Auto-landing of fixed wing unmanned aerial vehicles using the backstepping control.

The control of the unmanned aerial vehicles is a difficult problem because of their light weight and the strong coupling between the longitudinal and lateral modes. Motivated by this, a backstepping and dynamic inversion-based automatic landing system is designed in this paper for the flight control of a fixed wing unmanned aerial vehicle subject to wind shears, atmospheric disturbances, and wind gusts. Two backstepping-based controllers are designed for the stabilization of the attitude angles, while the controller associated to the forward velocity uses the dynamic inversion technique to obtain a constant forward velocity during all the three stages of landing. To provide an estimation of the wind shears, atmospheric turbulences, and wind gusts, a nonlinear disturbance observer is introduced in the control architecture. The lateral deviation with respect to the runway is canceled while the unmanned aerial vehicle maintains its desired trajectory slope angle. The novel adaptive automatic landing system is software implemented and validated by complex numerical simulations; the results of the numerical simulations prove the stability and robustness of the new control architecture for different initial conditions and wind type disturbances.

[1]  Mihai Lungu,et al.  Adaptive backstepping flight control for a mini‐UAV , 2013 .

[2]  Lucian Teodor Grigorie,et al.  ALSs with Conventional and Fuzzy Controllers Considering Wind Shear and Gyro Errors , 2013 .

[3]  Ligang Wu,et al.  Approximate Back-Stepping Fault-Tolerant Control of the Flexible Air-Breathing Hypersonic Vehicle , 2016, IEEE/ASME Transactions on Mechatronics.

[4]  Kuo-Chu Chang,et al.  UAV Path Planning with Tangent-plus-Lyapunov Vector Field Guidance and Obstacle Avoidance , 2013, IEEE Transactions on Aerospace and Electronic Systems.

[5]  Mihai Lungu,et al.  Automatic Control of Aircraft in Lateral‐Directional Plane During Landing , 2016 .

[6]  Vaios Lappas,et al.  Engineering Notes Online Evolutionary Swarm Algorithm for Self-Tuning Unmanned Flight Control Laws , 2015 .

[7]  Jun Zhang,et al.  Genetic Learning Particle Swarm Optimization , 2016, IEEE Transactions on Cybernetics.

[8]  Narasimhan Sundararajan,et al.  A fault-tolerant neural aided controller for aircraft auto-landing , 2006 .

[9]  Yang Yi-dong.  Analysis of the Approach Power Compensator System with Constant Angle of Attack , 2006 .

[10]  En-Hui Zheng,et al.  Position and attitude tracking control for a quadrotor UAV. , 2014, ISA transactions.

[11]  George A. Rovithakis,et al.  Prescribed Performance Tracking of a Variable Stiffness Actuated Robot , 2015, IEEE Transactions on Control Systems Technology.

[12]  Huaguang Zhang,et al.  A Comprehensive Review of Stability Analysis of Continuous-Time Recurrent Neural Networks , 2014, IEEE Transactions on Neural Networks and Learning Systems.

[13]  Cornel-Alexandru Brezoescu,et al.  Small lightweight aircraft navigation in the presence of wind , 2013 .

[14]  En-hui Zheng,et al.  Second order sliding mode control for a quadrotor UAV. , 2014, ISA transactions.

[15]  Yunpeng Ma,et al.  Prescribed performance control for automatic carrier landing with disturbance , 2018, Nonlinear Dynamics.

[16]  Gregory K. Egan,et al.  Robust μ-synthesis Loop Shaping for Altitude Flight Dynamics of a Flying-Wing Airframe , 2015, J. Intell. Robotic Syst..

[17]  Chen Wang,et al.  Trajectory Tracking Control for Quadrotor Robot Subject to Payload Variation and Wind Gust Disturbance , 2016, Journal of Intelligent & Robotic Systems.

[18]  D. M. McFarland,et al.  Non-linear system identification of the dynamics of aeroelastic instability suppression based on targeted energy transfers , 2010, The Aeronautical Journal (1968).

[19]  Sreenatha G. Anavatti,et al.  State-of-the-Art Intelligent Flight Control Systems in Unmanned Aerial Vehicles , 2018, IEEE Transactions on Automation Science and Engineering.

[20]  Ryota Mori,et al.  Neural Network Modeling of Lateral Pilot Landing Control , 2009 .

[21]  Wang Honglun,et al.  Back-stepping active disturbance rejection control design for integrated missile guidance and control system via reduced-order ESO. , 2015, ISA transactions.

[22]  Haibin Duan,et al.  Simplified brain storm optimization approach to control parameter optimization in F/A-18 automatic carrier landing system , 2015 .

[23]  Fendy Santoso,et al.  Modeling, Autopilot Design, and Field Tuning of a UAV With Minimum Control Surfaces , 2015, IEEE Transactions on Control Systems Technology.

[24]  Yew Chai Paw.  Synthesis and validation of flight control for UAV. , 2009 .

[25]  Mihai Lungu,et al.  Automatic control of aircraft lateral-directional motion during landing using neural networks and radio-technical subsystems , 2016, Neurocomputing.

[26]  Mihai Lungu,et al.  Application Of H2/H∞ Technique To Aircraft Landing Control , 2015 .

[27]  Alexandra Moutinho,et al.  Hover Control of an UAV With Backstepping Design Including Input Saturations , 2008, IEEE Transactions on Control Systems Technology.

[28]  W. Frost,et al.  Wind shear terms in the equations of aircraft motion , 1984 .

[29]  Zewei Zheng,et al.  Path Following of a Surface Vessel With Prescribed Performance in the Presence of Input Saturation and External Disturbances , 2017, IEEE/ASME Transactions on Mechatronics.

[30]  Radhakant Padhi,et al.  Autonomous Landing of Fixed Wing Unmanned Aerial Vehicle with Reactive Collision Avoidance , 2018 .