Design of Neural Network-based Backstepping Controller for the Folding-Boom Aerial Platform Vehicle
- 10.2991/meic-15.2015.63How to use a DOI?
- aerial platform vehicle; model uncertainties; trajectory tracking control; backstepping controller; neural network
In this paper, the robust trajectory tracking problem is addressed for the work platform of folding-boom aerial platform vehicle in the presence of uncertainties and disturbances. The control objective is to make the work platform move along a desired reference trajectory and make the vibration inhibit at the same time. Since neural network system can approximate any nonlinear function with arbitrary accuracy over a compact set in the light of the universal approximation theorem, a neural network-based backstepping controller, which composed of backstepping control and neural network, is proposed for the trajectory tracking control of the work platform in the case of modeling uncertainties and disturbances. According to Lyapunov stability theorem, the stability and convergence of the overall system can be guaranteed by the derived control law. In addition, simulation results demonstrate that the proposed controller is effective for suppressing the vibration and reducing trajectory tracking error of the work platform.
- © 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/).
Cite this article
TY - CONF AU - Haidong Hu AU - Yan Ren AU - Huibo Liu PY - 2015/04 DA - 2015/04 TI - Design of Neural Network-based Backstepping Controller for the Folding-Boom Aerial Platform Vehicle BT - Proceedings of the 2015 International Conference on Mechatronics, Electronic, Industrial and Control Engineering PB - Atlantis Press SP - 265 EP - 268 SN - 2352-5401 UR - https://doi.org/10.2991/meic-15.2015.63 DO - 10.2991/meic-15.2015.63 ID - Hu2015/04 ER -