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Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control


Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control

Qiao, Jing (2018) Trajectory Tracking and Payload Dropping of an Unmanned Quadrotor Helicopter Based on GS-PID and Backstepping Control. Masters thesis, Concordia University.

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Two useful control techniques, the Gain-Scheduled Proportional-Integral-Derivative (GS-PID) control and backstepping control, have been applied by using quadrotor Unmanned Aerial Vehicle (UAV) in the applications of trajectory tracking and payload dropping operations in this thesis. These control algorithms are analyzed and verified through software simulations and experimental tests.
The dynamic model of the quadrotor UAV is firstly established using Newton-Euler laws. The quadrotor comes with a symmetric, nonlinear and multiple-input-multiple output (MIMO) dynamic model.
The GS-PID control algorithm is implemented firstly in take-off, trajectory tracking, payload dropping, and landing periods of flight in trajectory tracking and payload dropping scenarios.
Unlike other control algorithms that tend to linearize nonlinear systems, backstepping works without cancelling the nonlinearities in the system. This leads to more flexible designs of the control model. The backstepping control is implemented in this thesis for better performance of the quadrotor UAV for the two scenarios as well. Both control algorithms are implemented on the parameters of an unmanned quadrotor helicopter platform known as Qball-X4 available at the Networked Autonomous Vehicles Lab (NAVL) of Concordia University.
Using MATLAB/Simulink to build the simulation control model, the flight simulation of the Qball-X4 is carried out for the trajectory tracking and the payload dropping. In order to further investigate these two control approaches, the Qball-X4 is used for experimental verification on payload dropping performance. The results indicate that both algorithms can obtain acceptable performance, but the backstepping controller proves to be a better performed one.

Divisions:Concordia University > Gina Cody School of Engineering and Computer Science > Mechanical, Industrial and Aerospace Engineering
Item Type:Thesis (Masters)
Authors:Qiao, Jing
Institution:Concordia University
Degree Name:M.A. Sc.
Program:Mechanical Engineering
Date:June 2018
Thesis Supervisor(s):Zhang, Youmin
Keywords:Quadrotor UAV, Trajectory tracking,Payload dropping, Gain-Scheduled (GS) PID, Backstepping control
ID Code:984022
Deposited By: JING QIAO
Deposited On:16 Nov 2018 16:28
Last Modified:16 Nov 2018 16:28


[1]Y. M. Zhang, A. Chamseddine, C. A. Rabbath, B. W. Gordon, C.-Y. Su, S. Rakheja, C. Fulford, J. Apkarian, and P. Gosselin, Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed, J. Franklin Inst. 350(9) (2013) 2396– 2422.
[2]F. Lin, K. Z. Y. Ang, F. Wang, B. M. Chen, T. H. Lee, B. Yang, M. Dong, X. Dong, J. Cui, S. K. Phang, B. Wang, D. Luo, K. Peng, G. Cai, S. Zhao, M. Yin, and K. Li, Development of an unmanned coaxial rotorcraft for the DARPA UAV Forge challenge, Unmanned Syst. 1(2) (2013) 211–245.
[3]J. Keller, D. Thakur, V. Dobrokhodov, K. Jones, M. Pivtoraiko, J. Gallier, I. Kaminer, and V. Kumar, A computationally efficient approach to trajectory management for coordinated aerial surveillance, Unmanned Syst. 1(1) (2013) 59–74.
[4]P. C. Niedfeldt, B. T. Carroll, J. A. Howard, R. W. Beard, B. S. Morse, and S. Pledgie, Enhanced UAS surveillance using a video utility metric, Unmanned Syst. 1(2) (2013) 277–296.
[5]C. C. Haddal and J. Gertler, Homeland security: Unmanned aerial vehicles and border surveillance, CRS Report for Congress, Congressional Research Service (2010).
[6]J. Hu, J. Xu, and L. Xie, Cooperative search and exploration in robotic networks, Unmanned Syst. 1(1) (2013) 121–142.
[7]M. K. Habib and Y. Baudoin, Robot-assisted risky intervention, search, rescue and environmental surveillance, Int. J. Adv. Robot. Syst. 7(1) (2010) 1–8.
[8]T. Skrzypietz, Unmanned aircraft systems for civilian missions, BIGS Policy Paper No. 1 (2012).
[9]R. W. Beard, T. W. McLain, D. B. Nelson, D. Kingston, and D. Johanson, Decentralized cooperative aerial surveillance using fixed-wing miniature UAVs, Proc. IEEE 94(7) (2006) 1306–1324.
[10]D. W. Casbeer, D. B. Kingston, R. W. Beard, and T. W. McLain, Cooperative forest fire surveillance using a team of small unmanned air vehicles, Int. J. Syst. Sci. 37(6) (2006) 351–360.
[11]H. Dieter, Z. Werner, S. Gunter, and S. Peter, Monitoring of gas pipelines: A civil UAV application, Aircraft Eng. Aerosp. Technol. 77(5) (2005) 352–360.
[12]S. Magazine (2007), Available at http://findarticles.com/p/ articles/mi m0OXU/is 5 62/ai n27236124/ (Accessed on 3 November 2012)
[13]B. Erginer and E. Altug, Modeling and PD control of a quadrotor VTOL vehicle, IEEE Intelligent Vehicles Symp. (2007), pp. 894–899.
[14]A. Wahyudie, T. B. Susilo, and H. Noura, Robust PID controller for quad-rotors, J. Unmanned Syst. Technol. 1(1) (2013) 14–19.
[15]K. Oner, E. Cetinsoy, M. Unel, M. Aksit, I. Kandemir and K. Gulez, Dynamic model and control of a new quadrotor UAV with tilt-wing mechanism, World Academy of Science, Engineering and Technology (2008).
[16]M. O. Efe, Robust low altitude behavior control of a quadrotor rotorcraft through sliding modes, Mediterranean Conf. on Control and Automation (2007).
[17]H. Bouadi, M. Bouchoucha, and M. Tadjine, Sliding mode control based on backstepping approach for an UAV type-quadrotor, World Academy of Science, Engineering and Technology (2007).
[18]M. Abdolhosseini, Y. M. Zhang and C. A. Rabbath, An efficient model predictive control scheme for an unmanned quadrotor helicopter, J. Int. Robot. Syst. 70(1) (2013) 27–38.
[19]T. Madani and A. Benallegue, Backstepping control for a quadrotor helicopter. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, 9-15 October 2006, 3255-3260.
[20]De Bothezat, Helicopter: development history, photos, technical data. http://www.aviastar.org/ helicopters_eng/bothezat.php
[21]P. McKerrow, Modelling the draganflyer four-rotor helicopter. In Proceedings of the 2004 IEEE International Conference Robotics and Automation, 2004.
[22]R. K. Arning and S. Sassen. Flight control of micro aerial vehicles. In AIAA Guidance, Navigation, and Control Conference and Exhibit, 2004
[23]P. Pounds, J. Gresham, R. Mahony, J. Robert, and P. Corke. Towards dynamically favourable quad-rotor aerial robots. Proceedings of the Australasian Conference on Robotics and Automation, Canberra, ACT, Australia, 2004.
[24]P. Pounds, R. Mahony and P. Corke, Modelling and control of a quad-rotor, Proceedings of the Australasian Conference on Robotics and Automation, Auckland, New Zealand., December 2006
[25]E. Altu, J. P. Ostrowski, and R. Mahony, Control of a quadrotor helicopter using visual feedback, Proceedings of the 2002 IEEE International Conference on Robotics and Automation, Washington, D.C, May 2002, pp 72-77
[26]E. Altu, J. P. Ostrowski, and C. Taylor, Quadrotor control using dual visual feedback. Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), Taipei, Taiwan, September 2003, pp. 4294-4299.
[27]Matthew G. Earl and Raffaello D’Andrea. Real-time attitude estimation technique applied to a quadrotor helicopter. Proceedings of the 43rd IEEE Conference on Decision and Control, 2004.
[28]E. B. Nice, Design of a Quadrotor Hovering Vehicle, Master Thesis, Cornell University, May, 2004
[29]S. Bouabdallah, A. Noth, and R. Siegwan. PID vs. LQ control techniques applied to an indoor micro quadrotor. Proceedings of 2004 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2004.
[30]G. Hoffmann, D. G. Rajnarayan, S. L. Waslander, D. Dostal, J. S. Jang, and C. J. Tomlin. The Standard Testbed of Autonomous Rotorcraft for Multi Agent Control (STARMAC). Proceedings of the 23rd Digital Avionics Systems Conference, 2004.
[31]M. Chen and M. Huzmezan, A combined MBPC/ 2 DOF H∞ controller for a quadrotor UAV, 2003 AIAA Guidance, Navigation, and Control Conference
[32]H. K. Khallil, Nonlinear Systems (3rd Edition), Prentice Hall, 2003
[33]J. D. Nicoud and J. C. Zufferey, Toward indoor flying robots, IEEE Conf.on Robots and Systems,2002: 787-792.
[34]S. Bouabdallah and R. Siegwart. Towards intelligent miniature flying robots.Proceeding of Field and Service Robotics, Australia, Port Douglas, 2005: 429-440.
[35]R. Olfati-Saber, Nonliner control of underactuated mechanical system with application to robotics and aerospace vehicles, MIT, 2001.
[36]F. Bin, S. Jia, and Y. Yao, An LQR controller for quadrotor: design and experiment, The 31st Youth Academic Annual Conference of Chinese Association of Automation, Wuhan, 2016: 81-86.
[37]L. Besnard, Y. B. Shtessel, and B. Landrum, Quadrotor vehicle control via sliding mode controller driven by sliding mode disturbance observer, Journal of the Franklin Institute, 2012, 349(2):658-684.
[38]A. Das, F. Lewis, and K. Subbarao, Backstepping approach for controlling a quadrotor using Lagrange form dynamics, Journal of Intelligent and Robotic System: Theory and Application, 2009, 56(1-2):127-151
[39]B. T. Whitehead, and S. R. Bieniawski, Model reference adaptive control of a quadrotor UAV, AIAA Guidance Navigation and Control Conference. Toronto, 2010:1-13.
[40]H. H. Wang, Y. M. Zhang, Y. M. Yi, et al, Nonlinear Tracking control method applied to Qball-4X quadrotor UAV against actuator faults, Proceedings of the 28th Chinese Control and Decision Conference. Yinchuan, 2016: 3478-3483.
[41]B. Yu, Y. M. Zhang, I. Minchala, et al. Fault-tolerant control with linear quadratic and model predictive control techniques against actuator faults in a quadrotor UAV, 2nd International Conference on Control and Fault-Tolerant System, Nice, 2013: 661-666.
[42]Z. X. Liu, C. Yuan, Y. M. Zhang, et al, A learning-based fault tolerant tracking control of an unmanned quadrotor helicopter. Journal of Intelligent and Robotic Systems, 2016, 84(1-4): 145-162.
[43]H. L. Yang, B. Jiang, and K. Zhang, Direct self-repairing control of the quadrotor helicopter based on adaptive sliding mode control technique, Proceedings of 2014 IEEE Chinese Guidance Navigation and Control Conference, 2014: 1403-1408.
[44]Z. H. Cen, H. Noura, T. Susilo, et al, Engineering implementation on fault diagnosis for quadrotors based on nonlinear observer, The 25th Chinese control and Decision Conference, Guiyang, 2013: 2971-2975.
[45]A. Drak, H. Noura, and M. Hejase, Sensor fault diagnostic and fault-tolerant control for the altitude control of a quadrotor UAV, 2015 IEEE 8th GCC Conference and Exhibition. Muscat, 2015: 1-5.
[46]Swiss Meteomatics new patent [EB/OL]. (2017-03-01) /[2017-04-03]. http://www.81uav.cn/ UAV-news/201703/01/23200.html.
[47]I. Sadeghzadeh, A. Mehta, A. Chamseddine, et al. Active fault tolerant control of a quadrotor UAV based on gain-scheduled PID control, the 25th IEEE Canadian Conference on Electrical and Computer Engineering, Montreal, 2012: 1-4.
[48]J. H. Lee, Model predictive control: Review of the three decades of development, Int. J. Control, Autom. Syst. 9(3) (2011) 415–424.
[49]V. Santibanez and R. Kelly, A class of nonlinear PID global regulators of robot manipulators, in Proc. IEEE Int. Conf. Robotics and Automation (1998), pp. 3601–3608.
[50]D. Sun, S. Hu, X. Shao, and C. Liu, Global stability of a saturated nonlinear PID controller for robot manipulators, IEEE Trans. Control Syst. Technol. 17 (2009) 892–899.
[51]A. Loria, E. Lefeber, and H. Nijmeijer, Global asymptotic stability of robot manipulators with linear PID and PI 2D Control, SACTA 3(2) (2000) 138–149.
[52]A. Yarza, V. Santibanez, and J. Moreno-Valenzuela, Global asymptotic stability of the classical PID controller by considering saturation effects in industrial robots, Int. J. Adv. Robot. Syst. 8(4) (2011) 34–42.
[53]P. Rocco, Stability of PID control for industrial robot arms, IEEE Trans. Robot. Autom. 12(4) (1996) 606–614.
[54]M. Lazar, W. P. M. H. Heemels, A. Bemporad, and S. Weiland, Discrete time non-smooth nonlinear MPC: Stability and robustness, in Assessment and Future Directions of Nonlinear Model Predictive Control, eds. R. Findeisen, et al, Lecture Notes in Control and Information Sciences, Vol. 358 (Springer, 2007), pp. 93–103.
[55]E. Siva, P. Goulart, J. Maciejowski, and N. Kantas, Stability of model predictive control using Markov chain Monte Carlo optimisation, in Proc. European Control Conf. (2009).
[56]D. Mayne, Nonlinear and Adaptive Control Design [Book Review]. IEEE Transactions on Automatic Control, 2002, 41(12):1849.
[57]R. Hull, D. Schumacher, and Z.Qu, Design and evaluation of robust nonlinear missile autopilots from a performance perspective, Proceedings of the IEEE American Control Conference, 1995: 189-193.
[58]M. Steinberg and A. Page, Nonlinear adaptive flight control with a backstepping design approach, 1998.
[59]M. L. Steinberg. Comparison of intelligent, adaptive, and nonlinear flight control laws. Journal of Guidance Control & Dynamics, 2001, 24(4): 12.
[60]M. Krstic, I. Kanellakopoulos, and P. V. Kokotovic, Nonlinear design of adaptive controllers for linear systems. IEEE Transactions on Automatic Control, 2002, 39(4): 738-752.
[61]T. Lee and Y. Kim, Nonlinear adaptive flight control using backstepping and neural networks controller. Journal of Guidance Control & Dynamics, 2012, 24(4): 675-682.
[62]S. John, Artificial intelligent-based feedforward optimized PID wheel slip controller. AFRICON, 12 September 2013, Pointe-Aux-Piments, 1-6.
[63]K. U. Lee, H. S. Kim, J. B. Park, and Y. H. Choi, Hovering control of a quadrotor. The 12th International Conference on Control, Automation and Systems (ICCAS), 17-21 October 2012, 162-167.
[64]J. Li and Y. Li, Dynamic analysis and PID control for a quadrotor. International Conference on Mechatronics and Automation (ICMA), 7-10 August 2011, 573-578.
[65]T. Madani and A. Benallegue, Backstepping control for a quadrotor helicopter. Proceedings of the 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, Beijing, 9-15 October 2006, 3255-3260.
[66]X. Huo, M. Huo, and H. R. Karimi, Attitude stabilization control of a quadrotor UAV by using backstepping approach. Mathematical Problems in Engineering, 2014, 1-9.
[67]Z. Fang and W. Gao, Adaptive integral backstepping control of a micro-quadrotor. Proceedings of the 2nd International Conference on Intelligent Control and Information Processing (ICICIP), Harbin, 25-28 July 2011, 910-915.
[68]J. M. Maciejowski, Predictive Control with Constraints, Prentice Hall, Pearson Education Limited, Harlow, UK, 2002.
[70]S. Bennett, A History of Control Engineering 1930-1955. IET 1993. pp. 48
[71]S. Bouabdallah and R. Siegwart. Backstepping and sliding-mode techniques applied to an indoor micro quadrotor. Proceedings of the 2005 IEEE International Conference on Robotics and Automation, 2247-2252.
[72]A. Nagaty, S. Saeedi, C. Thibault, M. Seto, and H. Li, Control and navigation framework for quadrotor helicopters. Journal of Intelligent and Robotic Systems, 70(1-4):1-12, 2013.
[73]Quaser, Quanser Qball-X4, User Manual, 2010.
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