Nonlinear Robust Control of a New Reconfigurable Unmanned Aerial Vehicle

In this paper, a nonlinear robust Fast Terminal Sliding Mode Controller (FTSMC) is designed to control and stabilize a new reconfigurable Unmanned Aerial Vehicle (UAV) in the presence of uncertain and variable parameters. The studied UAV is an over-actuated system due the number of actuator control inputs. It can modify the length and the angles between its four arms in different ways, which result an important variation in its Center of Gravity (CoG), inertia, and control matrix. The proposed FTSMC offers many advantages such as, reaching the desired states in a finite-time unlike the conventional sliding mode, robustness vis-a-vis uncertain and unknown parameters, fast convergence towards the sliding surface, high accuracy and reducing the chattering phenomena. Furthermore, the closed-loop stability of the this UAV is ensured by the Lyapunov theory. The eight actuators used to rotate and extend the UAV arms are controlled by simple Proportional Integral Derivative (PID) controllers. Lastly, the robustness and efficiency of the proposed controller are evaluated through a flight scenario, where the UAV geometric parameters are variable over time.

[1]  Davide Scaramuzza,et al.  Geometry-aware Compensation Scheme for Morphing Drones , 2020, 2021 IEEE International Conference on Robotics and Automation (ICRA).

[2]  Daniel J. Inman,et al.  A Review of Morphing Aircraft , 2011 .

[3]  Mou Chen,et al.  Terminal sliding mode tracking control for a class of SISO uncertain nonlinear systems. , 2013, ISA transactions.

[4]  Srikanth Gururajan,et al.  Evaluation of a Baseline Controller for Autonomous “Figure-8” Flights of a Morphing Geometry Quadcopter: Flight Performance , 2019, Drones.

[5]  Xiumin Diao,et al.  Optimize Energy Efficiency of Quadrotors Via Arm Rotation , 2019, Journal of Dynamic Systems, Measurement, and Control.

[6]  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).

[7]  Esther Luna Colombini,et al.  Drone Reconfigurable Architecture (DRA): a Multipurpose Modular Architecture for Unmanned Aerial Vehicles (UAVs) , 2020, J. Intell. Robotic Syst..

[8]  Kei Okada,et al.  Aerial Regrasping: Pivoting with Transformable Multilink Aerial Robot , 2020, 2020 IEEE International Conference on Robotics and Automation (ICRA).

[9]  A B Shahriman,et al.  Design A New Model of Unmanned Aerial Vehicle Quadrotor Using The Variation in The Length of The Arm , 2017 .

[10]  Tufan Kumbasar,et al.  FOLLY: A Self Foldable and Self Deployable Autonomous Quadcopter , 2018, 2018 6th International Conference on Control Engineering & Information Technology (CEIT).

[11]  Yasser Bouzid,et al.  A Comprehensive Review on Reconfigurable Drones: Classification, Characteristics, Design and Control Technologies , 2021, Unmanned Syst..

[12]  Dario Floreano,et al.  The Foldable Drone: A Morphing Quadrotor That Can Squeeze and Fly , 2019, IEEE Robotics and Automation Letters.

[13]  Y. Bouzid,et al.  Design and Modeling of Unconventional Quadrotors , 2020, 2020 28th Mediterranean Conference on Control and Automation (MED).

[14]  Esther Luna Colombini,et al.  A Novel Architecture for Multipurpose Reconfigurable Unmanned Aerial Vehicle (UAV): Concept, Design and Prototype Manufacturing , 2018, 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE).

[15]  Hooman Hedayati,et al.  PufferBot: Actuated Expandable Structures for Aerial Robots , 2020, 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[16]  David Hyunchul Shim,et al.  BAXTER: Bi-modal Aerial-Terrestrial Hybrid Vehicle for Long-endurance Versatile Mobility: Preprint Version , 2021, ISER.

[17]  Tugrul Oktay,et al.  Non Simultaneous Morphing System Desing for Quadrotors , 2019 .

[18]  Paolo Ermanni,et al.  Composite additive manufacturing of morphing aerospace structures , 2020 .

[19]  Mark W. Mueller,et al.  Design and Control of a Passively Morphing Quadcopter , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[20]  D. A. Wallace,et al.  Dynamics and Control of a Quadrotor with Active Geometric Morphing , 2016 .

[21]  Yahya H. Zweiri,et al.  Design and Implementation of a Dual-Axis Tilting Quadcopter , 2018, Robotics.

[22]  Ujjar Bhandari,et al.  The Design of Prometheus: A Reconfigurable UAV for Subterranean Mine Inspection , 2020, Robotics.

[23]  R. Eberhart,et al.  Empirical study of particle swarm optimization , 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

[24]  David Zarrouk,et al.  Flying STAR, a Hybrid Crawling and Flying Sprawl Tuned Robot , 2019, 2019 International Conference on Robotics and Automation (ICRA).

[25]  S. H. DERROUAOUI,et al.  Dynamic Modeling of a Transformable Quadrotor , 2020, 2020 International Conference on Unmanned Aircraft Systems (ICUAS).

[26]  Daniel Pastor,et al.  Design of a Ballistically-Launched Foldable Multirotor , 2019, 2019 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[27]  Valentin Riviere,et al.  Agile Robotic Fliers: A Morphing-Based Approach , 2018, Soft robotics.

[28]  George Nikolakopoulos,et al.  Geometry Aware NMPC Scheme for Morphing Quadrotor Navigation in Restricted Entrances , 2021, 2021 European Control Conference (ECC).

[29]  F. Ruffier,et al.  X-Morf: A crash-separable quadrotor that morfs its X-geometry in flight , 2017, 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS).

[30]  Wan Khairunizam,et al.  Effects of Variable Arm Length on UAV Control Systems , 2020 .