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Design and Implementation of an Iterative Learning Controller on Quadcopter Drone

Abdolahi, Yasin | 2018

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 51271 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Rezaeizadeh, Amin
  7. Abstract:
  8. In this thesis, black-box identification, designing and implementing an iterative learning controller for the quadcopter was performed. Initially, the open-loop quadcopter system is unstable, so for black-box identification, a controller must first be implemented to stabilize it, but since no model is available from the system, the controlling parameters of the stabilizer through a proportional-integral and a proportional controller are executed as trial and error. To identify the roll and pitch models, the quadcopter is carried out using a radio controller and the measurements are saved during flight. Different models and methods are used to black-box identification, and finally the best model is selected in terms of simplicity and accuracy. After identifying the quadcopter model, the iterative learning controller is introduced and formulated, with the aim of learning the path and, consequently, increasing the accuracy of tracking in subsequent repetitions. In this context, the direction of the path is a longitudinal path, in other words, the aim is to follow the angles of the roll and the pitch of the quadcopter of a repeat path, which, with these repetitions, increases the accuracy of the pursuit of the angular path. The designed controller was first applied to the roll and pitch model separately and then applied simultaneously and its results were investigated
  9. Keywords:
  10. Iterative Learning Control ; Trajectory Tracking ; Proportional-Integral (PI)Controller ; Quadcopter ; Black Box Identification

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