Model predictive gust load alleviation for a flexible wing considering system limitations

Abstract Future aircraft with increasingly flexible high aspect ratio wings are more vulnerable to gust and turbulence encounters. Active control technologies are therefore required to mitigate the effects of atmospheric disturbances and reduce structural sizing loads. However, the achievable load alleviation performance is constrained by system limitations such as time delays, parasitic dynamics, actuator limits, and sensor noise. In this context, model predictive control systems offer strong potential, as they can address these limitations. This paper presents the design and evaluation of such a model predictive gust load alleviation controller for a flexible test wing. The aeroelastic simulation model is based on a modal description of the structural dynamics and aerodynamic strip theory, with its parameters identified from ground vibration and wind tunnel tests. A Kalman filter is designed to estimate structural loads and non-measurable quantities including generalized structural coordinates and wind disturbances from highly noisy wind tunnel measurements. Preview information of upcoming gusts is provided to the controller, enabling feedforward control to compensate for time delays. The formulation can account for actuator limits and maximum allowable loads, ensuring effective operation within the system boundaries. To reduce the computational effort of the controller, Laguerre functions and an efficient soft output constraint formulation are employed. The resulting control system is evaluated in virtual wind tunnel tests based on the identified model with gust encounters of varying frequency. Further, the effects of degraded actuator limits and failure cases are investigated. Particular emphasis is placed on encounters with short and load-critical gusts, where the controller achieves good load alleviation performance despite restrictive system limitations.