Hostname: page-component-586b7cd67f-g8jcs Total loading time: 0 Render date: 2024-11-28T07:07:32.612Z Has data issue: false hasContentIssue false

Towards a new design with generic modeling and adaptive control of a transformable quadrotor

Published online by Cambridge University Press:  08 July 2021

S.H. Derrouaoui*
Affiliation:
Complex Systems Control and Simulators (CSCS) Laboratory Ecole Militaire Polytechnique Bordj el Bahri, AlgiersAlgeria
Y. Bouzid
Affiliation:
Complex Systems Control and Simulators (CSCS) Laboratory Ecole Militaire Polytechnique Bordj el Bahri, AlgiersAlgeria
M. Guiatni
Affiliation:
Complex Systems Control and Simulators (CSCS) Laboratory Ecole Militaire Polytechnique Bordj el Bahri, AlgiersAlgeria

Abstract

Recently, transformable Unmanned Aerial Vehicles (UAVs) have become a subject of great interest in the field of flying systems, due to their maneuverability, agility and morphological capacities. They can be used for specific missions and in more congested spaces. Moreover, this novel class of UAVs is considered as a viable solution for providing flying robots with specific and versatile functionalities. In this paper, we propose (i) a new design of a transformable quadrotor with (ii) generic modeling and (iii) adaptive control strategy. The proposed UAV is able to change its flight configuration by rotating its four arms independently around a central body, thanks to its adaptive geometry. To simplify and lighten the prototype, a simple mechanism with a light mechanical structure is proposed. Since the Center of Gravity (CoG) of the UAV moves according to the desired morphology of the system, a variation of the inertia and the allocation matrix occurs instantly. These dynamics parameters play an important role in the system control and its stability, representing a key difference compared with the classic quadrotor. Thus, a new generic model is developed, taking into account all these variations together with aerodynamic effects. To validate this model and ensure the stability of the designed UAV, an adaptive backstepping control strategy based on the change in the flight configuration is applied. MATLAB simulations are provided to evaluate and illustrate the performance and efficiency of the proposed controller. Finally, some experimental tests are presented.

Type
Research Article
Copyright
© The Author(s), 2021. Published by Cambridge University Press on behalf of Royal Aeronautical Society

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Gupte, S., Mohandas, P.I.T. and Conrad, J.M. A survey of quadrotor unmanned aerial vehicles, 2012 Proceedings of IEEE Southeastcon, 2012, pp 16.CrossRefGoogle Scholar
Puri, A. A survey of unmanned aerial vehicles (UAV) for traffic surveillance, 2005, pp 129, Department of Computer Science and Engineering, University of South Florida.Google Scholar
Derafa, L., Ouldali, A., Madani, T. and Benallegue, A. Non-linear control algorithm for the four rotors UAV attitude tracking problem, Aeronaut. J., 2011, 115, (1165), pp 175185.CrossRefGoogle Scholar
Floreano, D. and Wood, R.J. Science, technology and the future of small autonomous drones, Nature, 2015, 521, (7553), pp 460466.CrossRefGoogle Scholar
Mintchev, S. and Floreano, D. Adaptive morphology: A design principle for multimodal and multifunctional robots, IEEE Rob. Autom. Mag., 2016, 23, (3), pp 4254.CrossRefGoogle Scholar
Caballero, A., Suarez, A., Real, F., Vega, V.M., Bejar, M., RodriguezCastano, A. and Ollero, A. First experimental results on motion planning for transportation in aerial long-reach manipulators with two arms, 2018 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2018, pp 84718477.CrossRefGoogle Scholar
Yilmaz, E., Zaki, H. and Unel, M. Nonlinear adaptive control of an aerial manipulation system, 2019 18th European Control Conference (ECC), 2019, pp 39163921.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M., Dib, I. and Moudjari, N. Design and modeling of unconventional quadrotors, 2020 28th Mediterranean Conference on Control and Automation (MED), IEEE, 2020, pp 721726.Google Scholar
Zhao, M., Kawasaki, K., Okada, K. and Inaba, M. Transformable multirotor with two-dimensional multilinks: modeling, control, and motion planning for aerial transformation, Adv. Rob., 2016, 30, (13), pp 825845.CrossRefGoogle Scholar
Falanga, D., Kleber, K., Mintchev, S., Floreano, D. and Scaramuzza, D. The foldable drone: A morphing quadrotor that can squeeze and fly, IEEE Rob. Autom. Lett., 2018, 4, (2), pp 209216.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M., Halfaoui, K., Dib, I. and Moudjari, N. Backstepping controller applied to a foldable quadrotor for 3D trajectory tracking, Proceedings of the 17th International Conference on Informatics in Control, Automation and Robotics, 2020, pp 537544.CrossRefGoogle Scholar
Mintchev, S., Shintake, J. and Floreano, D. Bioinspired dual-stiffness origami, Sci. Rob., 2018, 3, (20).Google ScholarPubMed
Wallace, D.A., Dynamics and Control of a Quadrotor with Active Geometric Morphing, PhD Dissertation, University of Washington, 2016.Google Scholar
Kornatowski, P.M., Feroskhan, M., Stewart, W.J. and Floreano, D. A morphing cargo drone for safe flight in proximity of humans, IEEE Rob. Autom. Lett., 2020, 5, (3), pp 42334240.CrossRefGoogle Scholar
Bucki, N. and Mueller, M.W. Design and control of a passively morphing quadcopter, 2019 International Conference on Robotics and Automation (ICRA), 2019, pp 91169122.CrossRefGoogle Scholar
Sakaguchi, A., Takimoto, T. and Ushio, T. A novel quadcopter with a tilting frame using parallel link mechanism, 2019 International Conference on Unmanned Aircraft Systems (ICUAS), 2019, pp 674683.CrossRefGoogle Scholar
Zhao, N., Luo, Y., Deng, H. and Shen, Y. The deformable quadrotor: design, kinematics and dynamics characterization, and flight performance validation, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, pp 23912396.CrossRefGoogle Scholar
Riviere, V., Manecy, A. and Viollet, S. Agile robotic fliers: A morphing-based approach, Soft Rob., 2018, 5, (5), pp 541553.CrossRefGoogle ScholarPubMed
Zhao, M., Anzai, T., Shi, F., Chen, X., Okada, K. and Inaba, M. Design, modeling, and control of an aerial robot dragon: A dual-rotorembedded multilink robot with the ability of multi-degree-of-freedom aerial transformation, IEEE Rob. Autom. Lett., 2018, 3, (2), pp 11761183.CrossRefGoogle Scholar
Fabris, A., Kleber, K., Falanga, D. and Scaramuzza, D. Geometry aware compensation scheme for morphing drones, arXiv preprint arXiv:2003.03929, 2020.Google Scholar
Invernizzi, D., Giurato, M., Gattazzo, P. and Lovera, M. Comparison of control methods for trajectory tracking in fully actuated unmanned aerial vehicles, IEEE Trans. Control Syst. Technol., 2021, 29, (3), pp 11471160. doi: 10.1109/TCST.2020.2992389.CrossRefGoogle Scholar
Rohr, D., Stastny, T., Verling, S. and Siegwart, R. Attitude and cruise control of a vtol tiltwing uav, IEEE Rob. Autom. Lett., 2019, 4, (3), pp 26832690.CrossRefGoogle Scholar
Li, G., Gabrich, B., Saldana, D., Das, J., Kumar, V. and Yim, M. Modquad-vi: A vision-based self-assembling modular quadrotor, 2019 International Conference on Robotics and Automation (ICRA), 2019, pp 346352.CrossRefGoogle Scholar
Derrouaoui, S.H., Bouzid, Y., Guiatni, M. and Dib, I. A comprehensive review on reconfigurable drones: Classification, characteristics, design and control technologies, Unmanned Syst., 2021, 9, (3), pp 127.Google Scholar
Bai, Y. and Gururajan, S. Evaluation of a baseline controller for autonomous “figure-8” flights of a morphing geometry quadcopter: Flight performance, Drones, 2019, 3, (3), p 70.CrossRefGoogle Scholar
Avant, T., Lee, U., Katona, B. and Morgansen, K. Dynamics, hover configurations, and rotor failure restabilization of a morphing quadrotor, 2018 Annual American Control Conference (ACC), 2018, pp 8554862.CrossRefGoogle Scholar
Dilaveroglu, L. and Özcan, O. Minicore: A miniature, foldable, collision resilient quadcopter, 2020 3rd IEEE International Conference on Soft Robotics (RoboSoft), 2020, pp 176181.CrossRefGoogle Scholar
Tuna, T., Ovur, S.E., Gokbel, E. and Kumbasar, T. Folly: A self foldable and self deployable autonomous quadcopter, 2018 6th International Conference on Control Engineering and Information Technology (CEIT), 2018, pp 16.CrossRefGoogle Scholar
Xiong, H., Hu, J. and Diao, X. Optimize energy efficiency of quadrotors via arm rotation, J. Dyn. Syst. Meas. Control, 2019, 141, (9).CrossRefGoogle Scholar
Fasel, U., Keidel, D., Baumann, L., Cavolina, G., Eichenhofer, M. and Ermanni, P. Composite additive manufacturing of morphing aerospace structures, Manuf. Lett., 2020, 23, pp 8588.CrossRefGoogle Scholar
Jimenez-Cano, A., Martin, J., Heredia, G., Ollero, A. and Cano, R. Control of an aerial robot with multi-link arm for assembly tasks, 2013 IEEE International Conference on Robotics and Automation, 2013, pp 49164921.CrossRefGoogle Scholar
Suarez, A., Real, F., Vega, V.M., Heredia, G., Rodriguez-Castaño, A.and Ollero, A. Compliant bimanual aerial manipulation: Standard and long reach configurations, IEEE Access, 2020, 8, pp 8884488865. doi: 10.1109/ACCESS.2020.2993101.CrossRefGoogle Scholar
Derrouaoui, S.H., Guiatni, M., Bouzid, Y., Dib, I. and Moudjari, N. Dynamic modeling of a transformable quadrotor, 2020 International Conference on Unmanned Aircraft Systems (ICUAS), 2020, pp 17141719.CrossRefGoogle Scholar
Mintchev, S., Daler, L., L’Eplattenier, G.,Saint-Raymond, L. and Floreano, D. Foldable and self-deployable pocket sized quadrotor, 2015 IEEE International Conference on Robotics and Automation (ICRA), 2015, pp 21902195.CrossRefGoogle Scholar
Desbiez, A., Expert, F., Boyron, M., Diperi, J., Viollet, S. and Ruffier, F. X-morf: A crash-separable quadrotor that morfs its x-geometry in flight, 2017 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS), 2017, pp 222227.CrossRefGoogle Scholar
Abdulrahim, M. and Lind, R. Flight testing and response characteristics of a variable gull-wing morphing aircraft, AIAA Guidance, Navigation, and Control Conference and Exhibit, 2004, p 5113.CrossRefGoogle Scholar
Barbarino, S., Bilgen, O., Ajaj, R.M., Friswell, M.I. and Inman, D.J. A review of morphing aircraft, J. Intell. Material Syst. Struct., 2011, 22, (9), pp 823877.CrossRefGoogle Scholar
Matloff, L.Y., Chang, E., Feo, T.J., Jeffries, L., Stowers, A.K., Thomson, C. and Lentink, D. How flight feathers stick together to form a continuous morphing wing, Science, 2020, 367, (6475), pp 293297.CrossRefGoogle Scholar
Ma, H., Song, B., Pei, Y. and Chen, Z. Efficiency change of control surface of a biomimetic wing morphing UAV, IEEE Access, 2020, 8, pp 45 627–45 640.Google Scholar
Daler, L.S. Mintchev, C. Stefanini and D. Floreano. A bioinspired multi-modal flying and walking robot, Bioinspiration Biomimetics, 2015, 10, (1), p 016005.CrossRefGoogle Scholar
Morton, S. and Papanikolopoulos, N. A small hybrid ground-air vehicle concept, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2017, pp 51495154.CrossRefGoogle Scholar
D’Sa, R. Design of a Transformable Unmanned Aerial Vehicle, PhD Dissertation, University of Minnesota, 2020.Google Scholar
Zhao, M., Kawasaki, K., Chen, X., Noda, S., Okada, K. and Inaba, M. Whole-body aerial manipulation by transformable multirotor with two-dimensional multilinks, 2017 IEEE International Conference on Robotics and Automation (ICRA), 2017, pp 51755182.CrossRefGoogle Scholar
Bhat, P., Kuffner, J., Goldstein, S. and Srinivasa, S. Hierarchical motion planning for self-reconfigurable modular robots, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems, 2006, pp 886891.CrossRefGoogle Scholar
Han, J., Hui, Z., Tian, F. and Chen, G. Review on bio-inspired flight systems and bionic aerodynamics, Chin. J. Aeronaut., 2020. https://www.sciencedirect.com/science/article/pii/S1000936120302466?via%3Dihub.CrossRefGoogle Scholar
Jones, K., Bradshaw, C., Papadopoulos, J. and Platzer, M. Bio-inspired design of flapping-wing micro air vehicles, Aeronaut. J., 2005, 109, (1098), pp 385393.CrossRefGoogle Scholar
Zhang, S., Wang, Z., Wu, Y. and Yu, Y. Flight dynamic coupling analysis of a bio-inspired elastic-wing aircraft, Aeronaut. J., 2018, 122, (1250), p 572.CrossRefGoogle Scholar
Sanket, N.J., Singh, C.D., Ganguly, K., Fermã¼ller, C. and Aloimonos, Y. Gapflyt: Active vision based minimalist structure-less gap detection for quadrotor flight, IEEE Rob. Autom. Lett., 2018, 3, (4), pp 27992806.CrossRefGoogle Scholar
Fuller, S.B. Four wings: An insect-sized aerial robot with steering ability and payload capacity for autonomy, IEEE Rob. Autom. Lett., 2019, 4, (2), pp 570577.CrossRefGoogle Scholar
Kamil, Y., Hazry, D., Wan, K., Razlan, Z.M. and Abu Bakar, S. Design a new model of unmanned aerial vehicle quadrotor using the variation in the length of the arm, 2017 International Conference on Artificial Life and Robotics (ICAROB), 2017, pp 723–726.CrossRefGoogle Scholar
Borst, H.V. Review of v/stol aircraft with tilt-propellers and tiltrotors, Aeronaut. J., 1968, 72, (693), pp 817830.CrossRefGoogle Scholar
Gibertini, S.G., Auteri, F., Campanardi, G., Macchi, C., Zanotti, A. and Stabellini, A. Wind-tunnel tests of a tilt-rotor aircraft, Aeronaut. J., 2011, 115, (1167), pp 315.CrossRefGoogle Scholar
Kumar, R., Sridhar, S., Cazaurang, F., Cohen, K. and Kumar, M. Reconfigurable fault-tolerant tilt-rotor quadcopter system, ASME 2018 Dynamic Systems and Control Conference. American Society of Mechanical Engineers Digital Collection, 2018.CrossRefGoogle Scholar
Park, S., Her, J., Kim, J. and Lee, D. Design, modeling and control of omni-directional aerial robot, 2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), 2016, pp 15701575.CrossRefGoogle Scholar
Joshi, A., Tripathi, A. and Ponnalgu, R. Modelling and design of a hybrid aerial vehicle combining vtol capabilities with fixed wing aircraft, 2019 6th International Conference on Instrumentation, Control, and Automation (ICA), 2019, pp 4751.CrossRefGoogle Scholar
Anglade, A., Kai, J.M., Hamel, T. and Samson, C. Automatic control of convertible fixed-wing drones with vectorized thrust, 2019 IEEE 58th Conference on Decision and Control (CDC), 2019, pp 58805887.CrossRefGoogle Scholar
Hintz, C., Torno, C. and Carrillo, L.R.G. Design and dynamic modeling of a rotary wing aircraft with morphing capabilities, 2014 International Conference on Unmanned Aircraft Systems (ICUAS), 2014, pp 492498.CrossRefGoogle Scholar
Bai, Y. Control and Simulation of Morphing Quadcopter, PhD Dissertation, Saint Louis University, 2017.Google Scholar
Lee, J. Optimization of a modular drone delivery system, 2017 Annual IEEE International Systems Conference (SysCon), 2017, pp 18.CrossRefGoogle Scholar
da Silva Ferreira, M.A., Lopes, G.C., Colombini, E.L. and da Silva Simoes, A. A novel architecture for multipurpose reconfigurable unmanned aerial vehicle (UAV): Concept, design and prototype manufacturing, 2018 Latin American Robotic Symposium, 2018 Brazilian Symposium on Robotics (SBR) and 2018 Workshop on Robotics in Education (WRE), 2018, pp 443450.CrossRefGoogle Scholar
Mu, B. and Chirarattananon, P. Universal flying objects: Modular multirotor system for flight of rigid objects, IEEE Trans. Rob., 2020, 36, (2), pp 458471. doi: 10.1109/TRO.2019.2954679.CrossRefGoogle Scholar
Barbaraci, G. Modeling and control of a quadrotor with variable geometry arms, J. Unmanned Veh. Syst., 2015, 3, (2), pp 3557.CrossRefGoogle Scholar
Spong, M.W., Hutchinson, S. and Vidyasagar, M. Robot Modeling and Control, Wiley, New York, 2005. doi: 10.1108/ir.2006.33.5.403.1.Google Scholar
Bouzid, Y., Siguerdidjane, H. and Bestaoui, Y. Generic dynamic modeling for multirotor vtol uavs and robust sliding mode based model free control for 3d navigation, 2018 International Conference on Unmanned Aircraft Systems (ICUAS), 2018, pp 970979.CrossRefGoogle Scholar
Maximo, M., Ribeiro, C.H. and Afonso, R.J. Modeling of a position servo used in robotics applications, Proceedings of the 2017 Simposio Brasileiro de Automaçao Inteligente (SBAI), 2017.Google Scholar
Derafa, L., Madani, T. and Benallegue, A. Dynamic modeling and experimental identification of four rotors helicopter parameters, 2006 IEEE International Conference on Industrial Technology, 2006, pp 18341839.CrossRefGoogle Scholar
Bangura, M. and Mahony, R. Nonlinear dynamic modeling for high performance control of a quadrotor, Proceedings Australasian Conference on Robotics and Automation 2012, 2012.Google Scholar
Raj, N., Banavar, R., Abhishek and Kothari, M. Attitude control of novel tail sitter: Swiveling biplane–quadrotor, J. Guidance Control Dyn., 2020, 43, (3), pp 599607.CrossRefGoogle Scholar