M. M. Kamal

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Artificial Neural Network is an effective tool for highly nonlinear system. With the advent of high-speed computer system, there is more increased interest in the study of non-linear system. Neuro control algorithm is mostly implemented for the application to robotic systems and also some development has occurred in process control systems. Process Control(More)
In this paper, an intelligent model-based fault detection (FD) is developed for proton exchange membrane fuel cell (PEMFC) dynamic systems using an independent radial basis function (RBF) networks. The novelty is that this RBF networks is used to model the PEMFC dynamic systems and residuals are generated based on the differences between the PEMFC systems(More)
— In this work, a model-based fault detection and isolation (FDI) is developed for proton exchange membrane (PEM) fuel cell (FC) stack that is under feed-forward plus feedback control. The fault detection is achieved using an independent radial basis function (RBF) network model, whilst the fault isolation is based on the RBF classification. The novelty is(More)
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