Explicit model identification and control of a micro aerial vehicle

In this work, we provide a nonlinear mathematical model identification methodology of an autonomous micro quadrotor, and the design of its orientation and position controllers. In the model identification, we specifically focus on the brushed D.C. motor dynamics, which further breaks down into three different segments: voltage generation, motor dynamics, and force/torque generation. Test bench experiments and software simulation are conducted to identify the parameters of the model derived from first principles physics model. Upon obtaining a good mathematical model of the micro quadrotor, model based orientation and position controllers are respectively implemented with linear quadratic regulator (LQR) and robust and perfect tracking (RPT) controller. The proposed control structure is designed and realized in a low cost micro quadrotor codenamed KayLion developed by the National University of Singapore.

[1]  Peter G. Ifju,et al.  Vision-guided flight stability and control for micro air vehicles , 2002, IEEE/RSJ International Conference on Intelligent Robots and Systems.

[2]  Wei Wang,et al.  Autonomous Control for Micro-Flying Robot and Small Wireless Helicopter X.R.B , 2006, 2006 IEEE/RSJ International Conference on Intelligent Robots and Systems.

[3]  Geoffrey L. Barrows,et al.  Flying insect inspired vision for autonomous aerial robot maneuvers in near-earth environments , 2004, IEEE International Conference on Robotics and Automation, 2004. Proceedings. ICRA '04. 2004.

[4]  Roland Siegwart,et al.  Towards Autonomous Indoor Micro VTOL , 2005, Auton. Robots.

[5]  Vijay Kumar,et al.  Trajectory Generation and Control for Precise Aggressive Maneuvers with Quadrotors , 2010, ISER.

[6]  Dario Floreano,et al.  Optic-Flow Based Control of a 46g Quadrotor , 2013 .

[7]  Stéphane Viollet,et al.  Bio-inspired optical flow circuits for the visual guidance of micro air vehicles , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[8]  Tong Heng Lee,et al.  Platform design and mathematical modeling of an ultralight quadrotor micro aerial vehicle , 2013, 2013 International Conference on Unmanned Aircraft Systems (ICUAS).

[9]  Tong Heng Lee,et al.  Unmanned Rotorcraft Systems , 2011 .

[10]  Vijay Kumar,et al.  The GRASP Multiple Micro-UAV Testbed , 2010, IEEE Robotics & Automation Magazine.

[11]  Biao Wang,et al.  Formation flight of unmanned rotorcraft based on robust and perfect tracking approach , 2012, 2012 American Control Conference (ACC).

[12]  D. Pines,et al.  Challenges Facing Future Micro-Air-Vehicle Development , 2006 .

[13]  Albert S. Huang,et al.  Visual Odometry and Mapping for Autonomous Flight Using an RGB-D Camera , 2011, ISRR.

[14]  Russ Tedrake,et al.  Experiments in Fixed-Wing UAV Perching , 2008 .

[15]  Robert J. Wood,et al.  An Autonomous Palm-Sized Gliding Micro Air Vehicle , 2007, IEEE Robotics & Automation Magazine.

[16]  Marc Pollefeys,et al.  PIXHAWK: A micro aerial vehicle design for autonomous flight using onboard computer vision , 2012, Auton. Robots.