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

Abstract

Adaptive control techniques have the potential to address many of the special performance and robustness requirements of flight control for unmanned aerial vehicles. L 1 adaptive control offers potential benefits in terms of performance and robustness. An L 1 adaptive output feedback control design process is presented here in which control parameters are systematically determined based on intuitive desired performance and robustness metrics set by the designer. Flight test results verify the process for an indoor autonomous quadrotor helicopter, demonstrating that designer specifications correspond to the expected physical responses. In flight tests comparing it with the baseline linear controller, the augmented adaptive system shows definite performance and robustness improvements confirming the potential of L 1 adaptive control as a useful tool for autonomous aircraft.

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

“…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.…”

ℒ1adaptive control of a shape memory alloy actuated flexible beam

“…For realtime controller implementation on a computer, is limited by the stability of the numerical integration method, which is determined largely by available computational capabilities. As discussed in (Michini and How, 2009), the choice of M (s) is not so straightforward for achieving the desired specifications. Given these characteristic limitations, no intuitive method has been established to find combinations of C(s), M (s) and that yield optimal tracking performance for specific application.…”

Autonomous Parafoil Guidance in High Winds

“…There are numerous results in the literature for this process for the output-feedback case, including those based on satisfying another L 1 condition, using optimization [21], [15], as well as robust control [18]. For the present study, a method based on pole-placement [29] is pursued.…”