Quadrotor UAV trajectory tracking based on iterative self learning control

DOI

10.2991/asei-15.2015.39How to use a DOI?

Keywords

Quadrotor UAV; self-learning control; Iterative correction; Trajectory tracking

Abstract

In order to solve the problems in the traditional control method of Quadrotor UAV, Such as weak anti-interference ability and system modeling error has a greater impact on the tracking performance, A trajectory tracking algorithm based on self-learning control is designed. The algorithm can control the object accurately by the iterative correction. To control the unknown object in a certain time, have good anti-interference ability, It has good control effect for the uncertain system and nonlinear coupling system, As the structure of the control algorithm is relatively simple, So it is easy to implement in actual system. The simulation results verify the feasibility of the algorithm.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Li-ben Yang
AU  - Wei-guo Zhang
AU  - De-gang Huang
PY  - 2015/05
DA  - 2015/05
TI  - Quadrotor UAV trajectory tracking based on iterative self learning control
BT  - Proceedings of the 2015 International conference on Applied Science and Engineering Innovation
PB  - Atlantis Press
SP  - 182
EP  - 187
SN  - 2352-5401
UR  - https://doi.org/10.2991/asei-15.2015.39
DO  - 10.2991/asei-15.2015.39
ID  - Yang2015/05
ER  -