Showing papers presented at "IEEE India Conference in 2008"

Vector control of a permanent magnet synchronous motor

Abstract: This paper is concerned with vector control of permanent magnet synchronous motor (PMSM). Recent research has indicated that PMSM could become a serious competitor to the induction motor (IM) for high performance servo applications. Mathematical model of a PMSM is developed with the help of Park and Clarke transformations. The concept of vector control is applied to PMSM to obtain linear dynamics similar to that of a DC motor. The linearized model consists of two control loops namely, current loop and speed loop. The objective of the control scheme is to achieve very fast response. The performance of PMSM drive system under different speed reference input is evaluated on the basis of simulation and experimental results. All the experiments have been done on PMSM with the help of ADMC-401 motor control DSP and an inverter circuit.

A wavelet based approach for classification and location of faults in distribution systems

Abstract: Electrical distribution system, which is the largest portion of networks, acts as a final power delivery path to the end users. Hence, ensuring its efficient and reliable operation is an extremely important and challenging task. Utilities, all over the world are competing for improvement in service to consumers, and the area of fault detection and diagnosis in distribution systems have attracted the significant attention of researchers in last few decades. With availability of inadequate system information and presence of high impedance faults, locating faults in a distribution system pose a major challenge to the utility operators. Most of the previous work on fault identification and location concentrated on estimating the status of circuit breakers and relays with aid of some algorithmic approaches. In this paper, a fault identification and location technique using wavelet multi-resolution approach for radial distribution systems are proposed. The current measurements at the substation, available in the distribution network have been utilized and the effectiveness of the proposed approach is demonstrated on 7-node and 19-node three-phase test systems.

Discrete wavelet transform and probabilistic neural network based algorithm for classification of fault on transmission systems

Abstract: This paper presents the development of an algorithm based on discrete wavelet transform (DWT) and probabilistic neural network (PNN) for classifying the power system faults. The proposed technique consists of a preprocessing unit based on discrete wavelet transform in combination with PNN. The DWT acts as extractor of distinctive features in the input current signal, which are collected at source end. The information is then fed into PNN for classifying the faults. It can be used for off-line process using the data stored in the digital recording apparatus. Extensive simulation studies carried out using MATLAB show that the proposed algorithm not only provides an accepted degree of accuracy in fault classification under different fault conditions but it is also reliable, fast and computationally efficient tool.

Fuzzy logic based supervision of DC link PI control in a DSTATCOM

Abstract: In a DSTATCOM, generally, the DC capacitor voltage is regulated using a PI controller when various control algorithms are used for load compensation. However, during load changes, there is considerable variation in DC capacitor voltage which might affect compensation. In this work, a fuzzy logic based supervisory method is proposed to improve transient performance of the DC link. The fuzzy logic based supervisor varies the proportional and integral gains of the PI controller during the transient period immediately after a load change. An improvement in the performance of the controller is obtained because of appropriate variation of PI gains using expert knowledge of system behaviour and higher sampling during the transient period. A 50% reduction in the error in DC link capacitor voltage during load change compared to a normal PI controller is obtained. The voltage waveform also has a faster settling time. The efficacy of the proposed strategy is proved using detailed simulation studies.

Coupled neutronics-thermal hydraulics model of Advanced Heavy Water Reactor for control system studies

Abstract: A coupled neutronics-thermal hydraulics model of advanced heavy water reactor (AHWR) which can be used for control system studies, simulation etc. is presented in this paper. A nodal model is developed for core neutronics and a simple two-phase thermal hydraulics model is developed from first principles. Neutronics-thermal hydraulics coupling is achieved through the void reactivity feedback model. Selection of a suitable nodalization scheme through steady state analysis is discussed, and dynamic response of the model is also presented.

Robust control design for nonlinear Magnetic Levitation System using Quantitative Feedback Theory (QFT)

Abstract: There is a growing demand for magnetic suspension systems, especially in the field of high accuracy multi-dimensional positioning. Magnetic levitation (Maglev) systems offer many advantages such as frictionless, low noise, the ability to operate in high vacuum environments and so on. Reliable and robust controller synthesis of this system is of great practical interest. Robustness is a key issue in designing a control system for a magnetic levitation as the models are never 100 percent accurate and the uncertainties in the model must be accounted. In the present work, a new approach using quantitative feedback theory (QFT) is presented for design of a robust two degree of freedom controller for magnetic levitation. Experimental tests are conducted to check the reliability and robustness of the designed control system by subjecting it to disturbances. The experimental test results show the control system design to be reliable and robust.

A license plate localization using morphology and recognition

Abstract: Locating the car license plate in an image a car is an important step in car license plate recognition/identification applications. This problem poses many challenges like location of license plate from images taken in poor illumination and bad weather condition; plates that are partly obscured by dirt and images that have low contrast. This paper presents a morphology based method for license plate extraction from car images followed by the segmentation of characters and reorganization. This algorithm uses morphological operations on the preprocessed, edge images of the vehicles. Characteristic features such as license plate width and height, character height and spacing are considered for defining structural elements for morphological operations. The recognition of the contents of the license plate is performed using cross correlation followed by neural network. The experimental results with a reasonably large set of car images are very encouraging.

Three-phase four-wire dstatcom with H-bridge VSC and star/delta transformer for power quality improvement

Abstract: A new topology of three-phase four-wire DSTATCOM consisting of a H-bridge VSC (voltage source converter) with a star/delta transformer is proposed for power quality improvement in the distribution systems. The proposed DSTATCOM (distribution static compensator) provides the voltage regulation or power factor correction by reactive power compensation along with harmonics elimination, load balancing and neutral current compensation in three-phase four-wire distribution system. The transformer has star connected primary and delta connected secondary and the load neutral point is connected to the neutral of star winding so that it provides a path to the zero sequence fundamental as well as harmonics neutral currents. This topology has the advantages of the use of two-leg, H-bridge VSC which reduces the size and cost of the DSTATCOM. The rating of the transformer is decided based on the compensating neutral current. The performance of the proposed DSTATCOM system is validated through simulations using MATLAB software with its simulink and power system blockset (PSB) toolboxes.

A comparative study of pulse shaping functions for ICI power reduction in OFDM system

Abstract: For orthogonal frequency-division multiplexing (OFDM) communication systems, the frequency offsets in mobile radio channels distort the orthogonality between subcarriers resulting in intercarrier interference (ICI). In this paper, pulse shaping technique for ICI power reduction in OFDM systems are investigated. A number of pulse shaping functions such as rectangular pulse (REC), raised cosine pulse (RC), Better then raised cosine pulse (BTRC), Sinc power pulse (SP) and Improved sine power pulse (ISP) have been considered for ICI power reduction. The performance of each pulse shaping function is evaluated and compared with each other using the parameters such as ICI power, SIR (Signal to Interference Ratio) and BER (Bit Error Rate). It is observed from simulation results that ISP pulse shapes outperform the conventional pulse shaping functions in ICI power reduction remarkably.

Cross-validation for graph matching based Offline Signature Verification

Abstract: Biometric is an authentication system that identifies a person depending on his physiological or behavioral traits. Signature verification is a socially accepted biometric method and is widely used for banking transactions. In this paper, we propose Cross-validation for Graph Matching based Offline Signature Verification (CGMOSV) algorithm. Database signatures are preprocessed in which signature extraction method is used to obtain high resolution for smaller normalization box. The dissimilarity measure between two signatures in the database is determined by (i) constructing a bipartite graph G, (ii) obtaining complete matching in G and (iii) finding minimum Euclidean distance by Hungarian method. We use Cross-validation principle to select reference signatures from which an optimum decision threshold value is determined. The given test signature is pre-processed and a test feature is extracted from it, which is then compared with the threshold value to authenticate the test signature. It is observed that our algorithm gives better Equal Error Rate (EER) for skilled forgeries and random forgeries compared to the existing algorithm.

Noise robust multimodal biometric person authentication system using face, speech and signature features

Abstract: In this work, we present a multimodal biometric system using face, speech and signature features which is robust to noise. Face recognition is done using subspace, principal component analysis (PCA) and linear discriminant analysis (LDA) techniques. Speaker recognition system is built using mel frequency cepstral coefficients (MFCC) for feature extraction and vector quantization (VQ) for pattern matching. An off-line signature recognition system is built using vertical and horizontal projection profiles (VPP, HPP) and discrete cosine transform (DCT) for feature extraction. A multimodal biometric database with face, speech and signature biometric features has been collected for 30 users. A multimodal biometric system is built using score level fusion. Sum rule was used for the fusion of the biometric scores. Experimental results show the efficacy of the multimodal biometric system when the biometric data is affected by noise.

A simple approach to space vector pwm signal generation for a five-phase voltage source inverter

Abstract: An alternative and simple space vector pulse width modulation (SVPWM) scheme for a five-phase voltage source inverter (VSI) is proposed in this paper. The proposed PWM scheme generates the inverter leg switching times, from the sampled reference phase voltage amplitudes and centre the switching times for the middle vectors, in a sampling interval, as in the case of conventional space vector PWM. Similar technique has been reported in the literature for a three-phase VSI which is further extended in this paper to a five-phase VSI. The proposed PWM scheme utilizes only the sampled amplitude of reference phase voltages for implementing the SVPWM. It does not involve any sector identification and a number of look tables thus considerably reducing the computation time when compared to the conventional space vector PWM scheme. The proposed technique thus is simple and less demanding for use in real time DSP implementation.

A novel wavelet assisted neural network for transmission line fault analysis

Abstract: In this modern era, electric power has become the basic need for the business world. The quality and reliability of power needs to be maintained for obtaining optimum performance. Now-a-days power has also become a business commodity. Hence, faultless and lossless transmission and distribution of power is necessary. Power faults must be identified quickly from various sources (eg. information from relays etc.) and corrected as soon as possible. Advanced signal processing tools such as discrete wavelet transform (DWT) can be used very effectively for parameterization and characterization of the fault signals. On the other hand, properly configured neural network (NN) can be utilized for classification of the faults based on the DWT signal. Presently Electromagnetic Transient Program (EMTP) is used for simulation of a model transmission system and DWT and NN is performed using MATLAB. Faults of various types at different locations along the transmission line have been simulated and attempts have been made to correctly identify and locate the fault.

Implementation of a LabVIEW-based automated wind tunnel instrumentation system

Abstract: Wind tunnel testing is fundamental for understanding the aerodynamic response and performance of space/road vehicles during the design process The measurement and control applications for wind tunnel testing typically include the wind speed measurement and control; static and dynamic force measurement, pressure profile measurement; and position and motion control for orienting the model with respect to the wind direction These applications are repetitive as well as time consuming hence needs to be automated This paper presents the implementation aspects of a reliable and accurate LabVIEW-based automated wind tunnel instrumentation system The implemented system permits the aerodynamic measurements to be performed efficiently and without intervention Most importantly, it relieves the operator of the usual responsibility for manually controlling the position and orientation of the model as well as the need to manually set the desired wind speed for the test The system has been implemented at National Wind Tunnel Facility, IIT Kanpur using virtual instrumentation technique and PXI architecture which enhances the productivity and reduces the cost through easy-to-integrate LabVIEW-based application software and PXI modular hardware However, the system presented in this paper has been configured for automated wind tunnel testing, but can also be easily configured to perform various test and measurement functions automatically for aerospace/military, bio-medical, process control, and robotics applications

Energy evaluation of two on demand routing protocol under stochastic traffic

Abstract: Energy efficient routing protocols play an important role in MANET mainly due to limited bandwidth and battery power. Route discovery and route maintenance are also the most concern areas in MANET. Many efficient routing protocols have been developed for MANETs over the past few years. They have been analyzed under the CBR traffic. This paper evaluates the energy consumption of two on-demand routing protocols: dynamic source routing (DSR) and ad hoc on-demand distance vector (AODV) under the stochastic traffic (Pareto traffic) in comparison to constant bit rate (CBR) traffic. Energy consumption mainly due to mobility pattern, traffic pattern, area shape, sending rate and number of nodes are evaluated with the help of ns-2 simulator. The simulation results demonstrate the energy consumption behavior of DSR and AODV under different traffic models.

Improving performance of adhoc TCP in Mobile Adhoc Networks

Abstract: Modifying transmission control protocol (TCP) to improve its performance in wireless networks has been a long-standing research problem. Many methods have been proposed to improve TCPpsilas performance in mobile adhoc networks (MANETs). Among them ad hoc TCP (ADTCP) uses an end-to-end approach which requires minimal changes at the sender and receiver, provides the flexibility for backward compatibility, maintains end-to-end TCP semantics and is TCP-friendly. It uses end-to-end measurements to detect congestion, disconnection, route change, and channel error, and each detection result triggers corresponding control actions. This paper proposes improved-ADTCP (I-ADTCP) an improvement on ADTCP. To improve the performance of ADTCP we consider following: ensure sufficient bandwidth utilization of the sender-receiver path; avoid the overloading of network by limiting TCPpsilas congestion window below the upper bound of bandwidth delay product (BDP-UB) of the path; check for incipient congestion by calculating inter-packet delay difference and short term throughput using relative sample density (RSD) technique. In an incipient congestion condition, we reduce congestion window limit (CWL) to half, which limits the packets send by the sender and does not allow the congestion to build up. Thus the algorithm tries to remain in congestion avoidance phase at all times by detecting and reacting to incipient congestion. Results of simulation using NS-2 show that I-ADTCP performance is superior to that of ADTCP for all levels of traffic intensity in the network. The good put performance is improved by 10%-30% in I-ADTCP.

Five-phase induction motor behaviour under faulted conditions

Abstract: In this paper, simple phase variable model of a five-phase induction motor drive is presented. The model is implemented using MATLAB/SIMULINK software. A number of electrical faults which are common in inverter fed drives are created. The faults considered are open circuit faults in one phase and two phases. As these motor drives are intended for disturbance free operation, the analysis of these is an important aspect to investigate under different faults. Simulation results for each fault have been provided and their detailed analysis has been carried out. Experimental proof is also provided to support the findings.

Harmonics and common mode voltage reduction in multilevel SPWM technique

Abstract: Conventional 2-level PWM inverters generate high dv/dt and high frequency common mode voltages which is very harmful in electric drives applications. It may damage motor bearings, conducted electromagnetic interferences, and malfunctioning of electronic equipments. This paper presents the simple methods to control the harmonics as well as common mode voltages in multilevel inverters using different structures of sine-triangle comparison method such as phase disposition (PD), phase opposition disposition (POD), and common mode voltage off-set voltage addition method. Simulation results obtained in Matlab/Power System Blockset toolbox confirms the effectiveness of these simple methods to control common mode voltages. Experimental results presented have been obtained using dSpace 1104.

Fault diagnosis in multi-level inverter system using adaptive back propagation neural network

Abstract: In this paper, a fault diagnostic system in a multilevel- inverter using a adaptive back-propagation neural network is developed. An adaptive back propagation neural network classification is applied to the fault diagnosis of a MLI system to avoid the difficulties in using mathematical models. A multilayer perceptron (MLP) network with 40 - 12 - 8 architecture is used to identify the type and location of occurring faults from inverter output voltage measurement. The neural network design process is clearly described. The classification performance of the proposed network between normal and abnormal condition and that among fault features is obtained. Thus, by utilizing the proposed neural network fault diagnostic system, a better understanding about fault behaviors, diagnostics, and detections of a multilevel inverter system can be accomplished.

Context based medical image compression with application to ultrasound images

Abstract: The basic goal of medical image compression is to reduce the bit rate and enhance the compression efficiency for the transmission and storage of the medical imagery while maintaining an acceptable diagnostic image quality. Because of the storage, transmission bandwidth and the limitations of the conventional compression methods, the medical imagery need to be compressed selectively to reduce the transmission time and storage cost along with the preservance of the high quality of the image. The other important reason of context based medical image compression is the high spatial resolution and contrast sensitivity requirements. In medical images, contextual region is an area which contains the most useful and important information and must be coded carefully without appreciable distortion. A novel scheme for context based coding is proposed here and yields significantly better compression rates than the general methods of JPEG and JPEG2000. In the proposed method the contextual part of the image is encoded selectively on the high priority basis with a very low compression rate (high bpp) and the background of the image is separately encoded with a low priority and a high compression rate (low bpp). As a result, high over all compression rates, better diagnostic image quality and improved performance parameters (CR, MSE, PSNR and CoC) are obtained. The experimental results have been compared to the Scaling, Maxshift, Implicit and EBCOT methods on ultrasound medical images and it is found that the proposed algorithm gives better and improved results.

Cement rotary kiln control: A supervised adaptive model predictive approach

Abstract: Considering the need of an advanced process control in cement industry, this paper presents an adaptive model predictive algorithm to control a white cement rotary kiln. As any other burning process, the control scenario is to expect the controller to regulate the temperature and the period of baking a fixed quantity of raw material as desired, as well as to have the concentration of the combustion gases under control. To achieve these goals, this work presents a strategy which includes multivariable online identification of the kiln process and a constrained generalized predictive controller. An MLP neural network model derived from real plant data of Saveh cement factory in Iran is used as the kiln process simulator. The control efforts are made taken into account the operating constraints. At last the proposed control strategy is modified so as to gain good disturbance rejection ability.

Performance analysis of energy-efficient modulation techniques for wireless sensor networks

Abstract: The limited energy source of battery driven wireless sensor networks, combined with the need for operational lifetimes of months to years, necessitates that energy efficiency be treated as the most important factor while designing these wireless distributed sensing systems. In this paper, we compare the performance of narrowband communications to ultra-wideband communications in a simplistic wireless sensor network model with a view to conserve energy. The comparison has been done under various channel conditions and we present some simulation results of these comparative studies in this paper.

Planning optimal intelligent metering for distribution system monitoring and control

Abstract: The accuracy of the distribution system state estimation is highly influenced by optimal meter allocation. This paper presents an innovative method for the placement optimization of power distribution system measurement. The goal of the method is to minimize the number of necessary measurements and required Remote Terminal Units, subject to the system observability requirements. The method based on particle swarm optimization algorithm is proposed to solve the problem of optimal placement of meters for distribution system The algorithm predicts the cost and location of meters for identification and collection of measurements from the system. The algorithm has been tested with IEEE and TNEB systems.

Optimal reactive power allocation using PSO-DV hybrid algorithm

Abstract: The reactive power allocation aspect has received considerable attention in present day power system operation and control. At heavy/light load periods, voltage control is provided by the controllable reactive sources, which are scattered throughout the transmission network, function in co-ordination. Reactive power dispatch problem can be formulated as a nonlinear constrained optimization problem. This paper presents a Particle Swarm with Differentially perturbed Velocity (PSO-DV) hybrid algorithm for optimal reactive power dispatch and voltage control of power systems. The PSO-DV is applied for optimal power system reactive power dispatch on an IEEE 30-bus system in which the control of bus voltages, tap position of transformers and reactive power sources are involved to minimize the transmission loss of the power system. The simulation results show the effectiveness and robustness of the proposed approach.

Signal strength ratio based handoff algorithms for cellular networks

Abstract: In this paper, we propose signal strength ratio (SSR) based handoff algorithms for cellular networks. Conventional handoff algorithms use averaging method to minimize fluctuations of received signal strength at a mobile station (MS). The algorithm provides good performance under dynamic propagation environment and provides very less delay as averaging of signal strength is not done. Performance of the proposed algorithm is compared with a handover algorithm based on combined relative and absolute signal strength measurements (CSS).

Differential evolution based environmentally constrained economic dispatch

Abstract: A reliable differential evolution (DE) based algorithm for solving environmentally constrained economic dispatch (ECED) problem is presented in this paper. Environmentally constrained economic dispatch (ECED) problem is obtained by considering both the economy and emission objectives. A price penalty factor approach is used to convert the bi-objective ECED problem into a single objective function. Equality constraints on power balance as well as inequality constraints on generation capacity limits of the generators and transmission losses are considered. A six-unit test system is used to demonstrate the effectiveness of the proposed method. The results of the proposed method based on DE are compared with other standard methods. It is found that convergence rate of the proposed method is excellent and the results obtained by the proposed method are superior in terms of fuel cost, emission output and losses. It is further observed that the computation time is considerably reduced in DE.

Distributed SCADA system for optimization of power generation

Abstract: According to the International Energy Agency (IEA) the worldpsilas energy needs would be well over 50% higher in 2030 than today at an average annual rate of 18% per year Modern Information Technology based Supervisory Control and Data Acquisition Systems (SCADA) assume greater significance in this context to derive maximum efficiency in power plant operations by ensuring optimal use of available resources In this paper, we present the salient features of scalable, distributed Intelligent SCADA System developed by Centre for Development of Advanced Computing, Thiruvananthapuram and being implemented in a chain of hydel power stations along the Teesta canal in West Bengal Besides individual plant monitoring and control, the system facilitates co-ordinated remote monitoring and control of three power stations and their associated canal water flow from a central station The building blocks of our SCADA technology are well proven in Steel plants, Thermal power plants, Power Distribution Automation Systems, Water treatment plants and other Process industries and Transportation systems The overall philosophy for system development and implementation is one of distributed structure with redundancy built in at all levels Advanced Human Machine Interface on modern computer systems, Intelligent Process Controllers, Distributed Control Nodes over the field bus and the plant optimization models depict the superiority of the system Hydel specific optimization modules are implemented to identify and predict in advance the leakage in fluid flow circuits, in order to take counter measures at the appropriate instants The system tries to utilize optimally the water flow in the canal for maximum power generation from the plants The implemented system architecture provides a progressive path of adaptive migration to tomorrow's advanced Automation Systems Technology After the SCADA system implementation, Power Stations -I, II & III has achieved an increase in power generation by utilizing the water at its maximum

Improved identification of nonlinear dynamic systems using Artificial Immune System

Abstract: Over the recent few years the area of artificial immune system (AIS) has drawn attention of many researchers due to its broad applicability to different fields. In this paper the AIS technique has been suitably applied to develop a new model for efficient identification of nonlinear dynamic system. Simulation study of few benchmark identification problems is carried out to show superior performance of the proposed model over the standard multilayer perceptron (MLP) approach in terms of response matching, number of training samples used and convergence speed achieved. Thus it is concluded that the AIS based model used is a preferred candidate for identification of nonlinear dynamic system.

Nonholonomic mobile robots cooperative control for target capturing

Abstract: For N unicycles moving in formation, a cooperative control strategy for target capturing including the steering angle regulation problem is proposed in this paper. The stabilizing method is based on LaSallepsilas invariance principle and ensures, in the 2D space, the target capturing. The method does not require motion planning. Hence, the convergence to the desired attractive set surrounding the target is asserted only by the control. Being given a desired attack angle for each entity (agent) when surrounding the target, the proposed cooperative control law permits to achieve this goal. The stability of the formation is realized when all unicycles converge to a certain attractive set.

Control scheme for electrical drive of solar powered vehicles

Abstract: The developments in the automotive electrical systems necessitate the design and development of effective control strategies for electrical drives. The objective of this paper is to design a control scheme for the electrical drive of a conventional auto rickshaw model to be driven by an electric actuator system, which is powered by an electric source. The source is a set of lead-acid batteries which are charged by solar photo voltaic panels. The control of the vehicle is obtained by the motor control system which comprises an armature voltage pulse width modulation (PWM) control. The PWM is in turn controlled by an ATmega8 micro-controller. Rheostatic braking is employed apart from the hydraulic brake system available. The parameters are continuously monitored and displayed using the instrumentation and display system. Critical parameters are monitored, and autonomous corrective actions are taken to ensure the safe operation of the vehicle.