Yuichi Masukake and Yoshihisa Ishida
A Modelfollowing Adaptive Controller for LinearNonlinear Plantsusing Radial Basis Function Neural Networks
3419 - 3422
2007
1
11
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/6706
https://publications.waset.org/vol/11
World Academy of Science, Engineering and Technology
In this paper, we proposed a method to design a
modelfollowing adaptive controller for linearnonlinear plants.
Radial basis function neural networks (RBFNNs), which are known
for their stable learning capability and fast training, are used to
identify linearnonlinear plants. Simulation results show that the
proposed method is effective in controlling both linear and nonlinear
plants with disturbance in the plant input.
Open Science Index 11, 2007