Horizontal Nonlinear Path Following Guidance Law for a Small UAV With Parameter Optimized by NMPC

Abstract

In this study, the problem of guiding a small fixed-wing unmanned aerial vehicle (UAV) toward a predefined horizontal path is studied. A stable nonlinear guidance law, which is a function of the inertial positions and velocities of the UAV and the predefined path, is designed using Lyapunov stability arguments. The concept of the nonlinear model predictive control (NMPC) technique was applied to optimize a key parameter of the guidance law to improve the performance of the controller (PFC_NMPC), where the stability of the relative nonlinear system is maintained. The proposed method was verified in the MATLAB/Simulink environment to realize following the straight-line, square and circular paths. The path- following performance of the proposed method is compared with those of the guidance laws with parameter fixed (PFC) or tuned by fuzzy logic (PFC_FL). With the predictive ability, the proposed method can make the UAV fly more on the desired square and circular paths than the other two methods, PFC and PFC_FL. The error overshoot by using PFC_NMPC is much smaller than those by using the PFC and PFC_FL methods in the presence of wind at 8m/s.

Keywords

• Path following
• small unmanned aerial vehicle
• Lyapunov stability
• parameter optimization
• nonlinear model predictive control