DocumentCode :
2551608
Title :
Internal model control based on RBF neural network inverse system decoupling in a 3-DOf helicopter system
Author :
Dong, Xiucheng ; Zhao, Yunyuan ; Rui, Guangzheng
Author_Institution :
Provincial Key Lab. on Signal & Inf. Process., Xihua Univ., Chengdu, China
fYear :
2011
fDate :
21-25 June 2011
Firstpage :
570
Lastpage :
574
Abstract :
3-DOF helicopter is a typical multi-input multi-output (MIMO) system with high-order and strong channel coupling and nonlinearity. In this paper, an internal control strategy based on RBF neural network inverse system decoupling for helicopter process is proposed. First the mathematical model of helicopter system is obtained and the reversibility of system is testified, then the neural network inverse system of helicopter is established by neural network online identification, and the inverse model as controller model and helicopter in series, which forms a dynamic pseudo linear system. The MIMO helicopter system with strong coupling is converted into isolated dynamic decoupling pseudo linear system. Finally, a linear close-loop internal model controller is designed. The simulation shows that this strategy is very validity in tracking control of the 3-DOF helicopter system.
Keywords :
MIMO systems; closed loop systems; control system synthesis; helicopters; identification; mathematical analysis; neurocontrollers; radial basis function networks; vibrational modes; 3-DOf helicopter system; MIMO helicopter system; RBF neural network inverse system decoupling; helicopter process; high-order coupling; high-order nonlinearity; isolated dynamic decoupling pseudo linear system; linear close-loop internal model controller; mathematical model; multiinput multioutput system; neural network online identification; strong channel coupling; strong channel nonlinearity; Adaptation models; Artificial neural networks; Control systems; Couplings; Helicopters; Linear systems; Mathematical model; 3-DOF helicopter; Inverse system; RBF neural networks; internal model control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Control and Automation (WCICA), 2011 9th World Congress on
Conference_Location :
Taipei
Print_ISBN :
978-1-61284-698-9
Type :
conf
DOI :
10.1109/WCICA.2011.5970577
Filename :
5970577
Link To Document :
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