Flight Validation of Metrics Driven L1 Adaptive Control

Abstract

The paper addresses initial steps involved in the development and flight implementation of new metrics driven L1 adaptive flight control system. The work concentrates on (i) definition of appropriate control driven metrics that account for the control surface failures; (ii) tailoring recently developed L1 adaptive controller to the design of adaptive flight control systems that explicitly address these metrics in the presence of control surface failures and dynamic changes under adverse flight conditions; (iii) development of a flight control system for implementation of the resulting algorithms onboard of small UAV; and (iv) conducting a comprehensive flight test program that demonstrates performance of the developed adaptive control algorithms in the presence of failures. As the initial milestone the paper concentrates on the adaptive flight system setup and initial efforts addressing the ability of a commercial off-the-shelf autopilot with and without adaptive augmentation to recover from control surface failures.

Experimental Validation of L1 Adaptive Control: The Rohrs Counterexample in Flight

“…1. Preliminary flight-test results of this setup were first reported in [29], where Dobrokhodov et al analyzed stability and performance of the L 1 adaptive control system in the presence of locked-in-place control surface failures. The results obtained demonstrated that the L 1 augmented system provides fast recovery to sudden failures in one of the ailerons or in the rudder, while the unaugmented system would go unstable.…”

“…These adaptive algorithms, with and without modifications, are used to check the validity of the flight-test setup and to verify that the phenomena observed in Rohrs et al's simulations [7,8] can be replicated. Finally, we also present the L 1 output-feedback control architecture implemented on the RFTPS, which has been proven to enhance the angular-rate tracking capabilities of commercial APs [29,32]. For the design of both the MRAC and the L 1 augmentation algorithms, we will assume that the closed-loop UAV and its AP is represented by a single-input/singleoutput uncertain second-order transfer function with relative degree 1 and known sign of the high-frequency gain, and we will consider the system in Eq.…”

L1 Adaptive Control for Indoor Autonomous Vehicles: Design Process and Flight Testing

“…2,3,5 In [6], more than just the low-pass filter is considered, but the analysis again relies on a system norm as the only performance metric. Metrics are validated through extensive flight testing in [7], but these metrics are not considered in an a priori control design process. None of the approaches listed comprises a systematic design process that considers both transient performance and robustness simultaneously.…”

Simulink Based Hardware-in-the-Loop Simulator for Rapid Prototyping of UAV Control Algorithms

“…This allows, for instance, to still run a flight computer onboard as reported in Refs. 7,12,21 offering an added value of higher fidelity flight dynamics modeling to the previously reported flight architectures.…”