Performance Enhancement of Gust Load Alleviation Systems for Flexible Aircraft using H_∞Optimal Control with Preview

Abstract

Most of the gust load alleviation systems (GLAS) of currently-operational aircraft are of feedback-only control architecture based on inertial measurements. In few other aircraft, aerodynamic measurements from air data sensors are additionally included, or presently considered for inclusion, as they usually result in improving the performance of the GLAS. In both sensor types, the control system has very little time to react; and therefore, the performance of the GLAS would be further enhanced if the turbulence or gust could be measured at some distance ahead of the aircraft. Doppler LIDAR (LIght Detection And Ranging) sensors could enable such preview of the turbulence or gust, at a short range (typically between 30 and 200 meters) ahead of the aircraft. In this paper, the availability of a vertical wind profile ahead of the aircraft is assumed, and the paper focuses on the design of a load alleviation controller that exploits this information. The proposed methodology of designing this controller is based on the application of the H ∞ optimal control techniques to a discrete-time preview control problem. Minimizing the H ∞ norm of the transfer function from wind input to loads output, directly leads to the design of an effective load alleviation function. The preview-control formulation enables the design algorithm to synthesize a combined preview-capable feedforward and feedback load alleviation function. For a practical reason, the developed methodology is applied in the course of this paper to a flexible sailplane model (DLR's Discus-2c), although it is intended to be applied to larger airplanes (e.g. transport airplanes and business jets).

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

“…A complete derivation of the preview control problem can be found in Ref. [40], which yields the discrete-time system given by Equation (9). This system is in the standard form of a control problem given by Equation (7), hence the characterisation of solvability relies exclusively on that of control theory.…”

“…Each step of this procedure is then detailed in Subsection 4.2: Obtain the bare linear model of the aircraft Trim the non-linear model at the desired operating point Linearise the model at the trim point from the previous step Adjust the linear model to be in the standard form for control If not already defined in the original non-linear model, add the exogenous disturbance inputs (without delay) to the linear model Include the actuator/sensor dynamics, if not already defined in the original non-linear model Normalise and weight the performance channels Normalise the inputs and outputs of the performance channels to obtain an open-loop norm Add the appropriate input- and control-action weighting functions Obtain the discrete-time preview system model Discretise the model with an adequate sampling time Add a chain of h unit delays (explained in more detail in Ref. [40]) to obtain the discrete-time preview system model defined in Equation (9) Augment the measurement vector to include the previewed signal Proceed to the steps that a specific control design method may require (e.g. MATLAB’s or functions) …”

“…Obtain the discrete-time preview system model Discretise the model with an adequate sampling time Add a chain of h unit delays (explained in more detail in Ref. [40]) to obtain the discrete-time preview system model defined in Equation (9) Augment the measurement vector to include the previewed signal …”

“…Add a chain of h unit delays (explained in more detail in Ref. [40]) to obtain the discrete-time preview system model defined in Equation (9)…”

A multi-channel $$\varvec{H}_\infty $$ preview control approach to load alleviation design for flexible aircraft

“…In [3], the authors synthesized an H ∞ optimal controller for alleviating the structural loads and enhancing the ride qualities of a flexible aircraft. In their work, the controller was synthesized by two different methods of the H ∞ optimal control: full-order based on the work of [4,5], and fixedstructure based on the method presented in [6,7], and implemented in the MATLAB Robust Control Toolbox.…”