Identification of a Nonlinear Pneumatic Servo System Using Modular Neural Networks
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Sometimes, in the case of highly nonlinear systems the traditional approaches of identification and control could be difficult to implement. In this case, a good alternative are the neural networks. In this paper a modular neural network for the identification of a pneumatic servo system is proposed. This approach is based on the partitioning of static characteristic of the pneumatic system. The neural modules are implemented with multilayer neural networks.