A Model-following Adaptive Controller for Linear/Nonlinear Plantsusing Radial Basis Function Neural Networks

In this paper, we proposed a method to design a model-following adaptive controller for linear/nonlinear plants. Radial basis function neural networks (RBF-NNs), which are known for their stable learning capability and fast training, are used to identify linear/nonlinear plants. Simulation results show that the proposed method is effective in controlling both linear and nonlinear plants with disturbance in the plant input.

Authors:

• Yuichi Masukake
• Yoshihisa Ishida

Keywords:

• Linear/nonlinear plants
• neural networks
• radial basisfunction networks.

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