Identification and control of a small-scale helicopter

Deboucha, A. and Taha, Z. (2010) Identification and control of a small-scale helicopter. Journal of Zhejiang University Science A, 11 (12). pp. 978-985. ISSN 1673-565X,

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Designing reliable flight control for an autonomous helicopter requires a high performance dynamics model. In this paper, a nonlinear autoregressive with exogenous inputs (NLARX) model is selected as the mathematical structure for identifying and controlling the flight of a small-scale helicopter. A neural network learning algorithm is combined with the NLARX model to identify the dynamic component of the rotorcraft unmanned aerial vehicle (RUAV). This identification process is based on the well-known gradient descent learning algorithm. As a case study, the multiple-input multiple-output (MIMO) model predictive control (MPC) is applied to control the pitch motion of the helicopter. Results of the neural network output model are closely match with the real flight data. The MPC also shows good performance under various conditions.

Item Type: Article
Uncontrolled Keywords: Dynamics model; System identification; Black box; Small-scale helicopter; Neural networks (NNs); Control design
Subjects: Q Science > Q Science (General)
Depositing User: Mr Faizal 2
Date Deposited: 12 Jan 2015 04:04
Last Modified: 08 Jul 2017 07:15

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