Gust load alleviation for flexible aircraft using discrete-time preview control

Abstract

Turbulence and gusts cause variations in the aerodynamic forces and moments applied to the structure of aircraft, resulting in passenger discomfort and dynamic loads on the structure that it must be designed to support. By designing Gust Load Alleviation (GLA) systems, two objectives can be achieved: first, realizing higher passenger comfort; and second, reducing the dynamic structural loads, which allows the design of lighter structures. In this paper, a methodology for designing combined feedback/feedforward GLA systems is proposed. The methodology relies on the availability of a wind profile ahead of the aircraft measured by a Doppler LIDAR sensor, and is based on $H_{\infty}$-optimal control techniques and a discrete-time preview-control problem formulation. Moreover, to allow design trade-offs between those two objectives (to achieve design flexibility) as well as to allow specification of robustness criteria, a variant of the problem using multi-channel $H_{\infty}$-optimal control techniques is introduced. The methodology developed in this paper is intended to be applied to large aircraft, e.g. transport aircraft or business jets. The simulation results show the effectiveness of the proposed design methodology in accounting for the measured wind profile to achieve the two mentioned objectives, while ensuring both design flexibility and controller robustness and optimality.

Wind Tunnel Study of Preview H2 and H∞ Control for Gust Load Alleviation for Flexible Aircraft

“…This makes it possible for an aircraft with onboard LIDAR sensors to preview the gust disturbance ahead of encounter. The preview GLA formulation, simulation [15,[21][22][23][24][25][26], wind tunnel experiments [2,3,27], and flight test [28,29] have all been explored. [4], the testbed built in 3ft by 3ft wind tunnel for studying the control laws.…”

“…Lastly, once the controller is synthesized, the controller requires rescaling before implementation on the original system. The details are discussed in [23][24][25]41].…”

“…Khalil and Fezan's work in [23][24][25] are inspired by [33,38] solving the preview problem in full information structure as in Section 2.3. The differences between the two methods are subtle.…”

“…25 suggest the maximum gain results from the worst input signal d(t) of a sinusoidal with frequency ω * aligning the direction of σ(G(jω * )). Lastly, the H ∞ norm is equal to the induced power norm and has an interpretation of an induced norm in terms of expected values of stochastic signals.The difference of the H 2 and H ∞ norm could be seen in Equations 2.21 and 2.26 in term of singular values.…”

Performance evaluation of gust load alleviation systems for flexible aircraft via optimal control

“…Such framework gives interesting insights concerning control efficiency of the aircraft and the associated limiting factors. It could for instance be integrated in an automated design process or help to assess the potential benefits offered by modern technologies such as LIDAR as explored in the work of [8]. Still, the dimension of the model (1) remains an issue as it directly impacts the number of variables in the transcribed optimisation problem.…”