فصلنامه روشهای هوشمند در صنعت برق
پیاپی 21 (بهار 1394)

The full adder circuit is one of the most significant and prominent fundamental parts in digital processors and integrated circuits since it can be used for implementing all four basic computational functions including: addition، subtraction، multiplication، and division. so، in this paper a new low power and high performance full adder cell has been proposed with the benefit of using carbon nano tube field effect transistors. The proposed design contains 12 CNTFET transistors which are connected in pass transistor logic style to make the desired functionality. Carbon Nano Tube Field Effect Transistor (CNTFET) has modified electrical characteristics such as low power consumption and high speed in comparison with MOSFET transistor; The proposed design is simulated using Hspice software based on CNTFET model and 0. 65V supply voltage. the simulations are done considering three different frequencies، and three different load capacitors. The simulation results، which demonstrated in tables and diagrams، proved the superiority of proposed design in terms of power consumption and performance (PDP) compared to the existing counterparts.

This paper presents a new hybrid method for optimal multi-objective reconfiguration simultaneous determining the optimal size and location of Distributed Generation (DG) in a distribution feeder. The purposes of this research are reducing the losses، improving the voltage profile and equalizing the feeder load balancing in a distribution system. Invasive Weed Optimization (IWO) is used to simultaneously reconfigure and identify the optimal capacity and location for installation of DG units in the distribution network. In order to facilitate the algorithm for multi-objective search ability، the optimization problem is formulated for minimizing fuzzy performance indices. The multi-objective optimization problem is transformed into a fuzzy inference system (FIS)، where each objective function is quantified into a set of fuzzy objectives selected by fuzzy membership functions. The proposed method is validated using the IEEE 33 bus test system at nominal load. The obtained results prove this combined technique is more accurate and has an efficient convergence property compared to other intelligent search algorithms. Also، the obtained results lead to the conclusion that multi-objective reconfiguration along with placement of DGs can be more beneficial than separate single-objective optimization.

Automatic segmentation of multiple sclerosis (MS) lesions in brain MRI has been widely investigated in recent years with the goal of helping MS diagnosis and patient follow-up. In this study we applied gaussian mixture model (GMM) to segment MS lesions in MR images. Usually، GMM is optimized using expectation-maximization (EM) algorithm. One of the drawbacks of this optimization method is that، it does not convergence to optimal maximum or minimum. Starting from different initial points and saving best result، is a strategy which is used to reach the near optimal. This approach is time consuming and we used another way to initiate the EM algorithm. Also، FAST- Trimmed Likelihood Estimator (FAST-TLE) algorithm was applied to determine which voxels should be rejected. The automatically segmentation outputs were scored by two specialists and the results show that our method has capability to segment the MS lesions with Dice similarity coefficient (DSC) score of 0. 82.

This paper describes an optimal design for multivariable PI controller with a high gain structure for an irregular system by genetic algorithm. PI controllers with a high gain structure leads to the asymptotic decomposition of the fast and slow modes in the closed loop system that have unique characteristics. The slow modes are asymptotically uncontrollable and unobservable; therefore، they have not role in input and output behavior. The closed-loop response is affected only from rapid poles; therefore، the system response will have quick behavior. An essential requirement of this design is that the first Markov parameter of multivariable system (the matrix product CB) must have full rank. If the CB matrix is not full rank، the measurement matrix (M) is used with internal feedback. In this structure، the measurement matrix is chosen using genetic algorithm in order to reach the stable closed-loop system and minimize interference between outputs. The research is implemented on the two kind of different systems. The results show that the response time of PI controller with a high gain structure by genetic algorithms has good behavior in comparison with other methods.

In the recent years، the use of switched reluctance motors (SRM) in industrial applications has been increased. In this regard، a large amount of research studies have been conducted on controlling the speed and torque of the aforementioned motors. These motors not only have a simple and stable structure، but also production cost is low. In addition، these motors take advantage of great power، the ability to work in high speeds and inadequate environments (hot and dusty)، reliability، control-ability، and high efficiency. However، discrete torque production of SRM along with enormous magnetic saturation in their cores reduces the variety of their industrial applications and also causes the inappropriate torque ripples. In this paper، a modified logical-rule-based method is proposed which employs the technique of controlling torque sharing function. Moreover، the optimized turn-on angle for conducting each phase is achieved by estimating the inductance curve in the vicinity of unaligned position and based on an analytical solution. Simulation results on a four-phase switched reluctance motor and a comparison with the conventional methods indicates validity and effectiveness of the proposed modified method.

Although in existence for many years، only recently has the LLC resonant converters، in particular in its half-bridge implementation، gained in the popularity it certainly deserve. The advantages such as high efficiency، low level of EMI emissions، and its ability to achieve high power density are such features that suited for power supply demand of many modern applications such as ATX PCs and flat panel TVs. One of the major difficulties in concern with designing such converter is complex model and non-linear equations that cannot be easily used into a design procedure. So in this paper، design is based on the assumption that input-to-output power transfer is essentially due to the fundamental Fourier series components of currents and voltages. This technique known as First Harmonic Approximation (FHA) and is a proper method to obtain the voltage gain through solving the equivalent ac circuit of the resonant tank. The design simulated by Pspice and finally the experimental results show design procedure base on FHA technique.