Expert Systems with Applications: An International Journal
Interval Self-Organizing Map for Nonlinear System Identification and Control
ISNN '08 Proceedings of the 5th international symposium on Neural Networks: Advances in Neural Networks
Engineering Applications of Artificial Intelligence
Visualization of dynamics using local dynamic modelling with self organizing maps
ICANN'07 Proceedings of the 17th international conference on Artificial neural networks
Engineering Applications of Artificial Intelligence
Application of SOM-based visualization maps for time-response analysis of industrial processes
ICANN'10 Proceedings of the 20th international conference on Artificial neural networks: Part II
A Survey and Categorization of Small Low-Cost Unmanned Aerial Vehicle System Identification
Journal of Intelligent and Robotic Systems
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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.