Preprint Article Version 1 This version is not peer-reviewed

Adaptive Trajectory Tracking Control of a Quadrotor Based on Iterative Learning Algorithm

Version 1 : Received: 15 June 2018 / Approved: 18 June 2018 / Online: 18 June 2018 (13:43:18 CEST)

How to cite: Farzaneh, M.M.; Tavakolpour-Saleh, A. Adaptive Trajectory Tracking Control of a Quadrotor Based on Iterative Learning Algorithm. Preprints 2018, 2018060265 (doi: 10.20944/preprints201806.0265.v1). Farzaneh, M.M.; Tavakolpour-Saleh, A. Adaptive Trajectory Tracking Control of a Quadrotor Based on Iterative Learning Algorithm. Preprints 2018, 2018060265 (doi: 10.20944/preprints201806.0265.v1).

Abstract

This paper presents a new adaptive and optimal algorithm for the trajectory tracking control of a quadrotor using iterative learning algorithm (ILA) and enumerative learning algorithm. Ordinarily the ILA, as an adaptive method, can perform well with PID control to improve the controller’s performance for a nonlinear system. Quadrotors are considered as non-linear and unstable systems which the use of an adaptive and optimal controller can increase its stability and decrease error level. In this method, a PID controller is proposed for the outer and inner control loops of a quadrotor and the ILA is used to adapt PID control gains. Subsequently, an enumerative learning algorithm is used to optimize the learning rates of the ILA. For this purpose, at first, the dynamic model of the quadrotor is acquired. After that, the structure of the inner and outer control loops is defined. In the end, the simulation results for the trajectory tracking control of a quadrotor are demonstrated. Through simulation, it is concluded that as time increases, the performance of the suggested control method in trajectory tracking control becomes better and better and error signals convergence to zero.

Subject Areas

Quadrotor; trajectory tracking control; PID control; iterative learning algorithm.

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