Seamless Active Morphing Wing Simultaneous Gust and Maneuver Load Alleviation

Abstract

This paper deals with the simultaneous gust and maneuver load alleviation problem of a seamless active morphing wing. The incremental nonlinear dynamic inversion with quadratic programming control allocation and virtual shape functions (denoted as INDI-QP-V) is proposed to fulfill this goal. The designed control allocator provides an optimal solution while satisfying actuator position constraints, rate constraints, and relative position constraints. Virtual shape functions ensure the smoothness of the morphing wing at every moment. In the presence of model uncertainties, external disturbances, and control allocation errors, the closed-loop stability is guaranteed in the Lyapunov sense. Wind tunnel tests demonstrate that INDI-QP-V can make the seamless wing morph actively to resist "1-cos" gusts and modify the spanwise lift distribution at the same time. The wing root shear force and bending moment have been alleviated by more than 44% despite unexpected actuator fault and nonlinear backlash. Moreover, during the experiment, all the input constraints were satisfied, the wing shape was smooth all the time, and the control law was executed in real time. Furthermore, as compared with the linear quadratic Gaussian control, the hardware implementation of INDI-QP-V is easier; the robust performance of INDI-QP-V is also superior.

Black-Box Online Aerodynamic Performance Optimization for a Seamless Wing with Distributed Morphing

“…The ability to induce twisting of the trailing edge within each module by asymmetric actuator deflection allows for smoother morphing shapes than the distributed VCCTEFs. Control strategies for simultaneous gust and maneuver load alleviation have been demonstrated on SmartX-Alpha during wind tunnel experiments [17]. However, the in-flight drag minimization using the distributed morphing of SmartX-Alpha remains an open challenge, which will be addressed in this paper.…”

Aeroelastic Wing Demonstrator with a Distributed and Decentralized Control Architecture

“…The advantage of this design was the capability of local control of the lift distribution along the span through individual adjustment of the camber and twist of each morphing module. This allows the wing to settle into the most optimal lift to drag ratio (shape control) to minimize drag and perform the load alleviation tasks [6].…”

“…A distributed data-sharing architecture is developed based on the decentralized communication principle to facilitate smooth and adaptable integration of over-actuated wing systems and the multitude of sensors and real-time operation. This principle was investigated in sensor-based distributed control of the SmartX-Alpha demonstrated in a wind tunnel experiment in OJF [6]. Based on shared memory structure, the principle allows parallel integration of hardware and software components in various programming languages (Python, Matlab, Simulink, C++, .NET, etc.)…”

“…While active morphing benefits aerodynamic efficiency, the morphing mechanism required for smooth shape control generally needs larger actuation forces and a more complex design. In our previous study, we have demonstrated a seamless morphing wing concept [4,5], the SmartX-Alpha, capable of performing objectives such as shape control, drag minimization, and simultaneous gust and maneuver load alleviation [6]. This design showed a significant advantage over previous morphing concepts, allowing the lift distribution to be controlled locally by individually adjusting the camber and twist of each morphing module.…”

Vision-Based Nonlinear Incremental Control for a Morphing Wing With Mechanical Imperfections

“…An overactuated and oversensed wing prototype was developed for this project, named SmartX-Alpha, capable of seamless active wing morphing with six distributed translation-induced camber (TRIC) morphing modules [3]. 1 Coupled with advanced nonlinear control methods, this wing has demonstrated the capability to actively reduce gust loads while actively maintaining an optimal lift distribution in a recent wind tunnel study [4].…”