DocumentCode :
857402
Title :
Modeling and inverse controller design for an unmanned aerial vehicle based on the self-organizing map
Author :
Cho, Jeongho ; Principe, Jose C. ; Erdogmus, Deniz ; Motter, Mark A.
Author_Institution :
Comput. NeuroEng. Lab., Univ. of Florida, Gainesville, FL, USA
Volume :
17
Issue :
2
fYear :
2006
fDate :
3/1/2006 12:00:00 AM
Firstpage :
445
Lastpage :
460
Abstract :
The next generation of aircraft will have dynamics that vary considerably over the operating regime. A single controller will have difficulty to meet the design specifications. In this paper, a self-organizing map (SOM)-based local linear modeling scheme of an unmanned aerial vehicle (UAV) is developed to design a set of inverse controllers. The SOM selects the operating regime depending only on the embedded output space information and avoids normalization of the input data. Each local linear model is associated with a linear controller, which is easy to design. Switching of the controllers is done synchronously with the active local linear model that tracks the different operating conditions. The proposed multiple modeling and control strategy has been successfully tested in a simulator that models the LoFLYTE UAV.
Keywords :
aircraft control; control system synthesis; linear systems; nonlinear control systems; remotely operated vehicles; self-organising feature maps; LoFLYTE UAV; inverse controller design; linear controller; local linear modelling scheme; self-organizing map; unmanned aerial vehicle; Aerospace control; Aircraft; Control systems; Inverse problems; NASA; Nonlinear control systems; Nonlinear dynamical systems; Testing; Unmanned aerial vehicles; Vehicle dynamics; Inverse controller; local linear model; multiple models; self-organizing map (SOM); Aircraft; Algorithms; Computer Simulation; Equipment Design; Equipment Failure Analysis; Feedback; Models, Theoretical; Motion; Neural Networks (Computer); Robotics; Transducers;
fLanguage :
English
Journal_Title :
Neural Networks, IEEE Transactions on
Publisher :
ieee
ISSN :
1045-9227
Type :
jour
DOI :
10.1109/TNN.2005.863422
Filename :
1603629
Link To Document :
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