In this study, we introduce an indirect adaptive fuzzy wavelet neural controller (IAFWNC) as a power system stabilizer to damp inter-area modes of oscillations in a multi-machine power system. Quantum computing is an efficient method for improving the computational efficiency of neural networks, so we developed an identifier based on a quantum neural network (QNN) to train the IAFWNC in the pro...

We describe the implementation of a large scale disk array controller and subsystem incorporating over 100 high performance 3.5" disk drives. It is designed to provide 40 MB/s sustained performance and 40 GB capacity in three 19" racks. The array controller forms an integral part of a file server that attaches to a Gb/s local area network. The controller implements a high bandwidth interconnect...

The paper presents an investigation in to the effect of neural network predictive control of UPFC on the transient stability performance of a multimachine power system. The proposed controller consists of a neural network model of the test system. This model is used to predict the future control inputs using the damped Gauss-Newton method which employs ‘backtracking’ as the line search method f...

An artificial neural network can be used as an intelligent controller to control non-linear, dynamic system through learning. It can easily accommodate non-linearities and time dependencies. Most common multi-layer feed-forward neural networks have the drawbacks of large number of neurons and hidden layers required to deal with complex problems and require large training time. To overcome these...

The problem of detecting and resolving control conflicts has started to receive attention from the networking community. Corybantic [16] is an example of recent work in this area. We argue that it is too coarse grain in that it does not model the combined operational objectives of multiple controller functions. This paper proposes a finer grain approach where a network control function is repre...