Title :
Application of model-following adaptive neural network control theory in gust load alleviation
Author :
Nie, Rui ; Zhang, Weiguo ; Li, Guangwen ; Liu, Xiaoxiong
Author_Institution :
Coll. of Autom., Northwestern Polytech. Univ., Xi´´an, China
Abstract :
Based on the model-following adaptive neural network control theory, a gust load alleviation controller for civil airplanes by direct force control is proposed. For Dryden power spectral density function, the rational spectral theory is used to set up the linear state-space model of the vertical gust. The effects of gust to aircraft are considered to develop the synthesized system model of aircraft and gust. Simulation results show that the gust load alleviation control system based on neural network control theory can obtain good robust stability and the capability of restraining gust turbulence and measurement noises can be obtained by using the method in this paper.
Keywords :
adaptive control; aircraft control; control system synthesis; force control; neurocontrollers; robust control; spectral analysis; state-space methods; turbulence; Dryden power spectral density function; aircraft; civil airplane; direct force control; gust load alleviation controller; gust turbulence restraining; linear state-space model; model-following adaptive neural network control theory; rational spectral theory; robust stability; synthesized system model; Adaptive control; Adaptive systems; Aircraft; Airplanes; Control system synthesis; Control theory; Force control; Neural networks; Power system modeling; Programmable control; direct force control; gust load alleviation; modeling and simulation; neural network control;
Conference_Titel :
Automation and Logistics, 2009. ICAL '09. IEEE International Conference on
Conference_Location :
Shenyang
Print_ISBN :
978-1-4244-4794-7
Electronic_ISBN :
978-1-4244-4795-4
DOI :
10.1109/ICAL.2009.5262891
