| Popis: |
For the control of a process, usually the relation between past input-output data of the process and future outputs must be identified. For the identification of nonlinear systems, neural networks can be used [3]. In this context, neural networks are nonlinear black-box models, to be used with convential parameter estimation methods. Two important models are: NNFIR-models: Neural Network Finite Impulse Response models, which use only past process inputs u(k − n) as inputs for the network; NNARX-models: Neural Network Auto Regressive with eXogeneous input models, which use past process inputs u(k − n) and past process outputs y(k − n) as inputs for the network. |
