Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
5004606 | ISA Transactions | 2014 | 13 Pages |
Abstract
The referenced quadrotor helicopter in this paper has a unique configuration. It is more complex than commonly used quadrotors because of its inaccurate parameters, unideal symmetrical structure and unknown nonlinear dynamics. A novel method was presented to handle its modeling and control problems in this paper, which adopts a MIMO RBF neural nets-based state-dependent ARX (RBF-ARX) model to represent its nonlinear dynamics, and then a MIMO RBF-ARX model-based global LQR controller is proposed to stabilize the quadrotor's attitude. By comparing with a physical model-based LQR controller and an ARX model-set-based gain scheduling LQR controller, superiority of the MIMO RBF-ARX model-based control approach was confirmed. This successful application verified the validity of the MIMO RBF-ARX modeling method to the quadrotor helicopter with complex nonlinearity.
Related Topics
Physical Sciences and Engineering
Engineering
Control and Systems Engineering
Authors
Jun Wu, Hui Peng, Qing Chen, Xiaoyan Peng,