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A Side Lobe Canceller (SLC) structure is a conventional partially adaptive technique which is used in large adaptive array radars. If a desired signal has long time duration in comparison with the SLC adaptation time, signal components may be cancelled. So, this paper presents a modified SLC which eliminates desired signal cancellation problems and allows using an unconstrained adaptive algorithm. Simulation results demonstrate the performance of this modified structure for a planar array.
This paper presents a new adaptive Sliding-Mode flux observer for speed sensorless and rotor flux control of three-phase induction motor (IM) drives. The motor drive is supplied by a three-level space vector modulation (SVM) inverter. Considering the three-phase IM Equations in a stator stationary two axis reference frame, using the partial feedback linearization control and Sliding-Mode (SM) control, the rotor speed and rotor flux controllers are derived first. These controllers are capable of making the drive system states follow the system nominal trajectories in spite of the motor parameter uncertainties and external load torque disturbance. Then, based on the Lyapunov theory, a SM observer is developed in order to estimate the rotor flux, rotor speed and rotor resistance simultaneously. In addition, in order to satisfy the persistent excitation (P.E) condition, a low frequency low amplitude ac signal is superimposed to the rotor flux reference command. Finally, the validity and effectiveness of proposed control approach is verified by computer simulation.
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This paper deals with the G/G/R machining system consisting of M operating machines as well as S cold standbys. The concepts of balking and reneging are incorporated which make our model more versatile to deal with real time systems. The broken-down machines are sent to repair facilities consisting of R permanent repairmen. The failure times and repair times are generally identical and independent distributed random variables. The failed machines are repaired according to FIFO rules. By using a diffusion process, the steady-state probability density function for the queue size is obtained in terms of the first two moments of inter-arrival times and repair times of machines. Some expressions in explicit form that characterize the system performance are also mentioned.
Technology centered organizations must be able to identify promising new products or process improvements at an early stage so that the necessary resources can be allocated to those activities. It is essential to invest in targeted research and development (R and D) projects as opposed to a wide range of ideas so that resources can be focused on successful outcomes. The selection of the most appropriate projects is the aim of R and D project selection models. The project selection is complicated by many factors, such as vision and preferences of decision makers, allocating the right human resources, interrelationships between projects, and changes over time and success factors that are difficult to measure. In this article we formulate essential factors in R and D project portfolio selection by a mathematical model, which consider a multi- objective function for maximizing corporate benefit through quantitative and qualitative criteria as well as insight and preferences of decision makers and human resource allocation which does not exceed organizations constraints such as planning horizon, available resources and interrelationships between projects.
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Based on an effective energy conversion method between gas enthalpy and thermal radiation, a multi-layered type of porous air heater has been proposed. In the five layered structure which is analyzed in this work, there are five porous layers which are separated by four quartz glass windows. The main layer operates as a porous radiant burner that products a large amount of thermal radiative energy and in the other layers, the energy conversion process between gas enthalpy and thermal radiation takes place. In order to obtain the thermal characteristics of the heater, the coupled energy equations for the gas flows and porous layers are solved numerically by iterative method. The two–flux radiation model is used for computing the radiative fluxes from a solid matrix. Computational results show a very high efficiency for this type of porous air heater although it has a very simple structure.
In recent years, soft computing methods, like fuzzy logic and neural networks have been presented and developed for the purpose of mobile robot trajectory tracking. In this paper we will present a fuzzy approach to the problem of mobile robot path tracking for the CEDRA rescue robot with a complicated kinematical model. After designing the fuzzy tracking controller, the membership functions and rule weights will be optimized by genetic algorithm in order to obtain more acceptable results. Simulation results have demonstrated significant improvements in controller efficacy.