PhD Thesis Defense Session

Abstract:
In recent years, distributed generators have proliferated in electrical systems. In this regard, the concept of microgrid has been newly proposed. A microgrid is a small local grid which comprises distributed resources and loads and is able to operate in grid-connected and islanded modes. Distributed generators are often interfaced to the electrical system by power-electronic converters. The main role of the interface converter is to control power injection. In the present thesis, the control of distributed generators interface converters in order to improve microgrid power quality is addressed. This way, the need for dedicated power quality conditioners such as active power filters will be alleviated. The control of interface converters is coordinated in a way that the distributed generators cooperate in compensating power quality problems and supporting loads demands in proportion with their rated powers. The proposed control structures can be classified as hierarchical (centralized) and local (decentralized) control schemes. In the hierarchical scheme, the power quality enhancement is managed by a central controller which sends proper control signals to distributed generators while in the other scheme local controllers are in charge of compensation control. Various methods are proposed to provide virtual impedance by distributed generators aiming to improve the sharing of load current components and to enhance microgrid power quality. Furthermore, the coordinated control of distributed generators converters and active filters is presented in order to provide more options for power quality compensation. The proposed approaches are applicable in both grid-connected and islanded operation modes of microgrid. Control systems design procedures are discussed in detail and simulations (using Matlab/Simulink software package) and experiments are performed in different cases to validate the proposed control approaches.

PhD Thesis Defense Session

Abstract:
In the final step of any filter design process, the desired center frequency, coupling factor and external quality factor (Q_ext) are used to determine the physical parameters of the filter. Although in the most cases the physical dimensions of a single resonator for a given center frequency are determined using exact analytical or simple approximate equations, usually such simple equations cannot be found to easily relate the required coupling factor and Q_ext to the physical parameters of the filter. Analytical calculation of coupling factor and Q_ext versus dimensions are usually complicated due to the geometrical complexities or in some cases such as microstrip resonators due to the lack of exact solution for the field distribution. Therefore coupling factor and Q_ext of various kinds of resonators, especially microstrip resonators, are related to the physical parameters of the structure by the use of time consuming full wave simulations. In this dissertation a surprisingly fast and completely general approach based on a soft computing pattern-based processing technique, called active learning method (ALM) and spatial membership functions is proposed to overcome the time consuming process of coupling factor and Q_ext determination. ALM is an adaptive recursive fuzzy learning algorithm based on brain functionality and specifications which models a complex multi-input single-output (MISO) function or system as a fuzzy combination of some single-input single-output (SISO) one. In the modeling process the multi-dimensional functions of coupling factor and Q_ext are broken down into their simpler aspects, their behaviors are extracted and then final model will be constructed by combining these simpler aspects.

Date: 2012/3/6 Monday
Location: Room 302 Electrical Engineering Faculty

PhD Thesis Defense Session

Abstract:
The design of high performance electronic components and systems such as waveguide structures, digital systems interfaces and connections, RF circuits and systems requires careful attention to physical modeling. In this way, the intrinsic physical inherent limitations of implementation processes can be accounted for, and adverse effects such as substrate coupling, electromagnetic interference (EMI) and metallic edges effects can be minimized. A high degree of physical fidelity of the models is necessary and can only be achieved by detailed analysis employing electromagnetic field solvers. The time domain Transmission Line Matrix (TLM) method has proven to be a powerful tool for solving electromagnetic field problems and has been successfully applied to the analysis of various complicated planar and general three-dimensional structures.
The design of complex systems operating at high frequencies requires that the design and analysis tools can handle circuit and field analysis at the same time since the design system may include a combination of lumped circuits, transmission line components such as couplers, power dividers, interconnections, and waveguide components that may contain field singularities due to metallic sharp edges or corners. The field analysis of such a hybrid system is a difficult task for a space and time discrete numerical method like FDTD or TLM method. Existence of field singularities, complex media and materials such as dispersive materials, metamaterials and ferrite is one of the main problems in using such methods to simulate the desired structures. What is intended in this project is to efficiently eliminate the effects of singularities while increasing the accuracy of results without any additional computational cost. In addition, the ability to simulate dispersive materials and complex structures such as metamaterials using TLM algorithm is another main objectives of this project.

Date: 2012/3/14 Wednesday
Location: Ebnesina Conference Hall, Electrical Engineering Faculty

PhD Thesis Defense Session

Abstract:
In cooperative networks a nodes (source) can exploit other nodes (relay) antennas to obtain spatial diversity. In such networks the source broadcast its symbols and the relays receive the transmitted symbols, and after applying their designed algorithm, forward them to the destination node.
In this thesis, a Multi-Antenna Multiple Relay Network (MAMR) in which the source and the destination have the same number of antennas (M) and each transmit antenna is virtually paired to a different destination antenna is investigated. Amplify and forward (AF) strategy is used in the relays where the relays multiply the received vector by a matrix, dubbed the relay matrix, and forward the resulting vector to the destination. In this thesis, the aim is to find the optimized relay matrix.
The main contribution of this thesis is presented in three parts: In the first part, by applying ZF algorithm in the reception and transmission for each relay, the MAMR network is transformed to M Single-Antenna Multiple Relay Networks (SAMR). In consequence, the network beamforming proposed for SAMR network can be deployed.
In the second part, the optimal relay matrix in MAMR network is obtained for two assumptions of complete and partial channel state information (CSI). It is assumed that a parameter (η) that control signal to noise ratio at destination is known. In the optimization problem, the Mean Square Error (MSE) is minimized as the object function subject to individual power constraint at each relay. The duality is used to solve the problem and the parametric relay matrices are obtained where the parameters are Lagrange multipliers. Then these parameters are computed numerically using Active Set method. To obtain η a method based on its statistical properties is proposed. Then we show that problem with partial CSI is a generalization of the complete CSI case and by changing some variables the partial CSI problem is converted to the completed CSI problem. Thus the same approach of the complete CSI can be use to obtain the relay matrices in partial CSI case.
At the end, the parametric relations are achieved for special cases: two relays network and a network with high SNR. The obtained matrices are similar to precoding matrix in MIMO systems.

Date: 2012/7/3,Wednesday  Time: 16:30
Place: Ibn Sina Amphitheater 
Electrical Engineering Department

PhD Thesis Defense Session

Abstract:
The predictive torque control (PTC) method is being implemented by means of speed sensor in most cases. Also, in model predictive control, adjusting the weighting factor is an important challenge. Therefore, the PTC method has not succeeded to pave its way to the industrial applications.
The contributions of this dissertation are categorized to two main parts. In the first part, two novel methods for weighting factor calculation are developed. In the first method, weighting factor of the cost function is calculated via an optimization method in order to minimize the torque ripple. In the second method, a look-up table base method for two-step prediction method is developed. The second part of the dissertation is dedicated to the proposed sensorless predictive torque control methods. Finite control set model predictive control (FCS-MPC) method and dead-beat method are combined with full order and voltage model observers. In order to reduce the effect of sensorless estimation on sensorless prediction, a robust prediction model is proposed for FCS-MPC and an inherently sensorless prediction model is proposed for dead-beat control. For precise estimation of the states, robust full order observer and robust reduced order observer are developed. The robustness of the prediction model and observers is achieved by H-infinity analysis.
In order validate the proposed methods, simulation and experimental results are presented and analyzed. Low speed performance, robustness against the variation of the stator and rotor resistances and robustness against current measurement offset are examined to select the most useful method.

Date: 2012/102/26 Sunday
Location: Room 304 Electrical Engineering Faculty

PhD Thesis Defense Session

Abstract:
Steady-state and dynamic power-flow control, particularly under heavily loaded system conditions, is an indispensable operational requirement for an interconnected power system. One of the most conventional FACTS devices used to control and transfer the power through certain paths is Phase Shifting Transformer (PST) but it is only more effective to control steady-state power control because of its large time constant. Rotary Hybrid Flow Controller (RHFC) as a new member of  Flexible AC Transmission System (FACTS) controllers  is formed of combination of RPST and other power flow controllers for providing dynamic power flow control. This thesis describes the steady state single phase equivalent circuit and P-Q operational characteristics of RHFC based on power injection model. However OPF makes an objective function to be optimal in the network but it causes other objectives diverge from their optimal value. Therefore, it has been made most of multiobjective optimal power flow to fix all of function in admitting limits from their optimal value. The optimal location and setting of RHFC incorporated in Optimal Power Flow (OPF) problem are found to optimize the total fuel cost, power losses, system loadability in the IEEE 14-, 30- and 118-bus test systems. Furthermore, the results obtained by these devices have been compared to that of PST, HFC  and UPFC. The optimization problem is solved in MATLAB and GAMS softwares using Non Linear Programming (NLP) and Mixed Integer Non Linear Programming (MINLP) as solution procedures. Simulation results show that RHFC has  desirable operation in technical and economical point of views.

Day: Jan. 31, 13:00 Afternoon
Class: 305

PhD Thesis Defense Session

Abstract:
Designing multi modal biometric systems proposes more precise and confident technique than single systems, with one biometric modality and one matcher, for authentication. Because absolute security is impossible, investigation of various invasions to these systems and analyzing vulnerability of systems against these attacks cause proposing suitable methods for designing secure authentication systems and increment their robustness.
This thesis introduces the possibility and probability of spoof attacks to each modality of biometric matchers and investigates the vulnerability of combined biometric systems against spoofing of their matchers' modalities. In this research for case study face and fingerprint traits are fused in score level for generation of bimodal biometric systems. For studying the vulnerability of systems, we have simulated spoofed scores of each matcher, up on proposed parameters by a novel method, then imposed invasion to authentication systems by these simulated scores, and at last calculated the vulnerability of them by an applicable method.
Vulnerability of biometric systems is evaluated in individual and bimodal forms by the most common fusion rules, included fixed combination rules contained analytic and fuzzy rules, and linear and nonlinear trainable rules against various possibilities and probabilities of spoofing and experimental results have been analyzed and compared. Comparison of quality and quantity outcomes of various fusion rules shows the robustness and vulnerability of each of them. In this thesis, spoofed scores database has been constructed from real standard scores database with various possibilities and probabilities of spoofing. Following the goal of research and for improve the robustness of biometric systems against spoofing, rules and guidelines include: finding suitable biometric modality and its matcher, robust combination rule and its robustness conditions are proposed as the contribution of these research.
Novel applied experimental researches and extraction method of their results show the importance of consideration to and more investigation the robustness of biometric systems and can help to development of security and creation the appropriate robustness in biometric systems by investigation their vulnerabilities with fusion rules and biometric traits.

Viva Date:   Sunday 8 Jan 2012
Place: Electrical Engineering faculty, Seminar Room (Class 303)

PhD Thesis Defense Session

Abstract:
In non-destructive testing, detection and clustering of defects is an important issue. One of the exploited methods to determine the defects is the use of c-scan images obtained from ultrasound test. The goal of the thesis is detection and clustering of defetcts in ultrasound images. Since the quality of the obtained image is not suitable for processing, it is necessary to enhance the quality of images before applying clustering method. The proposed denoising method in preprocessing step is based on the denoising the wavelet coefficients of the image by the use of independent component analysis and a spatial filter. The filter is used to determine the homogenous areas from the areas containing image details. The method has the capability to reduce different kind of noises including Gaussian, speckle and the noise with weak Gaussian distribution.
The proposed clustering algorithm is based on the rosette pattern. For this purpose, by the use of the rosette pattern, the image is sampled and according to the rosette pattern characteristics, the samples are mapped to the two dimensional linear space. In this stage, based on the neighborhood property of the samples, the clustering is performed. Finally, the clustered samples are remapped to the main space. Unlike the conventional clustering methods such as k-means and FCM algorithms requiring the number of clusters as one of the initializing parameters, in the proposed method, there is no need to initialize any parameter. Based on different data sets, the results show that the algorithm improves the capability of clustering, run time and determining the optimal number of clusters about 92%, 99% and 71% compared to k-means and FCM algorithms, rspectively. Moreover, in dealing with high resolution data sets, the efficiency of the algorithm in clusters detection and run time improvement increases considerably.

Day: Wednesday, Date: 2012/01/11 Time: 17
Class: 303

PhD Thesis Defense Session

Abstract:
Control of Induction motor due to it’s the nonlinear property is one of the most popular research topics recently. Vector control based algorithms which are used for proper functioning need to estimate the rotor speed and magnetic flux. In many applications, flux and speed must be estimated without using sensors. Thus, in these cases, it is necessary to obtain speed and flux by measuring voltage and current.
In this thesis, a nonlinear observer for estimating motor parameters based on Lyapunov function is presented. Using the Lyapunov theory, inputs regulating system and control system are earned which improve increases system performance.
Moreover a novel control speed sensorless indirect field-oriented control for the full-order model of the induction motor is presented. It provides local exponential tracking of smooth speed and flux amplitude reference signals together with local exponential field orientation, on the basis of stator current measurements only and under assumption of unknown constant load torque.
The absence of the flux model in the proposed algorithm allows for simple and effective time-scale separation between the speed–flux tracking error dynamics (slow subsystem) and the current error dynamics (fast subsystem). This property is exploited to obtain a high performance sensorless controller, with features similar to those of standard field-oriented induction motor drives. The theoretical analysis based on the singular perturbation method enlightens that a persistency of excitation condition is necessary for the asymptotic stability.
Extensive simulation and experimental tests confirm the effectiveness of the proposed approach. These results show the advantages of proposed observer in control of induction motor transient performances. The merits of the proposed control system are also indicated in comparison with a traditional optimal control system.

Day : Wednesday     Date: 2011/12/28    Time:15
Class : 305

PhD Thesis Defense Session

Abstract:
In this Thesis, a new average modeling approach for brushless excitation system with improved dynamics was developed using mathematical derivation method. Using an efficient VBR model of the generator and taking into account the dynamics of a variable excitation current during the averaging period are the main features of the presented
model. Moreover, the analytic nature of this model makes it suitable for analysis of variable frequency systems as well as control and identification purposes.
The proposed model simulation results compared with laboratory tests and experimental studies carried out in an actual power plant confirm the validity of the suggested model in steady state and transient operation. The developed excitation system model is an appropriate model for large disturbance simulations and transient stability studies, where a computationally efficient exciter representation is necessary.

Date: Sunday 13 Nov. 2011   Time: 15:00

Room: Class 301, Department of Electrical Engineering