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This paper focuses on the problem of neural-network-based decentralized adaptive output-feedback control for a class of nonlinear strict-feedback large-scale stochastic systems. The dynamic surface control technique is used to avoid the explosion of computational complexity in the backstepping design process. A novel direct adaptive neural network approximation method is proposed to approximate the...
Motor fault diagnosis methods are crucial in acquiring safe and reliable operation in motor drive systems. In this paper, a new method for the motor fault diagnosis is proposed based on wavelet packet transform (WPT) and artificial neural network (ANN). The energy of the vibration signals of motor can be obtained by the multi-decomposition of WPT and used as feature values of ANN inputs for fault...
Motor fault diagnosis methods are crucial in acquiring safe and reliable operation in motor drive systems. In this paper, we propose a hybrid algorithm for motor fault diagnosis based on the combination of artificial immune system (AIS) and artificial neural network (ANN). The artificial immune algorithm (AIA) for data clustering is employed to adaptively choose the amount and location of the hidden...
This paper utilises topological learners, the self organising map in combination with the k means algorithm to organise potential engine faults and the respective location of faults, focussing on a 12 cylinder 2 stroke marine diesel engine. This method is applied to reduce the numerosity of the data presented to a user by selecting representative samples from a number of clusters to enable efficient...
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