Adaptive Integral-Type Terminal Sliding Mode Control for Unmanned Aerial Vehicle Under Model Uncertainties and External Disturbances

This paper proposes an adaptive integral-type terminal sliding mode approach for the attitude and position tracking control of a quadrotor UAV subject to model uncertainties and external disturbances. First, an integral-type terminal sliding tracker is designed to attain the quadrotor UAV tracking performance in finite time when the upper bound of perturbations and uncertainties are known. Next, an adaptation law is proposed and a modified parameter-tuning integral-type terminal sliding mode tracking control scheme is designed to compensate of the model uncertainties and external disturbances. The stability and finite time convergence of the proposed approach is verified using the Lyapunov theory. Its performance is assessed using a simulation study encompassing various scenarios. Low chattering dynamics, fast convergence rate, and absence of singularities are the main features of the proposed approach.

[1]  Tang Pan,et al.  An integral TSMC-based adaptive fault-tolerant control for quadrotor with external disturbances and parametric uncertainties , 2020 .

[2]  M. Anwar Ma'sum,et al.  Simulation of intelligent Unmanned Aerial Vehicle (UAV) For military surveillance , 2013, 2013 International Conference on Advanced Computer Science and Information Systems (ICACSIS).

[3]  Anis Koubaa,et al.  Fast terminal sliding mode controller for high speed and complex maneuvering of unmanned aerial vehicles , 2021 .

[4]  Bernhard Rinner,et al.  Information Exchange and Decision Making in Micro Aerial Vehicle Networks for Cooperative Search , 2015, IEEE Transactions on Control of Network Systems.

[5]  Chao Deng,et al.  Adaptive fuzzy global sliding mode control for trajectory tracking of quadrotor UAVs , 2019, Nonlinear Dynamics.

[6]  Fangliang Chen,et al.  Detecting and tracking vehicles in traffic by unmanned aerial vehicles , 2016 .

[7]  Xiaoyu Shi,et al.  Adaptive fast terminal sliding mode (FTSM) control design for quadrotor UAV under external windy disturbances* , 2020, 2020 International Conference on Unmanned Aircraft Systems (ICUAS).

[8]  Cheolkeun Ha,et al.  Design of Synchronization Controller for the Station-Keeping Hovering Mode of Quad-Rotor Unmanned Aerial Vehicles , 2019 .

[9]  Pratap Tokekar,et al.  Sensor planning for a symbiotic UAV and UGV system for precision agriculture , 2013, 2013 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[10]  Quan Quan Introduction to Multicopter Design and Control , 2017 .

[11]  Mahdi Khodabandeh,et al.  Adaptive fractional order sliding mode control for a quadrotor with a varying load , 2019, Aerospace Science and Technology.

[12]  Saleh Mobayen,et al.  Adaptive sliding mode control for finite-time stability of quad-rotor UAVs with parametric uncertainties. , 2017, ISA transactions.

[13]  Wing-Kwong Wong,et al.  Adaptive Terminal Sliding Mode Control for Attitude and Position Tracking Control of Quadrotor UAVs in the Existence of External Disturbance , 2021, IEEE Access.

[14]  Hector Rios,et al.  Comparative analysis of continuous sliding-modes control strategies for quad-rotor robust tracking , 2019, Control Engineering Practice.

[15]  Nishchal K. Verma,et al.  Fast Terminal Sliding Mode Super Twisting Controller For Position And Altitude Tracking of the Quadrotor , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[16]  Shuai Wang,et al.  Multicopter Design and Control Practice , 2020 .

[17]  Moussa Labbadi,et al.  Robust adaptive backstepping fast terminal sliding mode controller for uncertain quadrotor UAV , 2019, Aerospace Science and Technology.

[18]  Moussa Labbadi,et al.  Adaptive Fractional-Order Nonsingular Fast Terminal Sliding Mode Based Robust Tracking Control of Quadrotor UAV With Gaussian Random Disturbances and Uncertainties , 2021, IEEE Transactions on Aerospace and Electronic Systems.

[19]  S. Mobayen,et al.  An adaptive fast terminal sliding mode control combined with global sliding mode scheme for tracking control of uncertain nonlinear third-order systems , 2015 .

[20]  A. Ahaitouf,et al.  A new robust adaptive sliding mode controller for quadrotor UAV flight , 2020, 2020 IEEE 2nd International Conference on Electronics, Control, Optimization and Computer Science (ICECOCS).

[21]  Zhankui Song,et al.  Adaptive compensation control for attitude adjustment of quad-rotor unmanned aerial vehicle. , 2017, ISA transactions.

[22]  Sergio Dominguez,et al.  L1 adaptive control for Wind gust rejection in quad-rotor UAV wind turbine inspection , 2017, 2017 International Conference on Unmanned Aircraft Systems (ICUAS).

[23]  Stuart Barr,et al.  Commercial Off-the-Shelf Digital Cameras on Unmanned Aerial Vehicles for Multitemporal Monitoring of Vegetation Reflectance and NDVI , 2017, IEEE Transactions on Geoscience and Remote Sensing.

[24]  Ahmed Abbou,et al.  Robust adaptive global nonlinear sliding mode controller for a quadrotor under external disturbances and uncertainties , 2020 .

[25]  Randal W. Beard,et al.  Decentralized Perimeter Surveillance Using a Team of UAVs , 2005, IEEE Transactions on Robotics.

[26]  Marcello Chiaberge,et al.  Multipurpose UAV for search and rescue operations in mountain avalanche events , 2017 .

[27]  Lei Xing,et al.  Fuzzy-logic-based adaptive event-triggered sliding mode control for spacecraft attitude tracking , 2021 .

[28]  Bo Li,et al.  Appointed-finite-time Control for Quadrotor UAVs with External Disturbances: An Adaptive Sliding Mode Observer based Approach , 2020, 2020 Chinese Control And Decision Conference (CCDC).

[29]  Hemerson Pistori,et al.  Identification of Soybean Foliar Diseases Using Unmanned Aerial Vehicle Images , 2017, IEEE Geoscience and Remote Sensing Letters.