مجله مهندسی برق و الکترونیک ایران
سال چهارم شماره 2 (پاییز و زمستان 1386)

This paper presents a comprehensive case study on electro-mechanical analysis of MEMS1 variable capacitors. Using the fundamental mechanical and electrical equations, static and dynamic behaviors of the device are studied. The analysis is done for three different modes, namely: dc (static mode), small signal ac and large signal regime. A complete set of equations defining dynamic behavior of the MEMS, and an ac small signal equivalent circuit are presented. The mathematical models are defined and examined by the Matlab Simulink and a complete set f simulation results is reported for various cases separately. The results of this study would be useful in design and analysis of the MEMS based circuits which have some kind of mechanical dynamic action. Some examples of such devices may include VCO2s, frequency modulators, tunable filters and parametric effect circuits.

An integrated modelmagnetoencephalography (MEG) and functional Magnetic Resonance Imaging (fMRI) is proposed. In the proposed model, MEG and fMRI outputs are related to the corresponding aspects of neural activities in a voxel. Post synaptic potentials (PSPs) and action potentials (APs) are two main signals generated by neural activities. In the model, both of MEG and fMRI are related to the PSPs without any correlation to the APs. Each PSP is modeled by the direction and strength of its current flow, which are treated as random variables. The overall neural activity in each voxel is used for equivalent current dipole in MEG and as input of the extended Balloon model for producing Blood Oxygen Level Dependent (BOLD) signal in fMRI. The proposed model shows possibility of detecting activation by fMRI in a voxel while the voxel is silent for MEG and vice versa. This is according to the fact that fMRI signal reflects the sum of PSPs’ strengths (independent of their directions) but MEG signal reflects the vector sum of the PSPs (which depends on their directions). The model also shows that the crosstalk from neural activities of adjacent voxels in fMRI and properties of the inverse problem in MEG generate different spatial responses in the two modalities.We use real auditory MEG and Fmri datasets from 2 normal subjects to estimate the parameters of the model. Goodness of the real data our model shows the possibility of using the proposed model to simulate realistic datasets.

Among structured Peer-to-Peer systems, Chord has a general popularity due to its salient features like simplicity, high scalability, small path length with respect to network size, and flexibility on node join and departure. However, Chord doesn’t take into account the topology of underlying physical network when a new node is being added to the system, thus resulting in high routing latency and low efficiency in data lookup. In this paper, we introduce the TAC, a novel topology-aware protocol which is based on Chord. TAC introduces the local ring concept by dividing the geographical space into smaller areas. Through binding each new node to a proper local ring concerning its physical location, TAC considers the physical network topology of the overlay network to demonstrate more efficient key lookup. Simulation results show that TAC performs better in terms of more efficient routing and less bandwidth usage.

This paper presents a design procedure for an adaptive power management control strategy based on a driving cycle recognition algorithm. The design goal of the control strategy is to minimize fuel consumption and engine-out NOx, HC and CO emissions on a set of diversified driving schedules. Seven facility-specific drive cycles are considered to represent different driving scenarios. For each facility-specific drive cycle, the fuel economy and emission are optimized and obtained proper split between the two energy sources (engine and electric motor). A driving pattern recognition algorithm is subsequently developed and used to classify the current driving cycle into one of the facility-specific drive cycles; thus, the most appropriate control algorithm is adaptively selected. This control scheme was tested on a typical driving cycle and was found to operate satisfactorily.

This paper presents a detailed small-signal and transient analysis of a full bridge PWM DC-DC converter designed for high voltage, high power applications using an average model. The derived model is implemented in a typical system and used to produce the small-signal and transient characteristics of the converter. Results obtained in the analysis of the high voltage and high power design example is validated by comparison for actual system and derived model. The derived small signal model is used to design a controller to regulate output voltage of the converter under several disturbances. A PD controller with combination of a feedforward input voltage is designed so that the output voltage is equal to desired voltage and the time response is very short under load and input voltage disturbances.