IRANIAN JOURNAL OF ELECTRICAL AND COMPUTER ENGINEERING (IJECE)
Year:2008 | Volume:7 | Issue:1|Papers Count:13

This paper deals with a fundamental control issue in switched reluctance motor (SRM) drives – the torque ripple minimization. Normally, the torque ripple minimization is achieved by using a look-up table, i.e., the look-up table makes use of stored magnetic characteristics to provide reference currents for some specified torque. A number of techniques for the generation of reference current profiles have been suggested. However, because of highly nonlinear magnetic characteristics of SRM, all these schemes are not entirely successful. This work deals with a novel algorithm for generation of current waveforms by an iterative modulation of reference current pattern, using a multiplying factor. This multiplying factor is computed with help of a fuzzy system, which is well suited to compensate nonlinearities of the system. Two different schemes, i.e., one-phase-on scheme and two-phase-on scheme with torque sharing functions, are presented. The performance of the proposed strategy is verified by simulation studies.

Matrix converter induction motor drive system operated with a direct torque control (DTC) shows a sluggish response during startup and under changes of torque command. Fuzzy logic is used in conjunction with direct torque control to minimize these problems. A fuzzy logic controller chooses the switching states based on a set of fuzzy variables. Flux position, error in flux magnitude and error in torque are used as fuzzy state variables. Fuzzy rules are determined by observing the vector diagram of flux and currents. The operation of the direct torque controller becomes difficult at low speeds due to the effect of change in stator resistance on the flux measurements. To improve the system performance at low speeds a fuzzy resistance estimator is proposed to eliminate the error due to the change in stator resistance.At constant flux and torque commands any change in stator resistance of the induction machines causes an error in stator current. This error is utilized by the fuzzy resistance estimator to correct the stator resistance used by the controller to match the machine resistance. Both fuzzy controller and fuzzy resistance estimator are implemented using DSP TMS320C6711 for a 3 hp induction motor drive system. Results demonstrate enhanced performance.

Granted by Japan Society for Promotion Science (JSPS), this research deals with two vital problems in installation of Wind Power Generation (WPG) in an Existing Power System (EPS), one is determining the optimal installation bus and the other one is estimating the maximum limitation of WPG that can be safely introduced into EPS. Here, Domain-Link Method (DLM) is used for forming applicable domains based on the structural characteristic of EPS, consequently Maximizing Decision Method (MDM) is used for ensuring the best bus inside selected domain using operational indices of environment, economy, reliability and stability. The limitation of WPG is estimated after connecting WPG to the selected bus based on system steady constrains. The result is illustrated using the IEEE 30-Bus test system. Successive installation of WPG may be conducted with the same procedure satisfying new EPS constrains resulted from the previous installation. Other than complex computation process, this methodology shows its unique feasibility in application of WPG installation to EPS of different structure and capacity.

Transmission expansion planning (TEP) is one of the most important parts of expansion planning in power systems. Competition in these systems has resulted in essential changes in TEP models and criteria. While methods introduced so far are essentially based on dc load flow, the proposed method utilizes the ac optimal power flow (OPF) in order to model the real world condition and obtaining optimal plans. Furthermore, in order to model the operation and investment costs, transmission tariffs are used. Investigation on 8-bus system confirms the advantages of the proposed method as compared with previously presented approaches.

Stabilizers design for Static Var Compensators (SVCs) with fixed parameters can be adequate for some load characteristics but contrarily reduce system damping and contribute to system instability with loads having other characteristics. This paper proposed a novel stabilizer design for SVCs to enhance power systems damping in the presence of voltage-dependent load characteristics uncertainty. The proposed SVC stabilizer is based on a simple hierarchal self organizing fuzzy controller (SOFC) scheme. The SOFC has two levels, the main controller and the fuzzy gain controller. The later is responsible for on line tuning the main controller gains according to load characteristics variations. Computer simulation results show that the proposed SOFC SVC stabilizer provides better damping to the power system and it was able to keep system stability where conventional control techniques fail.

This paper presents a new space vector pulsewidth modulation (SVPWM) algorithm for reduction of common mode voltage in direct torque controlled induction motor drives. The proposed PWM algorithm does not use any zero voltage vectors for inverter control; hence it can restrict common mode voltage better than conventional SVPWM algorithm. The main advantage of the proposed algorithm is that the number of commutations required in one sector and from one sector to the next sector remains the same as in conventional SVPWM technique. To validate the proposed method, the simulation results are presented and compared to those obtained with conventional SVPWM based direct torque control algorithm.

In this paper, a new structure for bilateral teleoperation systems with bounded uncertain time delay in communication channel is proposed. The main contributions of the proposed method are two folds: 1) complete transparency for the system and 2) stability robustness. Moreover, due to the proposed structure, stability can be checked graphically using simple classical control methods, such as Bode plot. The key features of this structure are its simple design as well as the ability to analyze the stability of the closed-loop system using the property of the stable scalar functions and the small gain theorem. In the proposed structure, two local controllers will be designed, such that the transparency of the teleoperated system and the local stabilities are guaranteed. One local controller will be designated for position tracking of the slave system and the other one, whilst ensuring the stability of the closed-loop system in presence of uncertain time delay in communication channel, performs the force tracking. Simulation results demonstrate that the proposed control method is highly effective in providing a stable transparent teleoperation system under uncertain, but bounded, time delay in communication channel.

A new, input-output based discrete sliding mode control (DSMC) method is proposed for the control of processes with dead-time. However, it is necessary to combine DSMC with the Smith predictor for the dead-time compensation of processes with long dead-time. Because DSMC is sensitive to apparent dead-time in the process to be controlled, two Smith predictors were used in the control schema. One with high order is used to cancel out actual process output signal as good as possible. Another one with low order is used in the identification of the controlled process and in the design of DSMC. When this new DSMC is compared to the optimally tuned PID controller, it shows much better overall characteristics. Simulation experiments are made to illustrate the effectiveness of the new DSMC both for plants with short and with long dead-times.

Fast Euclidean Direction Search (FEDS) and Recursive Adaptive Matching Pursuit (RAMP) are two recently introduced algorithms for adaptive filtering characterized by low computational complexity, good convergence, and numerical robustness. While conceived from quite different perspectives, we point out, that both algorithms are closely related and can be interpreted as different variants of 1) A matching pursuit procedure applied to a particular over-determined equation set, 2) A constrained Least Squares (LS) optimization problem, and 3) A Gauss-Seidel like iterative solution procedure applied to a normal equation. Both FEDS and RAMP have been demonstrated experimentally to possess excellent convergence behavior in several application scenarios. However, a tool for predicting the convergence of these algorithms based on second order statistics is lacking. This paper provides such a tool to study the convergence analysis of these adaptive filter algorithms. This tool relies on energy conservation arguments and doses not restrict to assume specific models for the regression data. Finally, we demonstrate through simulations that these results are useful in predicting adaptive filter performance.

This paper investigates resonance phenomenon in active filters. The paper studies the effect of system/filter parameters on resonance conditions. It also proposes an active technique for damping such resonances. The study is based on modal analysis in which unstable modes or modes with slow damping are first extracted. Then, using a new technique, such modes are considerably damped. PSCAD/EMTDC software is also employed to verify the performance of the proposed technique.

This paper describes the implementation of an active integrated spiral antenna for Ultra-Wideband (UWB) applications. By integrating a low–noise amplifier (LNA) with an antenna, the voltage standing wave ratio (VSWR) can be kept low for a large bandwidth and this antenna indicates a 13 dB improvement in gain compared with one using a passive antenna having the same design, resulting in an improved spiral antenna performance for UWB. For the designed circuit in the UWB frequency range (3.1-10.6 GHz), the gain of the LNA is better than 13dB, its noise figure is less than 3dB, and both 11 S and 22 S are less than-13dB.

Mining association rules is an interesting problem in the field of knowledge discovery and data mining. In this paper a fast, new method for mining association rules is presented. In this new sampling approach, which utilizes FP-Growth to mine sample data, the candidate generation and test in the sample data is omitted because of the FP-Tree projection of sample data in the main memory. To overcome the main memory limitation in the new sampling method, a useful technique is proposed. Theoretical time consideration and empirical evaluation show that the new sampling approach is superior to the traditional Apriori-based sampling by orders of magnitude. Experimental evaluations on artificial and real-life datasets show that our approach, compared with a previously proposed sampling algorithm, is more efficient when the minimal support threshold is decreased and is also more stable as the size of the sample data increases.

A novel method to determine the characteristic impedance of a rectangular transmission line, through the evaluation of lumped parameters, is presented. Leaving of the current distribution that circulates in the central conductor is also compared with a technique that leaves the determination of the magnetic field inside the structure. The obtained results were satisfactory.