Verification and Tuning of an Adaptive Controller for an Unmanned Air Vehicle*

Abstract

This paper focuses on the analysis and tuning of a controller based on the "Adaptive Control Technology for Safe Flight (ACTS)" architecture. The ACTS architecture consists of a nominal, non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off-nominal ones. A framework unifying control verification and gain tuning is used to make the controller's ability to satisfy the closed-loop requirements more robust to uncertainty. In this paper we tune the gains of both controllers using this approach. Some advantages and drawbacks of adaptation are identified by performing a global robustness assessment of both the adaptive controller and its non-adaptive counterpart. The analyses used to determine these characteristics are based on evaluating the degradation in closed-loop performance resulting from uncertainties having increasing levels of severity. The specific adverse conditions considered can be grouped into three categories: aerodynamic uncertainties, structural damage, and actuator failures. These failures include partial and total loss of control effectiveness, locked-in-place control surface deflections, and engine out conditions. The requirements considered are the peak structural loading, the ability of the controller to track pilot commands, the ability of the controller to keep the aircraft's state within the reliable flight envelope, and the handling/riding qualities of the aircraft. The nominal controller resulting from these tuning strategies was successfully validated using the NASA GTM Flight Test Vehicle.

Automatic Flight Control Systems

“…This step is of considerable importance since the choice of nonlinear controller realization can greatly influence the closed loop performance (Leith & Leithead, 2000). Furthermore, actual mission requirements constraint quantitatively the time response of the augmented system (Crespo et al, 2010), e.g. by imposing tracking requirements of a reference trajectory or requiring relevant output variables to be enclosed within a limited flight envelope.…”

Verifying Spatiotemporal Systems via Robustness Bounds: An Application to Unmanned Underwater Vehicles

“…However, due to the high computational costs, the MC analysis is impractical for robustness verification of control systems. On the other hand, optimization-based methods [15][16][17] are used to determine the bounds in the uncertain parameter space where the system performance remains stable. Particularly for that type of methods, an adaptive control verification framework is applied to unmanned air vehicle to keep the aircraft's state within a reliable flight envelope in [16].…”

Unmanned aerial vehicle trajectory tracking algorithm comparison

“…UAVs have been used to develop and test fault tolerant control laws for manned aircraft (Perhinschi and Napolitano, 2007; Jordan et al , 2006); however, extensive fault tolerance for autonomous flight has been addressed only to a lesser extent as compared to manned aircraft (KrishnaKumar, 2002; KrishnaKumar and Gundy‐Burlet, 2002). While inherent robustness is desirable, robust control techniques (Sadraey and Colgren, 2006; Beard et al , 2005; Jayaram, 2009) alone are not sufficient and it is expected that adaptive control techniques (Amoozgar et al , 2012; Crespo et al , 2010; Kaminer et al , 2010, Zhang and Jiang, 2008; Ducard and Geering, 2008b; Suresh et al , 2006; Calise et al , 2003) must be used to provide a comprehensive and integrated solution to the problem of fault tolerant autonomous flight.…”