Modeling and inverse controller design for an unmanned aerial vehicle based on the self-organizing map.
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.
Computational NeuroEngineering Laboratory, University of Florida, Gainesville, FL 32611, USA. jeongho@cnel.ufl.edu
Jeongho
J
Cho
Jose C
JC
Principe
Deniz
D
Erdogmus
Mark A
MA
Motter
D000401:Aircraft / Q000295:instrumentation*; D000465:Algorithms; D003198:Computer Simulation; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005246:Feedback; D008962:Models, Theoretical; D009038:Motion; D016571:Neural Networks, Computer; D012371:Robotics / Q000295:instrumentation* / Q000379:methods; D014159:Transducers