Gain scheduled integral linear quadratic control for quadcopter

  • Authors

    • J Shah
    • M Okasha
    • W Faris
    2018-10-09
    https://doi.org/10.14419/ijet.v7i4.13.21334
  • quadcopter, LQR, gain scheduled, dynamics and control.

  • Abstract

    The findings of this paper are focused on the dynamics and control of a quadcopter using a modified version of a Linear Quadratic Regulator (LQR) control approach. The classical LQR control approach is extended to include an integral term to improve the quad copter tracking performance. The mathematical model is derived using the Newton-Euler method for the nonlinear six DOF model that includes the aerodynamics and detailed gyroscopic moments as a part of the system identification process. The linearized model is obtained and it is characterized by the heading angle (yaw angle) of the quadcopter. The adopted control approach is utilizing the LQR method to track several trajectories i.e. helical and lissajous curve with significant variation in the yaw angle. The integral term is introduced to the controller in order to minimize the steady state errors observed. The controller is modified to overcome difficulties related to the continuous changes in the operation points and to eliminate the chattering that was observed in the control technique. Numerical non-linear simulations are performed using MATLAB & Simulink to illustrate to accuracy and effectiveness of the proposed controller.

     

     

     

  • References

    1. [1] Nanomi K, Kendoul F, Suzuki S, Wang W & Nakazawa D (2010), Autonomous Flying Robots: Unmanned Aerial Vehicles and Micro Aerial Vehicles. Springer

      [2] Hoffmann GM, Huang H, Waslander SL & Tomlin CJ (2007), Quadrotor helicopter flight dynamics: theory and experiment. AIAA Guidance, Navigation and Control Conference

      [3] Okasha M, Shah J, Fauzi W & Hanouf Z (2017), Gain scheduled linear quadratic control of quadcopter. IOP Conference Series: Materials Science and Engineering 270, 012009

      [4] Bouabdallah S, Noth A & Siegwart R (2004), PID vs LQ control techniques applied to an indoor micro quadrotor. IEEE/RSJ International Conference on Intelligent Robots and Systems

      [5] Li J & Li Y (2011), Dynamic analysis and PID control for a quadrotor. International Conference in Mechatronics and Automation

      [6] Bouabdallah S & Siegwart R (2005), Backstepping and sliding-mode techniques applied to an indoor micro quadrotor. IEEE International Conference in Robotics and Automation

      [7] Nicol C, Macnab CJB & Ramirez-Serrano A (2011), Robust adaptive control of a quadrotor helicopter. Mechatronics 21, 927-938

      [8] Mueller WM & D’Andrea R (2013), A model predictive controller for quadrocopter state interception. European Control Conference

      [9] Elkholy H (2014), Dynamic Modeling and Control of A Quadrotor using Linear and Nonlinear Approaches. Thesis, American University in Cairo

      [10] Sawyer S (2015), Gain-Scheduled Control of a Quadcopter UAV. Thesis, University of Waterloo

      [11] Nasir A, Ahmed M & Rahmat M (2008), Performance comparison between LQR and PID controller for an inverted pendulum system. International Conference on Power Control and Optimization

      [12] Bouabdallah S, Noth A & Seigwart R (2014), PID vs LQ control technniques applied to an indoor micro quadrotor. Autonomous Systems Laboratory Swiss Federal Institute of Technology

  • Downloads

  • How to Cite

    Shah, J., Okasha, M., & Faris, W. (2018). Gain scheduled integral linear quadratic control for quadcopter. International Journal of Engineering & Technology, 7(4.13), 81-85. https://doi.org/10.14419/ijet.v7i4.13.21334

    Received date: 2018-10-08

    Accepted date: 2018-10-08

    Published date: 2018-10-09