Nonlinear control of a quadrotor for attitude stabilization

The design of attitude controllers for UAVs is a challenging problem due to the high nonlinearities of the plant and its inherent instability. This work presents the development of a nonlinear controller based on Lyapunov theory in order to achieve a robust tracking for the orientation of a quadcopter. Based on a typical model, the inclusion of error integrals in the Lyapunov functions allow the UAV to achieve the desired set points without steady state error despite of changes in plant parameters and sensors noise. The results are compared in simulations to another nonlinear controller to show the robustness of the proposed strategy to disturbance in plant and outputs.

[1]  Karim Salahshoor,et al.  Attitude flight control system design of UAV using LQG\LTR multivariable control with noise and disturbance , 2015, 2015 3rd RSI International Conference on Robotics and Mechatronics (ICROM).

[2]  Wang Honglin,et al.  Backstepping-based attitude control for a quadrotor UAV using nonlinear disturbance observer , 2015, 2015 34th Chinese Control Conference (CCC).

[3]  Abdelhamid Tayebi,et al.  Attitude stabilization of a VTOL quadrotor aircraft , 2006, IEEE Transactions on Control Systems Technology.

[4]  Yanmin Chen,et al.  Modeling and Control of a Quadrotor Helicopter System under Impact of Wind Field , 2013 .

[5]  Fei Qing,et al.  Attitude control research for quad-rotor UAV , 2014, Fifth International Conference on Intelligent Control and Information Processing.

[6]  Min Han,et al.  PID and neural net controller performance comparsion in UAV pitch attitude control , 2016, 2016 IEEE International Conference on Systems, Man, and Cybernetics (SMC).

[7]  Hyo-Sung Ahn,et al.  Nonlinear Control of Quadrotor for Point Tracking: Actual Implementation and Experimental Tests , 2015, IEEE/ASME Transactions on Mechatronics.

[8]  Lu Wang,et al.  Anti-disturbance control methodology for attitude tracking of an UAV , 2015, 2015 IEEE International Conference on Robotics and Biomimetics (ROBIO).

[9]  Kenzo Nonami,et al.  Autonomous Flying Robots , 2010 .

[10]  Aleksandar Rakic,et al.  Simple fuzzy solution for quadrotor attitude control , 2014, 12th Symposium on Neural Network Applications in Electrical Engineering (NEUREL).

[11]  Sina Rezazadeh,et al.  Optimal attitude control of a quadrotor UAV using Adaptive Neuro-Fuzzy Inference System (ANFIS) , 2013, The 3rd International Conference on Control, Instrumentation, and Automation.