The Development of Neural Network Based System Identification ...

Chapter 5
NN BASED SYSTEM IDENTIFICATION: RESULTS
AND DISCUSSION
5.1 INTRODUCTION
In this chapter, the model selection and validation results from the proposed NN based
system identification methods are presented and discussed. The model selection and
validation results from the off-line system identification for various NN architectures
are presented in Section 5.2, Section 5.3 and Section 5.4. Section 5.5 provides the
comparison results between off-line prediction performance from conventional MLP
architecture and the proposed HMLP and modified Elman network. In Section 5.6,
the identification results using recursive training are presented. The on-line training
proposed in Section 4.3.5 is implemented to identify the attitude dynamics of the UAS
helicopter model using the MLP network. The prediction performance of the MLP
network trained with off-line LM algorithm and the MLP network trained with repeated
recursive Gauss-Newton algorithm are compared.
The feasibility of implementing
recursive type training is analysed against mini-batch LM algorithm in term of training
time. Then, the prediction performance comparison of MLP, HMLP and Elman network
using the recursive training method is given in Section 5.7. Finally, the chapter is
summarised in Section 5.8.