Model-Following Control Of Nonlinear Servo Systems Using Neural Networks  

Oleh:

Ouyang, X. ; Morgan, C. ; Nwagboso, C.

Jenis: Article from Journal - ilmiah internasional
Dalam koleksi: Simulation vol. 76 no. 5 (May 2000), page 263-272.
Topik: Neural network; back-propagation; model-following control; nonlinear servo systems
Fulltext: 263.pdf (855.03KB)

Isi artikel

The most useful property of neural networks for system identification and control is their ability to approximate arbitrary nonlinear mappings. In this paper, a new neural network model-following control method is proposed for nonlinear servo systems. First, three-layer artificial neural networks are trained to describe the forward and inverse dynamic characteristics of one type of specified nonlinear servo systems by using the backpropagation algorithm. Then the neural network inverse model is used as a feedforward controller for model-following control of the nonlinear servo systems. Computer simulation results obtained from MATLAB verify the applicability of neural network identification and control for nonlinear servo systems.

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