Ground resonance (GR) is a potentially destructive mechanical instability involving the coupling of the regressive rotor mode to the fuselage motion. Vibration can be disastrous if measures are not taken in time to mitigate vibrations. This paper presents a study on the use of adaptive landing gear to eliminate GR in helicopters. A GR model considering adaptive landing gear is established, and the dynamic characteristics of the system are analyzed. In this paper, the Linear Quadratic Regulator (LQR) controller is applied to suppress the GR. The setting of the weighting matrix coefficients directly determines the effect of the control system. Therefore, a design method of LQR weighting matrix based on multi-objective genetic algorithm is proposed, which enables the control system to meet multiple performance indicators concurrently. Numerical simulations of GR suppression were performed for the rotor speed range where GR is most likely to occur. The results show that even if the rotor system is not equipped with any dampers, the suppression of helicopter GR can be achieved by using the control strategy proposed in this paper to control the adaptive landing gear. Therefore, the application of adaptive leg landing gear to helicopters can provide some ideas to eliminate GR. 

LQR-based Ground Resonance Suppression of Helicopter with Adaptive Landing Gear

Ground resonance (GR) is a potentially destructive mechanical instability involving the coupling of the regressive rotor mode to the fuselage motion. Vibration can be disastrous if measures are not taken in time to mitigate vibrations. This paper presents a study on the use of adaptive landing gear to eliminate GR in helicopters. A GR model considering adaptive landing gear is established, and the dynamic characteristics of the system are analyzed. In this paper, the Linear Quadratic Regulator (LQR) controller is applied to suppress the GR. The setting of the weighting matrix coefficients directly determines the effect of the control system. Therefore, a design method of LQR weighting matrix based on multi-objective genetic algorithm is proposed, which enables the control system to meet multiple performance indicators concurrently. Numerical simulations of GR suppression were performed for the rotor speed range where GR is most likely to occur. The results show that even if the rotor system is not equipped with any dampers, the suppression of helicopter GR can be achieved by using the control strategy proposed in this paper to control the adaptive landing gear. Therefore, the application of adaptive leg landing gear to helicopters can provide some ideas to eliminate GR.

LQR-based Ground Resonance Suppression of Helicopter with Adaptive Landing Gear*


Purpose
Helicopter fuselage vibration prediction is important to keep a safety and comfortable flight process. The helicopter vibration mechanism model is difficult to meet of demand for accurate vibration prediction. Thus, the purpose of this paper is to develop an intelligent algorithm for accurate helicopter fuselage vibration analysis.


Design/methodology/approach
In this research, a novel weighted variational mode decomposition (VMD)- extreme gradient boosting (xgboost) helicopter fuselage vibration prediction model is proposed. The vibration data is decomposed and reconstructed by the signal clustering results. The vibration response is predicted by xgboost algorithm based on the reconstructed data. The information transfer order between the controllable flight data and flight attitude are analyzed.


Findings
The mean absolute percentage error (MAPE), root mean square error (RMSE) and mean absolute error (MAE) of the proposed weighted VMD-xgboost model are decreased by 6.8%, 31.5% and 32.8% compared with xgboost model. The established weighted VMD-xgboost model has the highest prediction accuracy with the lowest mean MAPE, RMSE and MAE of 4.54%, 0.0162, and 0.0131, respectively. The attitude of horizontal tail and cycle pitch are the key factors to vibration.


Originality/value
A novel weighted VMD-xgboost intelligent prediction methods is proposed. The prediction effect of xgboost model is highly improved by using the signal-weighted reconstruction technique. In addition, the data set used is collected from actual helicopter flight process.


Flight data-driven intelligent prediction for fuselage vibration of helicopter

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 sufficie...

Jayachandran Warrier

Papers

Nonlinear dynamics and control of helicopter ground resonance