that the presented method can availably solve the speed jump problem for UUV tracking control existing in the backstepping control method. At the same time, the proposed algorithm is also proved to be effective in solving the tracking problem with trajectory planning.
Important Links:
Go Back
