... optimization Neural nets Programming and algorithm theory ASRWNNI=adaptive self‐recurrent wavelet neural network identifier ALR=adaptive learning rate BP=back‐propagation CPSS=conventional power system stabilizer COA=chaotic optimization algorithm FG‐PID=fixed‐gain PID GD...

... sensorless control even at high load levels. © Emerald Group Publishing Limited 2010 Control systems Flux Fourier transforms Neural nets Electric machines For the highly dynamical behavior of the induction machine operated under any kind of field‐oriented control (FOC), a position...

... “vague”. That is: Equation 15 De‐kai Xu can be contacted at: xudekai1983@sina.com © Emerald Group Publishing Limited 2010 Wireless Sensors Networks Neural nets Fault diagnosis of wireless sensor networks (WSN) nodes are fault‐tolerant design technology. WSN nodes on fault...

... of the parameters or significant disturbance, the system may become unstable. Owing to these disadvantages of the MRAC, individually using it to control a complex system always fails. © Emerald Group Publishing Limited 2009 Neural nets Control systems Adaptive system theory In servo‐system...

.../value As the reliability of the optimum solution is strongly affected by the accuracy of the neural approximation model, the approximation error is kept as low as possible, especially in the maximum/minimum points. © Emerald Group Publishing Limited 2009 Functional analysis Neural nets...

...). In this paper, the structure with feedbacks from the shaft torque and the difference between the motor and the load speeds is taken into account (Figure 2). © Emerald Group Publishing Limited 2009 Control systems Vibration Electric motors Neural nets Estimation In many industrial drives...

... 2008 Boundary‐elements methods Neural nets Recently, much effort has been devoted to the synthesis of new artificial materials that can be used in a proper manner in several special applications (Ziolkowski and Engheta, 2003). Depending on the chosen application these materials can...

..., in this situation, may result in controlled torque with minimum ripples. The component of the proposed control circuit shown in Figure 1 can be explained the following subsections. © Emerald Group Publishing Limited 2008 Torque Electric motors Neural nets Electromagnetism Owing...

.... Neural nets Software prototyping Fuzzy logic Programming and algorithm theory Optimum design ANN is a more promising area of artificial intelligence since they do not rely on human experience but attempt to learn by themselves. Most of the ANN applications utilize multilayer perceptron models...

... benchmarks in electromagnetism. Benchmarking Neural nets Optimization techniques Some analytical benchmarks are available to compare the performances of multi‐objective optimisation methods (Deb et al., 2005). However, in case of electromagnetic optimisation problems, analytical...

... Equation 4 Equation 5 Equation 6 © Emerald Group Publishing Limited 2007 Neural nets Fuzzy control Modelling Simulation One of the important type of axial field machines (Ficheux et al., 2001 ; Cavagnino et al., 2000, 2002 ; Caricchi...

.... The flow chart of the RWC algorithm is shown in Figure 7 . Motion Control systems Magnetic devices Neural nets Demand for using permanent magnet synchronous motors (PMSMs) in industrial drives has risen sharply in the last decade due to such favourable features of PMSMs as high power...

... in the energy‐production field. Since the sun is a natural energy source for sunny countries, this type of energy production is getting more importance (Harada and Zhao, 1993). Neural nets Fuzzy logic Control Solar power © Emerald Group Publishing Limited 2005 The proposed model...

.... Dh′ is the projection of Dh in the space Y , and Dy′ is the projection of Dy in the space H . © Emerald Group Publishing Limited 2005 Optimization techniques Neural nets Magnetic devices The optimal design of electromagnetic devices is a very...

.... The important problem is thus the generation of the features best representing the individual beats, i.e. suppressing the differences among the beats belonging to the same class and differing the beats of different classes as much as possible. Neural nets Classification Heart The classical...

... Limited 2005 Numerical analysis Neural nets Dielectric properties Recently, microwave power engineers have taken a particular interest in complex permittivity, ε=ε′−iε″. While modern electromagnetic simulators allow the engineers to extensively characterize...

... , and calculate the new F_B activation values using the equation below: where f( ) is the logistic sigmoid function Equation 2 Filter the F_B activation through W to F_C using the equation Electromagnetic fields Pipelines Neural nets...

... not presented in the training process. In this way, the developed models can be used for a valid prediction over a wide range of input parameters. © Emerald Group Publishing Limited 2004 Noise Microwaves Neural nets Neural net devices Microwave transistors In addition...

... by Equation 6 where Ψ_m,n (t) is given in . © Emerald Group Publishing Limited 2004 Inductance Loading (physics) Wavelengths Voltage fluctuations Neural nets Transient response Detection and measurement of voltage sags and transient voltages must be accurate enough...