DocumentCode :
2120346
Title :
On IMC structure scheme based on ANN´s inverse model for nonlinear system and simulation researches
Author :
Qu Dongcai ; Zhao Guorong
Author_Institution :
Dept. of Control Eng., Naval Aeronaut. & Astronaut. Univ., Yantai, China
fYear :
2010
fDate :
29-31 July 2010
Firstpage :
1168
Lastpage :
1171
Abstract :
It was one important method for controller design of the nonlinear control system based on the system´s inverse model, which was rapidly got development in recently years. However for massive complex, unknown and the indefinite nonlinear object, in order to model the inverse model with general use, there were many difficulties in the controller design of the actual nonlinear systems. Based on principle of IMC (Internal Model Control) and the good performance of the ANN´s (Artificial Neural Network) nonlinear mapping and so on, the ANN´s feedforward model identifier Mf and the ANN´s inverse model controller Mi were designed in the article. The IMC structure scheme based on the IMC principle and the ANN´s theory was designed for nonlinear system. Massive simulation researches show that the IMC structure scheme designed based on the ANN´s inverse model is successful and effective, and the ANN´s inverse model controller Mi has the well control performance and general use.
Keywords :
control system synthesis; feedforward; neural nets; nonlinear control systems; ANN inverse model; IMC structure scheme; feedforward model identifier; internal model control; nonlinear control system; Artificial neural networks; Control systems; Data models; Feedback control; Inverse problems; Nonlinear systems; Training; Artificial Neural Network (ANN); Internal Model Control (IMC); Inverse Model; Nonlinear System; Simulation Researches;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control Conference (CCC), 2010 29th Chinese
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6263-6
Type :
conf
Filename :
5573935
Link To Document :
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