Title :
On model identification of engine for unmanned aerial vehicle
Author :
Song, Pan ; Minxiang, Wei
Author_Institution :
Coll. of Energy & Power Eng., Nanjing Univ. of Aeronaut. & Astronaut., Nanjing
Abstract :
In the light of knowledge of statistics theory, the multi-element regression forecast algorithm is researched. Based on the experiments data of a two-stroke gasoline engine for unmanned aerial vehicle (UAV), a steady-state engine model is established by using a mathematical tool of stepwise regression. The procedure of modeling is described in detail. By comparing with experimental data, this model can describe the loading characteristic of the engine, and can achieve high fidelity model. The established engine model provides a basis for research of drive-train system and automatic control of UAV.
Keywords :
aircraft; engines; forecasting theory; mobile robots; regression analysis; remotely operated vehicles; UAV; automatic control; drive-train system; engine model identification; multielement regression forecast algorithm; statistics theory; steady-state engine model; stepwise regression; two-stroke gasoline engine; unmanned aerial vehicle; Educational institutions; Electronic mail; Engines; Lighting control; Load forecasting; Mathematical model; Power engineering and energy; Predictive models; Statistics; Unmanned aerial vehicles; Stepwise regression; System identification; Two-stroke engine model; Unmanned aerial vehicle;
Conference_Titel :
Control Conference, 2008. CCC 2008. 27th Chinese
Conference_Location :
Kunming
Print_ISBN :
978-7-900719-70-6
Electronic_ISBN :
978-7-900719-70-6
DOI :
10.1109/CHICC.2008.4605798