سال:1386 | دوره: | شماره: |تعداد مقالات:8

In this paper the design of new high-speed current mode BiCMOS logic circuits is proposed. By altering the threshold detector circuit of the conventional current mode logic circuits and applying the multiple value logic (MVL) approach the number of transistors in basic logic operators are significantly reduced and hence a reduction of chip area and power dissipation as well as an increase in speed is achieved. Simulation with HSpice using BSIM 3V3 model and experimental 65nm BiCMOS technology were carried out for speed, and power consumption considerations at different supply voltage levels. Finally the performance of the proposed circuit is compared to an 8 bit voltage mode adder.

In this paper, using the three-phase induction motor fifth order model in a stationary two axis reference frame with stator current and rotor flux as state variables, a conventional back stepping controller is first designed for speed and rotor flux control of an induction motor drive. Then in order to make the control system stable and robust against all electromechanical parameter uncertainties as well as to the unknown load torque disturbance, the back stepping control is combined with artificial neural networks in order to design a robust nonlinear controller. It will be shown that the composite controller is capable of compensating the parameters variations and rejecting the external load torque disturbance. The overall system stability is proved by the Lyapunov theory. It is also shown that the method of artificial neural network training, guarantees the bounded ness of errors and artificial neural network weights. Furthermore, in order to make the drive system free from flux sensor, a sliding mode rotor flux observer is employed that is also robust to all electrical parameter uncertainties and variations. Finally, the validity and effectiveness of the proposed controller is verified by computer simulation.

Statistical process control methods for monitoring processes with univariate or multivariate measurements are used widely when the quality variables fit to known probability distributions. Some processes, however, are better characterized by a profile or a function of quality variables. For each profile, it is assumed that a collection of data on the response variable along with the values of the corresponding quality variables is measured. While the linear function is the simplest, it occurs frequently that many of the nonlinear functions may be transferred to linear functions easily. This paper proposes a control chart based on the generalized linear test (GLT) to monitor coefficients of the linear profiles and an R-chart to monitor the error variance, the combination of which is called GLT/R chart. While fixed values of the explanatory variables are cornerstones in other control charts proposed to monitor profiles, in GLT/R chart, it is not a necessary condition. In order to illustrate the robustness of the GLT/R chart a simulation study has been done in two different cases, i.e. fixed and non-fixed values of the explanatory variables. Then, the results obtained from GLT/R charts are compared to the ones from a multivariate T2 and Exponentially Weighted Moving Average/R (EWMA/R) control charts.

This paper deals with the transient analysis of K-out-of-N: G system consisting of Noperating machines. To improve system reliability, Y cold standby and S warm standbys spares are provided to replace the failed machines. The machines are assumed to fail in multiple modes. At least K-out-of-N machines for smooth functioning of the system. Reliability and mean time to failure are established in terms of transient probabilities.

Location decision is an integral part of organizational strategies involving many factors that may be conflicting in nature. This paper presents a holistic approach of the multi-criteria decision making (MCDM) methodology to select the optimal location (s), which fits best for both investors and managers. A case study is also provided to illustrate the application of the proposed holistic approach. Finally, a comparison with the previous work is made and the informational efficacy of the proposed model is also discussed.

Due date assignment for customer orders has been studied in various production environments using different modeling approaches. In this paper the researchers consider a production system in which the orders of several customers are produced in a single batch because of the economy of scale. If a batch is completed before receiving customer orders, inventory carrying cost is incurred but if it is completed after receiving customer orders, shortage cost is incurred and finally if the order is delivered after its due date, tardiness cost is charged. The problem is to decide on batch size, due date of batch (imposed on supply process) and lead time (to be quoted to the next coming customers) so that relevant costs are minimized. The objective function is to minimize total cost of supply, inventory carrying, shortage and tardiness. Production flow times are probabilistic which follow a probability distribution. The proposed model is solved using real-coded genetic algorithms and numerical results are presented. This work was motivated by a heavy equipment production system which has some products with relatively low demand rates, high prices and long supply lead times.

In this paper, the effects of two different Particle Size Distributions (PSD) on packing behavior of ideal rigid spherical nanoparticles using a novel packing model based on parallel algorithms have been reported. A mersenne twister algorithm was used to generate pseudorandom numbers for the particles initial coordinates. Also, for this purpose a nanosized tetragonal confined container with a square floor (300 * 300 nm) were used in this work. The Andreasen and the Lognormal PSDs were chosen to investigate the packing behavior in a 3D bounded region. The effects of particle numbers on packing behavior of these two PSDs have been investigated. Also the reproducibility and the distribution of packing factor of these PSDs were compared.

For laterally complex media, it may be more suitable to take a different orientation of the displacement vector of Shear-waves. This may change the sign of several imaginary reflections and conversion coefficients to be used in reservoir characterization and AVO (Amplitude Versus Offset) analysis or modeling. In this new convention the positive direction of the displacement vector of reflected Shear-waves is chosen to the left of ray tangent (in the direction of wave propagation). Therefore, the definition of the displacement vector of shear-waves can be used properly even for very complicated media. Finally the shear-wave dynamic behavior of a reservoir zone can be illustrated for laterally varying structures in terms of the amplitude variation and phase behavior using this new orientation.