Abstract
Guidance, navigation, and control system design is, undoubtedly, one of the most relevant issues in any type of unmanned aerial vehicle, especially in the case of military missions. This task needs to be performed in the most efficient way possible, which involves trying to satisfy a set of requirements that are sometimes in opposition. The purpose of this article was to compare two different control strategies in conjunction with a path-planning and guidance system with the objective of completing military missions in the most satisfactory way. For this purpose, a novel dynamic trajectory-planning algorithm is employed, which can obtain an appropriate trajectory by analyzing the environment as a discrete 3D adaptive mesh and performs a softening process a posteriori. Moreover, two multivariable control techniques are proposed, i.e., the linear quadratic regulator and the model predictive control, which were designed to offer optimal responses in terms of stability and robustness.
Highlights
The code developed to perform all the simulations is available on Matlab Central [74], including the path-planning algorithms, control parameter definitions, and Simulink files, in which the controllers and guidance law that were employed in simulations are implemented
A realistic simulation environment was implemented for the F-86 Sabre acting as a unmanned aerial vehicles (UAVs) based on a group of known algorithms to analyze which multivariable control method provides a more satisfactory performance
The dynamic trajectory-planning algorithms, which are modified versions of those in [14,45,62], demonstrated a proper behavior in the creation of waypoints for trajectories that are perfectly trackable for the aircraft and allow one to avert 3D obstacles
Summary
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. One example of a military mission could be dropping bombs over an objective from an initial location, which is the purpose of the UAV proposed in this article. Path planning determines the flight trajectory that the UAV should follow to move from an initial point to a final one, avoiding obstacles during the route. The proposed trajectory along with the navigation information is computed by the guidance law to determine the main reference signals for the control algorithms. For trajectory tracking in combat missions in which obstacles are averted and a blitz is performed Both control techniques’ behaviors were studied based on flight autonomy, reference following, obstacle avoidance, and bomb impact accuracy. The autonomous flying system implemented in this article is composed of two fundamental blocks: path-planning algorithms and a guidance, navigation, and control (GNC) system
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