Adaptive Dynamic Surface Control for a Hybrid Aerial Underwater Vehicle With Parametric Dynamics and Uncertainties

A hybrid aerial underwater vehicle (HAUV) that could operate in the air and underwater might provide tremendous potential for ocean monitoring and search and rescue as well as underwater exploration. Differences between the aerial and underwater environments, along with common disturbances in wind or oceanic currents, present key challenges when designing a robust global controller. This paper presents a nonlinear dynamic controller, otherwise known as the adaptive dynamic surface control (ADSC) scheme, which effectively deals with the challenges aroused by the nonlinearities, uncertainties, and time-varying parameters of the system. First, the mathematical model of the HAUV is developed by means of the Newton–Euler formalism, highlighting the influence of the environment change on the vehicle dynamics. Second, the variations of added mass and damping during the water/air transition are estimated. Finally, the ADSC scheme is used to control and provided robust transition between distinct mediums for the vehicle in simulations, compared with the gain-scheduled proportional–integral–derivative scheme. The simulation results validate the good tracking performance and strong robustness of the presented scheme.

[1]  Zongyu Zuo,et al.  Trajectory tracking control design with command-filtered compensation for a quadrotor , 2010 .

[2]  Jana Fuhrmann,et al.  Guidance And Control Of Ocean Vehicles , 2016 .

[3]  Heinrich H. Bülthoff,et al.  Modeling and control of a quadrotor UAV with tilting propellers , 2012, 2012 IEEE International Conference on Robotics and Automation.

[4]  L.A.B. Torres,et al.  Development of a Hand-Launched Small UAV for Ground Reconnaissance , 2010, IEEE Transactions on Aerospace and Electronic Systems.

[5]  W.K.G. Seah,et al.  Multiple-UUV approach for enhancing connectivity in underwater ad-hoc sensor networks , 2005, Proceedings of OCEANS 2005 MTS/IEEE.

[6]  Karl Sammut,et al.  Shell space decomposition based path planning for AUVs operating in a variable environment , 2014 .

[7]  Robert J. Wood,et al.  Hybrid aerial and aquatic locomotion in an at-scale robotic insect , 2015, 2015 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[8]  Osamah A. Rawashdeh,et al.  Loon Copter: Implementation of a hybrid unmanned aquatic–aerial quadcopter with active buoyancy control , 2018, J. Field Robotics.

[9]  Zhiyong Dai,et al.  Backstepping dynamic surface control for a class of non-linear systems with time-varying output constraints , 2015 .

[10]  Glen Bright,et al.  Development of an UAV for search & rescue applications , 2011, IEEE Africon '11.

[11]  M Kovač,et al.  Launching the AquaMAV: bioinspired design for aerial–aquatic robotic platforms , 2014, Bioinspiration & biomimetics.

[12]  P.J. Alsina,et al.  Dynamic Modelling of a Quadrotor Aerial Vehicle with Nonlinear Inputs , 2008, 2008 IEEE Latin American Robotic Symposium.

[13]  Section De Microtechnique,et al.  design and control of quadrotors with application to autonomous flying , 2007 .

[14]  K W Watkinson,et al.  Prediction of Acceleration Hydrodynamic Coefficients for Underwater Vehicles from Geometric Parameters , 1978 .

[15]  M. Triantafyllou,et al.  Adding in-line motion and model-based optimization offers exceptional force control authority in flapping foils , 2014, Journal of Fluid Mechanics.

[16]  Mike Hall,et al.  Cooperative use of unmanned sea surface and micro aerial vehicles at Hurricane Wilma , 2008, J. Field Robotics.

[17]  Swaroop Darbha,et al.  Dynamic surface control for a class of nonlinear systems , 2000, IEEE Trans. Autom. Control..

[18]  Michael S. Triantafyllou,et al.  A novel degree of freedom in flapping wings shows promise for a dual aerial/aquatic vehicle propulsor , 2014, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[19]  Vijay Kumar,et al.  Opportunities and challenges with autonomous micro aerial vehicles , 2012, Int. J. Robotics Res..

[20]  James Carroll,et al.  Design, Fabrication, and Testing of the Fixed-Wing Air and Underwater Drone , 2017 .

[21]  Liu Hsu,et al.  Optimal control allocation of quadrotor UAVs subject to actuator constraints , 2016, 2016 American Control Conference (ACC).

[22]  Wei Lin,et al.  Adaptive control of nonlinearly parameterized systems: the smooth feedback case , 2002, IEEE Trans. Autom. Control..

[23]  Mario Fernando Montenegro Campos,et al.  Attitude control for an Hybrid Unmanned Aerial Underwater Vehicle: A robust switched strategy with global stability , 2015, 2015 IEEE International Conference on Robotics and Automation (ICRA).

[24]  Marco M. Maia,et al.  Design and implementation of multirotor aerial-underwater vehicles with experimental results , 2017, 2017 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS).

[25]  Liu Hsu,et al.  Adaptive backstepping control design for MIMO plants using factorization , 2002, Proceedings of the 2002 American Control Conference (IEEE Cat. No.CH37301).

[26]  L. Whitcomb,et al.  A SURVEY OF UNDERWATER VEHICLE NAVIGATION : RECENT ADVANCES AND NEW CHALLENGES , 2006 .

[27]  Karl Sammut,et al.  Rendezvous Path Planning for Multiple Autonomous Marine Vehicles , 2018, IEEE Journal of Oceanic Engineering.

[28]  Agus Budiyono,et al.  Advances in unmanned underwater vehicles technologies: Modeling, control and guidance perspectives , 2009 .

[29]  Robert L. Wernli Low Cost UUV's for Military Applications: Is the Technology Ready? , 2000 .

[30]  Jose Barata,et al.  An open-source watertight unmanned aerial vehicle for water quality monitoring , 2015, OCEANS 2015 - MTS/IEEE Washington.

[31]  Ashok Gopalarathnam,et al.  Testing and Characterization of a Fixed Wing Cross-Domain Unmanned Vehicle Operating in Aerial and Underwater Environments , 2018, IEEE Journal of Oceanic Engineering.

[32]  Gregory Dudek,et al.  Multi-domain monitoring of marine environments using a heterogeneous robot team , 2012, 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[33]  Yan Lin,et al.  Adaptive dynamic surface control for MIMO nonlinear time-varying systems with prescribed tracking performance , 2015, Int. J. Control.

[34]  Tieshan Li,et al.  Robust adaptive backstepping design for course-keeping control of ship with parameter uncertainty and input saturation , 2011, 2011 International Conference of Soft Computing and Pattern Recognition (SoCPaR).

[35]  Mirko Kovac,et al.  Fast Aquatic Escape With a Jet Thruster , 2017, IEEE/ASME Transactions on Mechatronics.

[36]  Mario Fernando Montenegro Campos,et al.  Hybrid Unmanned Aerial Underwater Vehicle: Modeling and simulation , 2014, 2014 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[37]  D. Spencer,et al.  The Force of Impact on a Sphere Striking a Water Surface , 2015 .

[38]  U. Lei,et al.  Viscous torque on a sphere under arbitrary rotation , 2006 .

[39]  Mirko Kovac,et al.  Efficient Aerial–Aquatic Locomotion With a Single Propulsion System , 2017, IEEE Robotics and Automation Letters.

[40]  Marco M. Maia,et al.  Modeling and control of unmanned aerial/underwater vehicles using hybrid control , 2018, Control Engineering Practice.

[41]  Diego A. Mercado,et al.  Aerial-Underwater Systems, a New Paradigm in Unmanned Vehicles , 2017, 2017 International Conference on Unmanned Aircraft Systems (ICUAS).

[42]  Christopher E. Brennen,et al.  A Review of Added Mass and Fluid Inertial Forces , 1982 .

[43]  R. G. Dong Effective mass and damping of submerged structures , 1978 .