INVESTINGATION DOWNWARD WIND PRESSURE ON A SMALL QUADROTOR HELICOPTER

Yıl 2015, Cilt: 36 Sayı: 3, 174 - 189, 13.05.2015

Sadegh Rahmatı Amir Ghased

Öz

Abstract. Small rotary-wing UAVs are susceptible to gusts and other environmental disturbances that affect inflow at their rotors. Inflow variations cause unexpected aerodynamic forces through changes in thrust conditions and unmodeled blade-flapping dynamics. This pa­per introduces an onboard, pressure-based flow measurement system developed for a small quadrotor helicopter. The probe-based instrumentation package provides spatially dis­tributed airspeed measurements along each of the aircraft-fixed axes. Lateral and vertical windspeed estimates enable the development of disturbance-tolerant flight control strate­gies. The focus of this paper is vertical flow disturbances such as those caused by the downwash of a second vehicle. Real-time velocity measurements are incorporated into a recursive Bayesian estimator to localize a nearby rotorcraft using its downwash. A path planner developed for proximity flight is demonstrated through indoor flight testing with multiple vehicles to safely guide an instrumented quadrotor towards a goal point while avoiding another quadrotor.

Anahtar Kelimeler

Wind Pressure, Quadrotor Helıcopter

Kaynakça

• M. Belkhert, A. Rabhi, A. Hajjaji, and C, Pergard. Different Linearization control techniques for a quadrotor system. In end Int. on Communications, Computing and Control Applications, pages 1-6, December 2010.
• D. Alexander and S. Vogel. Nature’s Fkters: Birds, Insects, and the Bioechanies of Flight. Johns Hopking University Press, October 2004.
• M. Gewecke and Martin Woile. Breast feathers as an air-current senso organ for the control of flight behavior in a songbird (carduelisspinus). In ZeitschriftfrTierpsychologie,, volume 47, pages 203-298, 1978.
• R. Brown and M. Fedde. Airflow sensors in the avian wing. In Journal of Experimental Biology,, volume 179, pages 13-30, 1993.
• S. Herwitz, K. Allmendinger, R. slye, S. Dunagan, B. Lobitz, I. Johnson, and J. Brass. Nighttime UAV vineyard mission: Challenges of see-and-avoid in the NAS. In Proc. AIAA 3rd Unmanned Unlimited Conference, Workshop and Erhibit, pages 1-6 September 2004.
• R. Beard, D. Kingston, M. Quigley, D. Snyder, R. Christiansen, W. Johnson, T. Melain, and M. Goodrich. Autonomous vehicle technologies for small fixed wing UAVs. In AIAA Journal of Aerospace Computing, Information, and Communication, volume 2, page 92, January 2005.
• R. Hirokawa, D. Kubo, S. Suzuki, J. Meguro, and T. Suzuki. Small UAV for immediate hazard map generation. In AIAA Infotech @ Aerospace Conf, may 2007.
• F. Hsiao, Y. Ding. C. Chuang, C. Lin, and Y. Huang. The design of a small UAV system as a lest bed of formation flight. In AIAA Infotech@AerospaceConf, March 2011.
• R. Eubank, E. Athins, and D. Macy. Autonomous guidance and control of the flying fish ocean surveillance platform. In AIAA Infotech@AerspaceConf, April 2009.
• N. Rasmussen, B. Morso, and C. Taylor, Fixed-wing, mini-UAV system for aerial search operations. In AIAA Guidance Navigation and Control Conference and Exhibit, August 2007.
• P. Xie, A. Flores-Abad, G. Martinez, and O. Ma. Development of a small UAV with autopilot capability. In Proc. AIAA Atmosperic Flight Mechanics Conference, August 2011.
• M. Patel, Z. Sowle, T. Corke, and C. He. Autonomous sensing and control of wing stall using a smart plasma slat. In Proc, 44th AIAA Aerospace Sciences Meeting January 2006.
• P. Bowles and T. Corke. Stall detection on a leading-edge plasma actuated pitching airfoil utilizing onboard measurement. In Proc, 47th Aerospace Sciences Meeting, January 2009.
• Y. Xu, F. Jiang, S. Newbern, A. Huand, C. Ho, and Y. Tai. Flexible shear-stress sensor skin and its application to unmanned aerial vehicles. In Sensors and Actuators A: Physical , Volume 105. Pages 321-329, 2003.
• C. Gorsjean, G. Lee, W. Hong, Y. Tai, and C. Ho. Micro balloon actuators for aerodynamic control. In Micro Elector Mechanical Systems, The Eleventh Annual International Workshop on, pages 166-171. IEEF, January 1998.
• Air Force Office of Scientific Research (AFOSR) .Mutidisciplinary university research initiative (muri). W. Barnwell, Flight Control Using Distributed Actuation and Sensing . Master’s thesis, North Carolina state University USA, 2003.
• S. Lion, Control Authorities of a distributed Actuation and Sensing Array on a Blended- Wing-Body Uninhabites Aerial Vehicle. Master’s thesis, North Carolina State University, USA, 200 C. Hall. C. Cox, A. Gopalarathnam. Flight test of stable automated cruise flap for an adaptive wing aircraft. In journal of Aircraft, volume 47, pages 1178-1188, January 2009.
• D. Yeo, E. Atkins, L. Bernal, and W. Shyy. Aerodynamic sensing ofr a fixed wing uas operating at high angles of attack. In Proc. AIAA Atmosheric Flight Mechanics Conference, August, 2012.
• N. Sydney, B. Smyth, and D. A. Paley. Dynamic control of autonomous quadrotor flight in an estimated wind field. In Decision and Control (GDC), 2013 IEEE 52nd Annual Conference on, pages 3609-3616, Dec 2013.
• K. Alexis, G. Nikolakopoulos, and A. Tzes. Experimental model predictive attitude tracking control of a quadrotor helicopter subject to wind-gusts. In 18th Mediterranean Conf. on Control Automation (MED) , 2010. Pages 1461-1466, June 2010.
• K. Alexis, G. Nikolakopoulos, and A. Tzes. Constrained-control of a quadrotor helicopter for trajectory tracking under wind-gust disturbances. In MELECON 2010, pages 1411-1416, April 2010.
• C. Power, D. Mellinger, A. Kushleyev, B. Kothmann, and V. Kumar. Influence of aerodynamics and proximity effects in quadrotor flight. In Proc, of the Int. Symp. On Experimental Robotics, June 2012.
• F. White. Viscous Flud Flow. McGraw-Hill Mechanical Engineering 3 edition, January 200 R. Jenson M. Albertson, Y. Dai and H. Rouse. Diffusion of submerged jets. In Transactions of the American Socety of Civil Engineers, Volume 115, page 639-697, American Society of Civil Engineers, 1950.
• W. Khan, R. Carerly, and M. Nahon. Propeller slipstream model for small unmanned aerial vehicles. In AIAA Modelting and Simulation conference. AIAA, August 2013. Nomenclature u,v,w Velocity components, m/s Lu,wmh vwmhVelocity calibral ion factor ,wmhVelocity calibral ion factor i Port pressure, inH20 Air density, kg/m3 ρ β
• External source location vector z(tk) Flow speed measurement, vector A Posterior scaling constant µ Dynamic viscosity. kg/(ms) W Velocity constant Radial distance from center line r y,x Control input K Control gain J KJ Optimization weighting variable x.y Quadrotor position Subset ipt i A Time step s Disturbance source index