Nonlinear tracking control methods applied to Qball-X4 quadrotor UAV against actuator faults

This work is dedicated to the robust tracking control problem for an unmanned aerial vehicle (UAV) in the presence of disturbances and actuator partial faults. Two nonlinear control strategies, which include sliding mode control (SMC) and backstepping control (BSC), are investigated and tested on a multi-input multi-output (MIMO) nonlinear quadrotor helicopter system: Qball-X4. For comparison and verifying the capability of the developed algorithms, a linear quadratic regulator (LQR) controller with integral action is also implemented and tested on a real quadrotor vehicle. The MATLAB/Simulink simulation testing results for the conditions without propeller fault, and with partial faults in all four propellers show that SMC and BSC possess strong robustness for dealing with disturbances and system uncertainties induced by faults. The real flight experiments using SMC and LQR algorithms are realized and the results further indicate that SMC has stronger robustness than LQR for dealing with disturbances and system uncertainties.

[1]  Q. Hu,et al.  Fault-Tolerant Tracking Control of Spacecraft with Attitude-Only Measurement Under Actuator Failures , 2014 .

[2]  Robert E. Mahony,et al.  Landing a VTOL Unmanned Aerial Vehicle on a Moving Platform Using Optical Flow , 2012, IEEE Transactions on Robotics.

[3]  Youmin Zhang,et al.  Adaptive Sliding Mode Fault Tolerant Attitude Tracking Control for Flexible Spacecraft Under Actuator Saturation , 2012, IEEE Transactions on Control Systems Technology.

[4]  Ümit Özgüner,et al.  Sliding mode control of a class of underactuated systems , 2008, Autom..

[5]  Y. M. Zhang,et al.  A learning-based fuzzy LQR control scheme for height control of an unmanned quadrotor helicopter , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[6]  Hassan Noura,et al.  Active fault tolerant control of quadrotor UAV using Sliding Mode Control , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[7]  Rafael Castro,et al.  Quadrotors flight formation control using a leader-follower approach , 2013, 2013 European Control Conference (ECC).

[8]  C.J.B. Macnab,et al.  Robust neural network control of a quadrotor helicopter , 2008, 2008 Canadian Conference on Electrical and Computer Engineering.

[9]  Anthony J. Calise,et al.  Adaptive Output Feedback for High-Bandwidth Control of an Unmanned Helicopter , 2001 .

[10]  Abdelhamid Rabhi,et al.  Model-free control of a quadrotor vehicle , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).

[11]  Roland Siegwart,et al.  Backstepping and Sliding-mode Techniques Applied to an Indoor Micro Quadrotor , 2005, Proceedings of the 2005 IEEE International Conference on Robotics and Automation.

[12]  Youmin Zhang,et al.  Development of advanced FDD and FTC techniques with application to an unmanned quadrotor helicopter testbed , 2013, J. Frankl. Inst..

[13]  Abdelaziz Benallegue,et al.  Backstepping Control for a Quadrotor Helicopter , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[14]  Youmin Zhang,et al.  Sliding mode fault tolerant control dealing with modeling uncertainties and actuator faults. , 2012, ISA transactions.

[15]  Bin Xian,et al.  Nonlinear robust output feedback tracking control of a quadrotor UAV using quaternion representation , 2015 .

[16]  Niels Kjølstad Poulsen,et al.  An MPC approach to individual pitch control of wind turbines using uncertain LIDAR measurements , 2013, 2013 European Control Conference (ECC).

[17]  Frank L. Lewis,et al.  Dynamic inversion with zero-dynamics stabilisation for quadrotor control , 2009 .

[18]  C. Cozaa,et al.  Adaptive fuzzy control for a quadrotor helicopter robust to wind buffeting , 2012 .

[19]  D. Theilliol,et al.  Robust sensor fault diagnosis and tracking controller for a UAV modelled as LPV system , 2014, 2014 International Conference on Unmanned Aircraft Systems (ICUAS).