Research on Velocity Vector Tracking Technology Based on Nonlinear Model Predictive Control

To achieve precise tracking of velocity vectors, a guidance method based on nonlinear model predictive control is proposed. This method establishes the relationship between the dynamic desired velocity vector and the actual velocity vector of the unmanned aerial vehicle (UAV) based on the error between them. For a given sequence of velocity vectors, a cubic spline interpolation function is employed for trajectory optimization, yielding a parameterized desired velocity vector curve that ensures curvature continuity. A nonlinear guidance law is designed based on dynamic virtual target points, incorporating UAV roll capabilities and constraints on the speed of dynamic reference points. This approach formulates a nonlinear optimization problem to track velocity vectors, utilizing a sequential quadratic programming algorithm to compute guidance commands that follow complex velocity vectors. Simulation results demonstrate that this method achieves stable tracking of complex velocity vectors with tracking accuracy at the decimeter level.