Hardware-in-the-Loop Motion Simulator of Quadrotor: Analysis of Autonomous Trajectory Tracking

Document Type : Research Article

Authors

Faculty of Mechanical Engineering, K. N. Toosi University of Technology, Tehran, Iran

Abstract

Direct trajectory tracking of quadrotor system in 3D space is not possible originating from the fact that control inputs are not independent in manipulating all flying degrees of freedom. The major concentration of the presented study is to describe the design procedure of a new intelligent algorithm for moving the quadrotor along a trajectory curve in space. The presented algorithm consists of two major parts. In the primary one, the desired Euler angles and their associated rates are intelligently estimated by a Fuzzy Logic Controller (FLC) working based on the experimentally Fuzzyfied rules. The second part of the proposed algorithm is the Sliding Mode Control (SMC) designed for precise tracking of the commanded Euler angles while guaranteeing the robust stability of the quadrotor flight. To simulate the airborne performance of the quadrotor equipped with the proposed trajectory algorithm, a heavy-duty 6-DOF Hardware-In-the-Loop Motion Simulator (HILMS) by which all motions of a quadrotor (either translational or rotational movements) can be precisely evaluated, is designed and fabricated. The introduced HILMS employs one load cells for each arm of the quadrotor, allowing the microcontroller to access to the thrust of the motors during operation. This way, while the translational motion is restricted, the position of the quadrotor can be computed along the governing mathematical motion equations. The empirical results confirm stability and trajectory tracking quality of the quadrotor by implementation of the proposed two-staged intelligent algorithm.

Keywords

Main Subjects


[1] Lugo-Cardenas, I., Salazar, S., & Lozano, R. (2016, June). The MAV3DSim Hardware in the Loop Simulation Platform for Research and Validation of UAV Controllers. In 2016 International Conference on Unmanned Aircraft Systems (ICUAS) (pp. 1335-1341). IEEE.
[2] Lange, S., & Protzel, P. (2012, March). Cost-Efficient Mono-Camera Tracking System for a Multirotor UAV Aimed for Hardware-in-the-Loop Experiments. In International Multi-Conference on Systems, Sygnals & Devices (pp. 1-6). IEEE.
[3] Lange, S., & Protzel, P. (2012, March). Cost-Efficient Mono-Camera Tracking System for a Multirotor UAV Aimed for Hardware-in-the-Loop Experiments. In International Multi-Conference on Systems, Sygnals & Devices (pp. 1-6). IEEE.
[4] Berbra, C., Simon, D., Gentil, S., & Lesecq, S. (2009). Hardware in the loop networked control and diagnosis of a quadrotor drone. IFAC Proceedings Volumes, 42(8), 971-976.
[5] Odelga, M., Stegagno, P., Bülthoff, H. H., & Ahmad, A. (2015, November). A Setup for Multi-UAV Hardware-in-the-Loop Simulations. In 2015 Workshop on Research, Education and Development of Unmanned Aerial Systems (RED-UAS) (pp. 204-210). IEEE.
[6] Bayrakceken, M. K., Ilarslan, M., Arisoy, A., & Karamancioglu, A. (2010). HILSim for attitude control of a quadrotor. In Unmanned Vehicles Workshop, UVW 2010, Proceedings of the International Workshop on Unmanned Vehicles in Istanbul/TURKEY (pp. 151-155).
[7] Nicol, C., Macnab, C. J. B., & Ramirez-Serrano, A. (2011). Robust adaptive control of a quadrotor helicopter. Mechatronics21(6), 927-938.
[8] Islam, S., Liu, X. P., & El Saddik, A. (2015). Adaptive sliding mode control of unmanned four rotor flying vehicle. International Journal of Robotics and Automation30(2).
[9] Sampath, B. G., Perera, K. C. R., Wijesuriya, W. A. S. I., & Dassanayake, V. P. C. (2014). Fuzzy Based Stabilizer Control System for Quad-Rotor. International Journal of Mechanical, Aerospace, Industrial and Mechatronics Engineering8(2), 455-461.
[10] Valenti, M., Bethke, B., Fiore, G., How, J. P., & Feron, E. (2006, August). Indoor multi-vehicle flight testbed for fault detection, isolation, and recovery. In Proceedings of the AIAA Guidance, Navigation, and Control Conference and Exhibit, Keystone, CO (Vol. 63, p. 64).
[11] Hoffmann, G. M., Huang, H., Waslander, S. L., & Tomlin, C. J. (2007, August). Quadrotor helicopter flight dynamics and control: Theory and experiment. In Proc. of the AIAA Guidance, Navigation, and Control Conference (Vol. 2).
[12] Castillo, P., Lozano, R., & Dzul, A. (2005). Stabilization of a mini rotorcraft with four rotors. IEEE Control Systems Magazine25(6), 45-55.
[13] Bouabdallah, S., Murrieri, P., & Siegwart, R. (2005). Towards autonomous indoor micro VTOL. Autonomous Robots18(2), 171-183.
[14] Regula, G., & Lantos, B. (2011). Backstepping based control design with state estimation and path tracking to an indoor quadrotor helicopter. Periodica Polytechnica Electrical Engineering, 53(3-4), 151-161.
[15] Pizetta, I. H. B., Brandao, A. S., & Sarcinelli-Filho, M. (2016). A Hardware-in-the-Loop Platform for Rotary-Wing Unmanned Aerial Vehicles. Journal of Intelligent & Robotic Systems, 84(1-4), 725-743.
[16] Lee, D., Kim, H. J., & Sastry, S. (2009). Feedback linearization vs. adaptive sliding mode control for a quadrotor helicopter. International Journal of control, Automation and systems7(3), 419-428.
[17] Erginer, B., & Altuğ, E. (2012). Design and implementation of a hybrid fuzzy logic controller for a quadrotor VTOL vehicle. International Journal of Control, Automation and Systems10(1), 61-70.
[18] Cheon, S. H., Ha, S. W., & Moon, Y. H. (2016, September). Hardware-in-the-loop simulation platform for image-based object tracking method using small UAV. In 2016 IEEE/AIAA 35th Digital Avionics Systems Conference (DASC) (pp. 1-5). IEEE.
[19] Zhao, B., Xian, B., Zhang, Y., & Zhang, X. (2015). Nonlinear robust sliding mode control of a quadrotor unmanned aerial vehicle based on immersion and invariance method. International Journal of Robust and Nonlinear Control, 25(18), 3714-3731.
[20] Mehta, A. M., Rus, D., Mohta, K., Mulgaonkar, Y., Piccoli, M., & Kumar, V. (2016). A scripted printable quadrotor: Rapid design and fabrication of a folded MAV. In Robotics Research(pp. 203-219). Springer, Cham.
[21] Goel, R., Shah, S. M., Gupta, N. K., & Ananthkrishnan, N. (2009). Modeling, simulation and flight testing of an autonomous quadrotor. Proceedings of ICEAE, 2009.
[22] Saeedi, S., Nagaty, A., Thibault, C., Trentini, M., & Li, H. (2016). Perception and Navigation for an Autonomous Quadrotor in GPS-denied Environments. International Journal of Robotics and Automation31(6).
[23] Zeghlache, S., Saigaa, D., Kara, K., Harrag, A., & Bouguerra, A. (2012). Fuzzy sliding mode control with chattering elimination for a quadrotor helicopter in vertical flight. In Hybrid Artificial Intelligent Systems (pp. 125-136). Springer Berlin Heidelberg.
[24] Sabatino, F. (2015). Quadrotor control: modeling, nonlinearcontrol design, and simulation.
[25] Slotine, J. J. E., & Li, W. (1991). Applied nonlinear control (Vol. 199, No. 1). Englewood Cliffs, NJ: Prentice-hall.
[26] Homaeinezhad, M. R., Tahbaz‐zadeh Moghaddam, I., Khakpour, Z., & Naseri, H. (2015). Short‐Time Linear Quadratic Form Technique for Estimating Fast‐Varying Parameters in Feedback Loops. Asian Journal of Control17(6), 2289-2302.
[27] Wang, L. X. (1999). A course in fuzzy systems. Prentice-Hall press, USA.
[28] Bernstein, D. S. (2009). Matrix mathematics: theory, facts, and formulas. Princeton University Press.
[29] Naseri, H., & Homaeinezhad, M. R. (2014). Improving measurement quality of a MEMS-based gyro-free inertial navigation system. Sensors and Actuators A: Physical207, 10-19.
[30] Ghasemi‐Moghadam, S., & Homaeinezhad, M. R. (2018). Attitude determination by combining arrays of MEMS accelerometers, gyros, and magnetometers via quaternion‐based complementary filter. International Journal of Numerical Modelling: Electronic Networks, Devices and Fields31(3), e2282.
[31] Bouabdallah, S. (2007). Design and control of quadrotors with application to autonomous flying (Doctoral dissertation, École Polytechnique federale de Lausanne).
[32] Voos, I. (2009, April). Nonlinear control of a quadrotor micro-UAV using feedback-linearization. In Mechatronics, 2009. ICM 2009. IEEE International Conference on (pp. 1-6). IEEE.