Department of Electrical Engineering

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IIT Jodhpur

Swarm intelligence is applied to a module of high speed system design problem. To maintain power integrity in a high speed system, an effective methodology for suppressing the cavity-mode anti-resonances' peaks is presented. The optimal values and the optimal positions of the decoupling capacitors are found using three different swarm intelligence methods -particle swarm optimization, cuckoo search method and firefly algorithm. Optimum values and locations of decoupling capacitors are obtained, by which anti-resonances' peaks of loaded board are minimized. © 2012 IEEE.

World University root node

ISCAS 2012 - 2012 IEEE International Symposium on Circuits and Systems

Damping the cavity-mode anti-resonances' peaks on a power plane by swarm intelligence algorithms

Electric power quality, which is a current interest to several power utilities all over the world, is often severely affected by harmonics and transient disturbances. There is no unique model which can assess the power quality problem and to identify and classify them properly. Existing automatic recognition methods need improvement in terms of their versatility, reliability, and accuracy. The FUZZY LOGIC based tools have been applied for the PQ classification. This paper addresses Power quality problem classification by wavelet and fuzzy expert system. Major Key issues and challenges related to these advanced techniques in automatic classification of PQ problems are highlighted. New intelligent system technologies using DSP, expert systems, AI and machine learning provide some unique advantages in intelligent classification of PQ distortions. © (2012) Trans Tech Publications.

Fulltext

Advanced Materials Research

Classification of power quality problems by wavelet fuzzy expert system

The SVC (Static Var Compensator) based on voltage source converter (VSC) is used for voltage regulation in transmission and distribution system. The SVC can rapidly supply dynamic VARs required during system faults for voltage support. The apparent impedance is influenced by the reactive power injected or absorbed by the SVC, which will result in the under reaching or over reaching of distance relay. This paper presents simulation results of the application of distance relays for the protection of transmission systems employing flexible alternating current transmission controllers such as SVC. The complete digital simulation of the Static Var Compensator within a transmission system is performed in the MATLAB/Simulink environment using the Power System Block set (PSB). This paper presents an efficient method based on wavelet transforms, fault detection, classification and location using ANN technique which is almost independent of fault impedance, fault distance and fault inception angle.

Proceedings of the 2012 International Conference on Artificial Intelligence, ICAI 2012

A transient current based transmission line protection using neuro-wavelet approach in the presence of static var compensator

This paper presents a novel approach to monolithically implement a planar multiport radio-frequency (RF) microelectromechanical systems (MEMS) T-type switch. T-type switches are used as building blocks for redundancy switch matrix applications in space telecommunication. The T-type switch performs signal routing in three operational states. Two of them are turning states while the other one is a crossover state. The proposed design uses a series metal contact clamped-clamped beam SPST switches, four port cross junctions and a RF crossover. The simulated results for the entire T-type switch demonstrates an insertion loss of -0.46dB, return loss of better than -15.50dB and isolation better than -17.73dB for all states for a wideband frequency range 0-30GHz. The switch gives excellent RF performance near X-band and Ku-band which is the most widely used frequency range for satellite communication. © 2012 IEEE.

2012 International Conference on Computing, Electronics and Electrical Technologies, ICCEET 2012

Design and optimization of RF MEMS T-type switch for redundancy switch matrix applications

In this paper a generalized Simulink model has been developed for control of linear induction motor (LIM) by different control strategies (VVVF, CVVF and CFVV control). These control strategies have been implemented on a LIM based conveyor belt test-rig through dSPACE and IFM model. ©2012 IEEE.

IEEE International Conference on Sustainable Energy Technologies, ICSET

Implementation of VVVF, CVVF &amp; CFVV control strategies for control of LIM

In this paper, a dynamic stochastic resonance (DSR)-based technique has been proposed for contrast enhancement of dark and low contrast images in discrete wavelet transform (DWT) domain. Traditionally, the performance of a stochastic resonance (SR)-based system is improved by addition of external noise. However, in the proposed DSR-based approach, the internal noise of an image has been utilized for the purpose of contrast enhancement. The degradation due to inadequate illumination is treated as noise, and is used to produce a noise-induced transition of the image from a low-contrast state to a high-contrast state. Stochastic resonance is induced in the approximation and detail coefficients in an iterative fashion, producing an increase in variance and mean of the coefficient distribution. Optimal output response is ensured by selection of optimal of bistable system parameters. An iterative algorithm is followed to achieve target value of performance metrics, such as relative contrast enhancement factor (F), perceptual quality measures (PQM), and color enhancement factor (CEF), at minimum iteration count. When compared with the existing SR-based and non SR-based enhancement techniques in spatial and frequency domains, the proposed technique is found to give noteworthy performance in terms of contrast enhancement, perceptual quality, as well as colorfulness. © 2012 ACM.

Wavelet-based contrast enhancement of dark images using dynamic stochastic resonance

Objective video quality assessment (VQA) is the use of computational models to evaluate the video quality in line with the perception of the human visual system (HVS). It is challenging due to the underlying complexity, and the relatively limited understanding of the HVS and its intricate mechanisms. There are three important issues that arise in objective VQA in comparison with image quality assessment: 1) the temporal factors apart from the spatial ones also need to be considered, 2) the contribution of each factor (spatial and temporal) and their interaction to the overall video quality need to be determined, and 3) the computational complexity of the resultant method. In this paper, we seek to tackle the first issue by utilizing the worst case pooling strategy and the variations of spatial quality along the temporal axis with proper analysis and justification. The second issue is addressed by the use of machine learning; we believe this to be more convincing since the relationship between the factors and the overall quality is derived via training with substantial ground truth (i.e., subjective scores). Experiments conducted using publicly available video databases show the effectiveness of the proposed full-reference (FR) algorithm in comparison to the relevant existing VQA schemes. Focus has also been placed on demonstrating the robustness of the proposed method to new and untrained data. To that end, cross-database tests have been carried out to provide a proper perspective of the performance of proposed scheme as compared to other VQA methods. © 2012 IEEE.

IEEE Transactions on Multimedia

Low-complexity video quality assessment using temporal quality variations

Measurement of image quality is of fundamental importance to numerous image and video processing applications. Objective image quality assessment (IQA) is a two-stage process comprising of the following: (a) extraction of important information and discarding the redundant one, (b) pooling the detected features using appropriate weights. These two stages are not easy to tackle due to the complex nature of the human visual system (HVS). In this paper, we first investigate image features based on two-dimensional (2D) mel-cepstrum for the purpose of IQA. It is shown that these features are effective since they can represent the structural information, which is crucial for IQA. Moreover, they are also beneficial in a reduced-reference scenario where only partial reference image information is used for quality assessment. We address the second issue by exploiting machine learning. In our opinion, the well established methodology of machine learning/pattern recognition has not been adequately used for IQA so far; we believe that it will be an effective tool for feature pooling since the required weights/parameters can be determined in a more convincing way via training with the ground truth obtained according to subjective scores. This helps to overcome the limitations of the existing pooling methods, which tend to be over simplistic and lack theoretical justification. Therefore, we propose a new metric by formulating IQA as a pattern recognition problem. Extensive experiments conducted using six publicly available image databases (totally 3211 images with diverse distortions) and one video database (with 78 video sequences) demonstrate the effectiveness and efficiency of the proposed metric, in comparison with seven relevant existing metrics. © 2011 Elsevier Ltd. All rights reserved.

Pattern Recognition

Scalable image quality assessment with 2D mel-cepstrum and machine learning approach

A new approach is presented to analyze sliding mode control in discrete-time systems using an established reaching law, whereby the ultimate band is obtained to be lesser than any previous analysis done with the same reaching law. Also, the controller parameters are evaluated according to the ultimate band that is desired. The approach begins with defining several bands in the space of the surface variable, which are key to understanding the dynamics of it. Conditions on these band values are key to assigning appropriate values to the controller parameters. The switching gain obtained in this way comes out to be negative contradicting popular notion of non-negative switching gains used in sliding mode control. A case is also studied where the states measured contribute a quantization error in the system dynamics. The idea developed in analyzing the case without quantization is used while dealing with it. © 2012 IEEE.

Proceedings of IEEE International Workshop on Variable Structure Systems

Discrete time sliding mode control with minimal quasi sliding mode band

The super-twisting second-order sliding-mode algorithm is modified for a class of nonlinear systems with non vanishing unmatched disturbance. The proposed method is based on the modified super-twisting algorithm where the states can be estimated exactly in the presence of non vanishing unmatched disturbance. The value of the equivalent output injection is used to reconstruct disturbance directly. The effectiveness of the modified algorithm is shown by simulation. © 2012 IEEE.