Suppression of ground resonance in rotorcraft using active landing gear

Author(s):  
Arjun Krishnan ◽  
Ashwin Krishnan ◽  
Mark Costello

This article examines the fundamental aspects of controlling ground resonance in rotorcraft equipped with actively controlled landing gear. Ground resonance is a mechanical instability affecting rotorcraft on the ground. It occurs at certain rotor speeds, where the lead–lag motion of the rotor couples with the motion of fuselage creating a self-excited oscillation. Typically, passive or semi-active lag dampers are used to avoid instability; however, these are undesirable from a design and maintenance perspective. Innovations in active landing gear for rotorcraft, such as articulated robotic legs, have provided an alternate approach to avoid the instability, eliminating the need for lag dampers with respect to ground resonance. This article extends classic ground resonance to include movable landing gear and identifies key physical parameters affecting dynamic behavior. Applying LQ optimal control to this model, it is shown that ground resonance instability can be eliminated using active landing gear as the control mechanism, even when there is no lag damping present in the rotor. In addition, while superior performance is achieved when landing gear movement can occur both longitudinally and laterally, it is still possible to stabilize ground resonance with inputs in a single direction, albeit with reduced performance.

2021 ◽  
pp. 107754632199693
Author(s):  
Jayachandran Warrier ◽  
Shaikh Faruque Ali

Ground resonance is an aero-mechanical instability in helicopters that use soft in-plane rotors. Traditionally, ground resonance is mitigated by using passive lead–lag dampers that provide sufficient in-plane damping. However, these dampers because of their passive nature cannot adapt to all operating conditions. In this work, a magnetorheological fluid–based semi-active lead–lag damper is proposed to offer controllable damping. Two nonlinear control strategies are reported to operate the voltage to be supplied to the magnetorheological damper. The first strategy is a model-based control using dynamic inversion. The second is a fuzzy logic control integrated with a particle swarm optimization algorithm to optimize the control parameters. Both control strategies are shown to be effective in eliminating ground resonance. Unlike bang–bang control, the prescribed control algorithms can make use of complete voltage level available in the magnetorheological damper with smooth voltage updates. A comparative study of the controller performances is made through appropriate performance indices and system responses. Finally, the most optimum control strategy to mitigate ground resonance is inferred.


1996 ◽  
Vol 118 (3) ◽  
pp. 482-488 ◽  
Author(s):  
Sergio Bittanti ◽  
Fabrizio Lorito ◽  
Silvia Strada

In this paper, Linear Quadratic (LQ) optimal control concepts are applied for the active control of vibrations in helicopters. The study is based on an identified dynamic model of the rotor. The vibration effect is captured by suitably augmenting the state vector of the rotor model. Then, Kalman filtering concepts can be used to obtain a real-time estimate of the vibration, which is then fed back to form a suitable compensation signal. This design rationale is derived here starting from a rigorous problem position in an optimal control context. Among other things, this calls for a suitable definition of the performance index, of nonstandard type. The application of these ideas to a test helicopter, by means of computer simulations, shows good performances both in terms of disturbance rejection effectiveness and control effort limitation. The performance of the obtained controller is compared with the one achievable by the so called Higher Harmonic Control (HHC) approach, well known within the helicopter community.


1998 ◽  
Vol 335 (7) ◽  
pp. 1207-1213
Author(s):  
W.Q. Liu ◽  
K.L. Teo ◽  
W.Y. Yan ◽  
V. Sreeram

2010 ◽  
Vol 31 (6) ◽  
pp. 547-566 ◽  
Author(s):  
Charlotte Beauthier ◽  
Joseph J. Winkin

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