Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
Neural Networks for Modelling and Control of Dynamic Systems: A Practitioner's Handbook
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Modeling using the modified cascade correlation radial basis function (CCRBF) networks for an experimental platform is presented. We develop a practical algorithm coupled with model validity tests for identifying nonlinear autoregressive moving average model with exogenous inputs (NARMAX). The effectiveness of this modeling procedure is demonstrated by a four degrees-of-freedom (DOF) platform, and the experimental results show that the modified CCRBF networks for the platform are more appropriate than the conventional ones. The estimated model can be utilized for nonlinear flight simulation and control studies.