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Ever since its first development, Fuzzy Logic Controllers (FLC) have been popular among the practitioners due to its robustness, interpretability, and especially its ability to handle imprecision. Many constructions of these controllers are still heavily dependent on the presence of experts' knowledge. This drawback has been investigated by many researchers, resulting in several methods integrated...
A new neural network structure for adaptive modeling of dynamic system is presented in this paper. Based on multi-layer perceptron (MLP), the network possesses parameter expansion and external recurrence. Parameter expansion is obtained by using tapped delay lines (TDLs) to the outputs of the hidden layer. This increases the number of parameters between the hidden layer and the output layer. Furthermore,...
A new idea to improve the performance of neural networks in modelling is presented in this paper. As the networks obtain their knowledge through learning process, it can be influenced through stronger optimization or more suited cost function to be minimized. In this paper, the implementation of linear-quadratic cost function is proposed. This cost function comprises of quadratic and linear function...
A new scheme for adaptive neural networks for nonlinear dynamic system identification is proposed in this paper. The network of structure multi-layer perceptron with external recurrence is trained offline at first to get the initial network parameters. The parameters of the network are classified into short-term memory part and long-term memory part. The short-term memory part includes the parameters...
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