Technical Papers
Oct 17, 2012

Adaptive Control of Helicopter Pitch Angle and Velocity

Publication: Journal of Aerospace Engineering
Volume 27, Issue 5

Abstract

This paper discusses flying objects’ adaptive control with direct application to the flight of helicopters. Two new automatic adaptive control systems are suggested: the former is used for pitch angle control, while the latter is used for control of helicopter pitch angle and velocity; this second system is an extension of the first one. The adaptive control is based on the dynamic inversion principle and the use of neural networks. The two adaptive control systems have reference models, linear dynamic compensators, linear observers, and neural networks. The adaptive components of the automatic control laws compensate for the approximation errors of the dynamic model’s nonlinear functions. The used actuators are linear or nonlinear. To eliminate the neural networks’ adapting difficulties, a pseudo-control hedging (PCH) block is inserted in the adaptive system; it limits the adaptive pseudo-control by means of a component that represents the estimation error of the actuator dynamics. Thus, the PCH block moves back the reference model—i.e., it introduces a reference model response correction with respect to the actuator position estimation; the signal provided by the PCH block represents a reference model’s additional input. For the two new automatic adaptive control systems, a technical computing environment is used to obtain time characteristics of the adaptive systems with linear and nonlinear actuators. Phase trajectories of the two adaptive control systems with nonlinear actuators express the convergence of the nonlinear systems to stable limit cycles.

Get full access to this article

View all available purchase options and get full access to this article.

References

Balestrassi, P. P., Popova, E., Paiva, A. P., and Lima, M. (2009). “Design of experiments on neural network’s training for nonlinear time series forecasting.” J. Neurocomput., 72(4–6), 1160–1178.
Calise, A. J. (2003). “Flight evaluation of an adaptive velocity command system for unmanned helicopters.” AIAA Guidance, Navigation and Control Conf. and Exhibit, Austin, TX.
Calise, A. J., Hovakymyan, N., and Idan, M. (2001). “Output control of nonlinear systems using neural networks.” Automatica, 37(8), 1201–1211.
Calise, A. J., Johnson, E. N., Johnson, M. D., and Corban, J. E. (2006). “Applications of adaptive neural networks control to unmanned aerial vehicles.” J. Harbin Inst. Technol., 38(11), 1865–1869.
Calise, A. J., Lee, H., and Kim, N. (2000). “High bandwidth adaptive flight control.” AIAA Guidance, Navigation and Control Conf., American Institute of Aeronautics and Astronautics (AIAA), Reston, VA.
Che, J., and Chen, D. (2001). “Automatic landing control using H∞ control and stable inversion.” Proc., 40th Conf. on Decision and Control, Institute of Electrical and Electronics Engineers (IEEE), New Brunswick, NJ, 241–246.
Chen, X., Gaofeng, W., Wei, Z., Sheng, C., and Shilei, S. (2006). Efficient sigmoid function for neural networks based FPGA design, Springer, Berlin.
Chwa, D., and Choi, J. (2003). “Adaptive nonlinear guidance law considering control loop dynamics.” IEEE Trans. Aerosp. Electron. Syst., 39(4), 1134–1143.
Chwa, D., Choi, J., and Seo, J. H. (2004). “Compensation of actuator dynamics in nonlinear missile control.” IEEE Trans. Contr. Syst. Technol., 12(4), 620–626.
Eltantawie, M. A. (2010). “Application of neuro-fuzzy reduced order observer in magnetic bearing systems.” Proc., Int. Multi-Conf. on Engineers and Computer Scientists, Vol. II, International Association of Engineers (IAENG), Hong Kong.
Ferrari, S. (2005). “Smooth function approximation using neural networks.” IEEE Trans. Neural Networks, 16(1), 24–38.
Ghinea, M., and Fireteanu, V. (2001). Matlab - calcul numeric - grafica - aplicatii, Teora.
Gregory, L. P. (2000). Adaptive inverse control of plants with disturbances, Stanford University Press, Redwood City, CA.
Hampel, R., Wagenknecht, M., and Chaker, N. (2000). Fuzzy control—Theory and practice, Springer, Berlin.
Hoseini, S. M., Farrokhi, M., and Kashkonei, A. J. (2006). “Robust adaptive control systems using neural networks.” Int. J. Contr., 81(8), 1319–1330.
Hovakimyan, N., Kim, N., Calise, A. J., and Parasad, J. V. R. (2005). “Adaptive output feedback for high-bandwidth control of an unmanned helicopter.” AIAA Guidance, Navigation and Control Conf., American Institute of Aeronautics and Astronautics (AIAA), Montreal, Canada.
Hovakimyan, N., Nardi, F., Kim, N., and Calise, A. J. (2002). “Adaptive output feedback control of uncertain systems using single hidden layer neural networks.” IEEE Trans. Neural Networks, 13(6), 1420–1431.
Isidori, A. (1995). Nonlinear control systems, Springer, Berlin.
Jantzen, J. (1998). “Tuning of fuzzy PID controllers.”, Dept. of Automation, Technical Univ. of Denmark, Kongens Lyngby, Denmark.
Johnson, E. N., and Calise, A. J. (2000). “Pseudo-control hedging: A new method for adaptive control.” Advances in Navigation Guidance and Control Technology Workshop, Redstone Arsenal, AL.
Johnson, E. N., and Calise, A. J. (2001a). “Adaptive guidance and control for autonomous launch vehicles.” IEEE Aerospace Conf., Institute of Electrical and Electronics Engineers (IEEE), New Brunswick, NJ.
Johnson, E. N., and Calise, A. J. (2001b). “Neural network adaptive control of systems with input saturation.” American Control Conf., American Automatic Control Council (AACC), Troy, NY.
Johnson, E. N., Calise, A. J., Rysdyk, R., and Shirbiny, E. A. (2000). “Feedback linearization with neural network augmentation applied to X-33 attitude control.” AIAA Guidance, Navigation and Control Conf. and Exhibit, American Institute of Aeronautics and Astronautics (AIAA), Reston, VA.
Kargin, V. (2007). “Design of an autonomous landing control algorithm for a fixed wing UAV.” M.S. thesis, Middle East Technical Univ., Ankara, Turkey.
Kumar, V., Rana, K. P., and Gupta, V. (2008). “Real-time performance evaluation of a fuzzy PI + fuzzy PD controller for liquid-level process.” Int. J. Intell. Contr. Syst., 13(2), 89–96.
Kurdjukov, A. P., Pavlov, B. V., and Timin, V. N. (1996). “Longitudinal flight control by windshear via H∞ methods.”, American Institute of Aeronautics and Astronautics (AIAA), Reston, VA.
Lungu, M. (2008). Flight control systems, Sitech Publisher, Craiova, 219–242.
Lungu, R. (1997). Gyro equipment and systems, Universitaria Publisher, Craiova, 135–145.
Lungu, R. (2000). Automatic flight control systems, Universitaria Publisher, Craiova, 252–259.
Lungu, R., Lungu, M., and Rotaru, C. (2011). “Non-linear adaptive system for the control of the helicopters pitch’s angle.” Proc. Romanian Acad. Ser. A Math. Phys. Tech. Sci. Inform. Sci., 12(2), 133–142.
Mahfouf, M., Linkens, D. A., and Kandiah, S. (1999). Fuzzy Takagi-Sugeno Kang model predictive control for process engineering, IEE Savoy Place Publisher, London.
MIT Open Courseware website. (2007). “Aircraft lateral autopilots.” Cambridge, MA.
Mori, R., and Suzuki, S. (2009). “Neural network modeling of lateral pilot landing control.” J. Aircraft, 46(5), 1721–1726.
Niewoenhner, R. J., and Kaminer, I. I. (1996). “Design of an autoland controller for an F-14 aircraft using H∞ synthesis.” J. Guidance Contr. Dynam., 19(3), 656–663.
Prasad, J. V. R., Calise, A. J., Pei, Y., and Corban, J. E. (1999). “Adaptive nonlinear controller synthesis and flight test evaluation on an unmanned helicopter.” IEEE Int. Conf. Control Application, Institute of Electrical and Electronics Engineers (IEEE), New Brunswick, NJ.
Sharma, M., and Calise, A. J. (2001). “Adaptive trajectory control for autonomous helicopters.” Proc., AIAA Guidance, Navigation and Control Conf., American Institute of Aeronautics and Astronautics (AIAA), Reston, VA.
Shao, L., Wang, J., and Shao, S. (2008). “Study on the fitting ways of artificial neural networks.” J. Coal Sci. Eng., 14(2), 334–337.
Tomescu, B. (2001). “The use of fuzzy logic to control paralleled DC-DC converters.” Ph.D. thesis, Virginia Polytechnic Institute and State Univ., Blacksburg, VA.
Tudosie, A. (2008). “Jet engine’s speed controller with constant pressure chamber.” Int. Conf. on Automation and Information (ICAI’08), World Scientific and Engineering Academy and Society (WSEAS), Stevens Point, WI, 229–234.
Zdenko, K., and Stjepan, B. (2006). Fuzzy controller design—Theory and applications, Taylor and Francis Group, London.
Zeng, S., and Zhu, J. (2006). “Adaptive compensated dynamic inversion control for a helicopter with approximate mathematical model.” Int. Conf. on Computational Intelligence for Modeling, Control and Automation, Institute of Electrical and Electronics Engineers (IEEE), New Brunswick, NJ.

Information & Authors

Information

Published In

Go to Journal of Aerospace Engineering
Journal of Aerospace Engineering
Volume 27Issue 5September 2014

History

Received: Mar 8, 2012
Accepted: Oct 15, 2012
Published online: Oct 17, 2012
Published in print: Sep 1, 2014
Discussion open until: Oct 6, 2014

Permissions

Request permissions for this article.

Authors

Affiliations

Romulus Lungu, Ph.D. [email protected]
Professor, Avionics Division, Univ. of Craiova, Decebal Blvd., No. 107, 200440, Romania. E-mail: [email protected]
Mihai Lungu, Ph.D. [email protected]
Lecturer, Avionics Division, Univ. of Craiova, Decebal Blvd., No. 107, 200440, Romania (corresponding author). E-mail: [email protected]

Metrics & Citations

Metrics

Citations

Download citation

If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.

Cited by

View Options

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Get Access

Access content

Please select your options to get access

Log in/Register Log in via your institution (Shibboleth)
ASCE Members: Please log in to see member pricing

Purchase

Save for later Information on ASCE Library Cards
ASCE Library Cards let you download journal articles, proceedings papers, and available book chapters across the entire ASCE Library platform. ASCE Library Cards remain active for 24 months or until all downloads are used. Note: This content will be debited as one download at time of checkout.

Terms of Use: ASCE Library Cards are for individual, personal use only. Reselling, republishing, or forwarding the materials to libraries or reading rooms is prohibited.
ASCE Library Card (5 downloads)
$105.00
Add to cart
ASCE Library Card (20 downloads)
$280.00
Add to cart
Buy Single Article
$35.00
Add to cart

Media

Figures

Other

Tables

Share

Share

Copy the content Link

Share with email

Email a colleague

Share