A Comprehensive Analytical Tool for Control Validation of Fixed-Wing Unmanned Aircraft.

This paper improves and implements a framework based on robustness analysis to aid in the certification of unmanned aircraft system (UAS) flight controllers. The approach first models the UAS using a linear fractional transformation on uncertainties and then conducts robustness analysis on the uncertain system via integral quadratic constraint (IQC) theory. By expressing the set of desired UAS flight paths with an uncertainty, the framework considers the analysis of the uncertain UAS flying about any level path whose radius of curvature is bounded. The approach is capable of analyzing trajectory-tracking and path-following controllers, and an accurate expression of UAS path-following dynamics in the presence of nonzero wind is derived. To demonstrate the versatility of this technique, we use IQC analysis to tune trajectory-tracking and path-following controllers that are designed via $\mathcal {H}_{2}$ or $\mathcal {H}_\infty $ synthesis methods. IQC analysis is also used to tune path-following PID controllers. By employing a nondeterministic simulation environment and conducting numerous flight tests, we see that the uncertain UAS framework reliably predicts loss of control, compares the robustness of different controllers, and provides tuned controllers that are sufficiently robust. Finally, this work demonstrates that signal IQCs have an important role in obtaining IQC analysis results that are less conservative and more consistent with observations from flight test data. [ABSTRACT FROM AUTHOR]