Nonlinear Model Predictive Controller-Based Line Tracking Guidance

This chapter addresses an online optimization on the path following guidance law for an unmanned aerial vehicle (UAV) against an external disturbance. The guidance problem is formulated in the nonlinear model predictive control (NMPC) framework with a nonlinear discrete-time kinematics model. The derived error dynamics with respect to the flight path are solved by numerical optimization minimizing the associated performance index in conjunction with equality/inequality constraints and the terminal condition. An NMPC solves the online optimal control problem at each sampling time by repeating the prediction of the trajectory of a nonlinear system over a receding time horizon from the current time and the generation of the control input sequences by solving the given optimal control problem. Numerical simulation demonstrates the effectiveness of the NMPC-based guidance algorithm compared with other benchmark guidance schemes.