Adaptive non-linear flight controller using neural networks for unmanned helicopter

Murthy, Satyanarayana PV (2003) Adaptive non-linear flight controller using neural networks for unmanned helicopter. Technical Report. National Aerospace Laboratories, Bangalore, India.

[img] PDF
Restricted to Repository staff only

Download (1MB)
[img] Indexer Terms (Generate index codes conversion from application/pdf to indexcodes)
Restricted to Repository staff only

Download (4kB)


Recent publications on automatic flight controls are concentrated on neural network based adaptive controls. The ability of the neural networks to approximate the continuous smooth functions has been explored for adaptation. In this report the design details of an adaptive controller for an unmanned helicopter using these modern concepts is explained. This controller consists of feedback linearization, linear model inversion and learning while controlling neural network architecture. The time scale separation between position and attitude dynamics of the vehicle is used in the controller synthesis. In order to simplify the nonlinear controller, approximations to the body axis forces are used in the controller calculation. The attitude control uses the neural networks to adaptively cancel the inversion errors. Finally the design is verified using the simulation results.

Item Type: Monograph (Technical Report)
Uncontrolled Keywords: Automatic flight control;Adaptive control;Nonlinear control;Neural networks;Feedback linearization;Model inversion;Unmanned helicopter
Subjects: AERONAUTICS > Aircraft Design, Testing & Performance
Depositing User: Mr. N A
Date Deposited: 27 Jun 2006
Last Modified: 24 May 2010 04:13

Actions (login required)

View Item View Item