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.
Highlights
In the past two decades, the autonomous capability of small fixed-wing unmanned aerial vehicle (UAV) has been greatly developed [1]
As all of the planar curves can be approximated by a series of segments, and considering the course rate constraint, this study focuses on the UAVs’ straight-line and circular paths as follows
The length of the predefined circular path followed (LOPCPF) is defined as the length of the actual flight path after the time that the UAV has converged to the desired circular path with the absolute value of distance |dd(xx, yy)| becomes less than 1.45m
Summary
In the past two decades, the autonomous capability of small fixed-wing UAVs has been greatly developed [1]. Y. Chen et al.: Horizontal Nonlinear Path Following Guidance Law for a Small UAV with Parameter Optimized by NMPC predefined straight-line path. The PD-like nonlinear guidance law is extended to follow a class of horizontal paths, and the open-loop optimization of the NMPC technique is used to optimize a key parameter of the controller to make it adaptive. The proposed novel nonlinear guidance law adopts both the simple structure of the basic method and the predictive optimization of the NMPC technique to improve the path-following performance. In contrast to the traditional stable closed-loop system design under NMPC, the stability of the guidance system is guaranteed by the initial nonlinear control law, whereas the NMPC technique is only used for parameter optimization.
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