Showing 5 results for V. Tahani
R. Hooshmand, H. Seifi, and V. Tahani,
Volume 15, Issue 2 (1-1997)
Abstract
In this article, an effective method to control a power system during emergency conditions is presented. Based on Fuzzy Linear Programming (FLP), a new technique is developed to solve the Load Shedding and Generation Reallocation (LSGR) optimization Problem. The objective function consists of terms of load curtailments and deviations in generation schedules. The constraints are power system variables limitations. The objective function and constraints coefficients are uncertain, thus it is more appropriate to use fuzzy linear programming. Considering the network frequency as an essential variable, and using the electrical load model, a fuzzy environment is prepared to solve more realistically and successfully the LSGR optimization problem. The results of various cases of fuzzy and crisp modes of the problem are demonstrated. It will be observed that the application of the FLP on one hand, will provide a more realistic model of power systems, and on the other hand, will cause a reduction in the values of the objective function.
B. Mirzaeian, M. Moallem, V. Tahani and Caro Lucas,
Volume 20, Issue 1 (7-2001)
Abstract
In this paper, a new method based on genetic-fuzzy algorithm for multi-objective optimization is proposed. This method is successfully applied to several multi-objective optimization problems. Two examples are presented: the first example is the optimization of two nonlinear mathematical functions and the second one is the design of PI controller for control of an induction motor drive supplied by Current-Source-Inverter (CSI). Step response of the system is considered and controller parameters are designed based on multi-objective optimization technique. Rise-time, maximum over-shoot, settling time and steady state error are considered as objective functions. The simulation results of the new method for induction motor speed control and optimization of two nonlinear mathematical functions are compared with the results obtained from other methods [4,14,15], which shows better performance.
S. Mirzaei, M. Saghaein - Nejad, V. Tahani and M. Moallem,
Volume 20, Issue 2 (4-2001)
Abstract
This paper introduces a novel passive suspension system for ground vehicles. This system is based on a flexible Electromagnetic Shock Absorber (EMSA). In the proposed system, efforts are made to a) select a high damping coefficient usable in a car b) determine Physical dimensions and geometry not much different from those of the mechanical shock absorbers and c) seletct EMSA weight and volume low enough for the core not to be saturated. A model is designed and developed followed by determining the dynamic equations for the model. The results from the simulation in a quarter car model are then compared with those from passive and active suspension systems.
Keywords: Active Suspension Systems, Electromagnetic damper, Finite Element method
S.samavi, V. Tahani and P. Khadivi,
Volume 20, Issue 2 (4-2001)
Abstract
Routing is one of the basic parts of a message passing multiprocessor system. The routing procedure has a great impact on the efficiency of a system. Neural algorithms that are currently in use for computer networks require a large number of neurons. If a specific topology of a multiprocessor network is considered, the number of neurons can be reduced. In this paper a new recurrent neural network and its energy function is introduced. This network requires a significantly smaller number of neurons compared to its counterparts. Also presented is the performance of this neural network.
Keywords: Routing, Multicomputer systems, Recurrent neural networks, Mesh interconnection networks.
V. Tahani, S. M. Saghaeian Nezhad and G. R. Arab,
Volume 21, Issue 1 (7-2002)
Abstract
Because of extreme local saturation at pole tips of excited phase and uncircular shape of rotor and stator, a Swithed Reluctance Motor (SRM) does not have a simple and accurate mathematical model. Therefore, the output control of this motor requires a robust controller which is not based on an accurate model of the process. Fuzzy controllers, to some extent, will satisfy these requirements. Teta-on and teta-off are controller outputs. The output of teta-off controller is a Variable Structure Controller (VSC) which contains two parts: coarse controller which is used when the speed error is large and its output causes large changes in teta-on angle. This part of the controller is similar to a fuzzy PI controller. The other part of the controller is a fine controller and is used when the speed error is low. The fine controller increases the speed of response and reduces the speed error to zero. This part is similar to a fuzzy I or PI controller. Finally, experimental results of no-load and underload speed controls are demonstrated. The fuzzy controller robustness to measurement noise and parameter uncertainty is also studied.
Keywords: Fuzzy Controller. SRM Variable Structure Controller
