Active Modeling Based Yaw Control of Unmanned Rotorcraft


Share / Export Citation / Email / Print / Text size:

International Journal on Smart Sensing and Intelligent Systems

Professor Subhas Chandra Mukhopadhyay

Exeley Inc. (New York)

Subject: Computational Science & Engineering, Engineering, Electrical & Electronic


eISSN: 1178-5608



VOLUME 7 , ISSUE 1 (March 2014) > List of articles

Active Modeling Based Yaw Control of Unmanned Rotorcraft

Yan Peng * / Wenqing Guo / Mei Liu / Shaorong Xie

Keywords : Unmanned Rotorcraft, Active modeling technique, Model error, Kalman filter (KF).

Citation Information : International Journal on Smart Sensing and Intelligent Systems. Volume 7, Issue 1, Pages 380-399, DOI:

License : (CC BY-NC-ND 4.0)

Received Date : 10-October-2013 / Accepted: 02-February-2014 / Published Online: 27-December-2017



With the characteristics of input nonlinearity, time-varying parameters and the couplings between main and tail rotor, it is difficult for the yaw dynamics of Rotorcraft to realize good tracking performance while maintaining stability and robustness simultaneously. In this paper, a new kind of robust controller design strategy based on active modeling technique is proposed to attenuate the uncertainties pre-described in the yaw control of unmanned systems. Firstly, by detailed analysis, the uncertainties are introduced into the new-designed yaw dynamics model by using the concept of modeling errors. Then, Kalman filter is used to estimate the modeling errors simultaneously, which is used subsequently to design the robust controller. Finally, the new strategy is tested with respect to the unmanned Rotorcraft system to show the feasibility and validity of it.

Content not available PDF Share



[1] Castillo, C. L., Alvis, W., Castillo-Effen, M., Moreno, W. and Valavanis, K., “Small scale helicopter analysis and controller design for nonaggressive flights”, Proc., 2005 IEEE Int. Conf. on Systems, Man and Cybernetics, Vol. 4, IEEE, Washington, DC, pp. 3305-3312.
[2] Shin, J., Nonami, K., Fujiwara, D., and Hazawa, K., “Model-based optimal attitude and positioning control of small-scale unmanned helicopter”, Robotica, vol. 23, no. 1, pp. 51-63.
[3] Kumar, M. V., Sampath, P., Suresh, S., Omkar, S. N., and Ganguli, R., “Design of a stability augmentation system for a helicopter using LQR control and ADS-33 handling qualities specifications”, Aircr. Eng. Aerosp, Technol., vol.80, no. 2, 2008, pp.111-123.
[4] Kumar, M. V., Suresh, S., Omkar, S. N., Ganguli, R., and Sampath, P., “A direct adaptive neural command controller design for an unstable helicopter”, Eng. Applic. Artif. Intell., vol. 22,no. 2, 2009, pp.181-191.
[5] Suresh, S., “Adaptive neural flight control system for helicopter”, Proc., IEEE Symp. on Computational Intelligence in Security and Defense Applications, IEEE, 2009, Washington, DC,1-8.
[6] Cai, G., Chen, B. M., Dong, X., and Lee, T. H., “Design and implementation of a robust and nonlinear flight control system for an unmanned helicopter”, Mechatronics, vol. 21, no. 5, 2011,pp. 803-820.
[7] Nejjari, F., Saldivar, E., and Morcego, B., “Heading control system design for an unmanned helicopter”, Proc., 19th Mediterranean Conf. on Control and Automation, IEEE, Washington, DC, 2011, pp.1373-1378.
[8] Nonaka, K., and Sugizaki, H., “Integral sliding mode altitude control for a small model helicopter with ground effect compensation”, Proc., 2011 American Control Conf., IEEE, Washington, DC, pp. 202-207.
[9] Joelianto, E., Sumarjono, E. M., Budiyono, A., and Penggalih, D. R., “Model predictive control for autonomous unmanned helicopters”, Aircr. Eng. Aerosp. Technol., vol. 83, no. 6,2011, pp. 375– 387.
[10] Shin, Jongho, et. al., “Autonomous Flight of the Rotorcraft-Based UAV Using RISE Feedback and NN Feedforward Terms”, IEEE Transactions on Control Systems Technology,2012(20.5): 1392-1399.
[11] Cai G W , Biao W, Ben M,, “Design and implantation of a flight control system for an unmanned rotorcraft using RPT control approach”, Asian Journal of Control, Vol. 15, No. 1,2013, pp. 95–119.
[12] Sridevi M, Mahavasarma P, “Model identification and Smart structural vibration control using  H controller”, international journal on smart sensing and intelligent systems, Vol. 3, No.4, 2010.
[13] Gadewadikar, J., Lewis, F. L., Subbarao, K., Peng, K., Chen, B. M., “H-Infinity static output-feedback control for rotorcraft”, J. Intell. Robot. Syst., vol.54, no.4, 2009, pp.629– 646.
[14] Zhao, X., and Han, J., “Yaw control of RUAVs: an adaptive robust  H control method”,Proc., 17th World Congress, International Federation of Automatic Control, 2008, Seoul, Korea.
[15] Dharmayanda, H. R., Budiyono, A. and Kang, T., “State space identification and implementation of  H control design for small-scale helicopter”, Aircr. Eng. Aerosp. Technol., vol. 82, no. 6, 2010, pp. 340-352.
[16] Jeong D Y, Kang T, Dharmayanda H R, et al, “H-infinity attitude control system design for a small-Scale Autonomous Helicopter with Nonlinear dynamics and uncertainties”, Journal of aerospace engineering , 2012(25), pp. 501-518.
[17] Zhe Jiang, Juntong Qi, Xingang Zhao,“Feedback control for yaw angle with input nonlinearity via input-state linearization”. Proceedings of the 2006 IEEE International Conference on Robotics and Biomimetics, Kunming, pp. 323-328.