Department of Electrical Engineering

Indian Institute of Technology Palakkad&nbsp;(IIT Palakkad or IIT PKD) is a public autonomous&nbsp;engineering&nbsp;and&nbsp;research&nbsp;institute located in&nbsp;Palakkad,&nbsp;Kerala. It was&nbsp;one of the five new&nbsp;IITs&nbsp;proposed in the&nbsp;2014 Union budget of India. The campus was inaugurated on 3 August 2015. The institute has 94 faculty, 978 students, and 63 non-teaching staffs.

IT Palakkad currently offers four-year Bachelor of Technology (B.Tech) and two years MS programmes in 8 different engineering disciplines including&nbsp;Computer Science, Electrical, Mechanical, Civil among others.

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IIT Palakkad

This paper presents a geometric framework for analysis of dynamics of flapping wing micro aerial vehicles (FWMAV) which achieve locomotion in the special Euclidean group SE(3) using internal shape changes. We review the special structure of the configuration manifold of such systems. This work addresses to extend the work in geometric locomotion to the aerial locomotion problem. Furthermore, there seems to be limited work in modelling of flapping wing bodies in a geometric framework. We derive the dynamic model of the FWMAV using Lagrangian reduction theory defined on symmetry groups. The reduction is achieved by applying Hamilton's variation principle on a reduced Lagrangian. The resultant dynamics is governed by the Euler-Poincare and Euler-Lagrange equations.

World University root node

arXiv preprint arXiv:1511.

A geometric approach to the dynamics of flapping wing micro aerial vehicles: Modelling and reduction

In this article, we consider a continuous-time state-dependent jump linear system (SDJLS), a kind of stochastic hybrid system, with the presence of uncertainties in system parameters. In SDJLS, we consider that the transition rates of the underlying random jump process depend on the state variable. In particular, we assume the transition rates to have different values across suitably defined sets to which the state of the system belongs, and address a problem of robust stability and stabilization analysis. We obtain sufficient conditions for robust stability and state-feedback stabilization in terms of linear matrix inequalities (LMIs). We validate the obtained sufficient robust stability and stabilization conditions with numerical examples. © 2015 Elsevier Ltd.

Nonlinear Analysis: Hybrid Systems

Robust stabilization of a class of state-dependent jump linear systems

Automatic Modulation Classification (AMC) is a essential component in Cognitive Radio (CR) for recognizing the modulation scheme. Many modulated signals manifest the property of cyclostationarity as a feature so it can be exploited for classification. In this paper, we study the performance of digital modulation classification technique based on the cy-clostationary features and different classifiers such as Neural Network, Support Vector Machine, k-Nearest Neighbor, Naive Bayes, Linear Discriminant Analysis and Neuro-Fuzzy classifier. In this study we considered modulations i.e. BPSK, QPSK, FSK and MSK for classification. All classification methods studied using performance matrix including classification accuracy and computational complexity (time). The robustness of these methods are studied with SNR ranging from 0 to 20dB. Based upon the result we found that combining cyclostationary features with Naive Bayes and Linear Discriminant Analysis classifiers leads to provide better classification accuracy with less computational complexity. © 2014 IEEE.

9th International Conference on Industrial and Information Systems, ICIIS 2014

Performance study of cyclostationary based digital modulation classification schemes

An automated noise-robust premature ventricular contraction (PVC) detection method is proposed based on the sparse signal decomposition, temporal features, and decision rules. In this Letter, the authors exploit sparse expansion of electrocardiogram (ECG) signals on mixed dictionaries for simultaneously enhancing the QRS complex and reducing the influence of tall P and T waves, baseline wanders, and muscle artefacts. They further investigate a set of ten generalised temporal features combined with decision-rule-based detection algorithm for discriminating PVC beats from non-PVC beats. The accuracy and robustness of the proposed method is evaluated using 47 ECG recordings from the MIT/BIH arrhythmia database. Evaluation results show that the proposed method achieves an average sensitivity of 89.69%, and specificity 99.63%. Results further show that the proposed decision-rule-based algorithm with ten generalised features can accurately detect different patterns of PVC beats (uniform and multiform, couplets, triplets, and ventricular tachycardia) in presence of other normal and abnormal heartbeats. © The Institution of Engineering and Technology 2015.

Healthcare Technology Letters

Robust detection of premature ventricular contractions using sparse signal decomposition and temporal features

Several methods have been proposed for detection and classification of power quality (PQ) disturbances using wavelet, Hilbert transform, Gabor transform, Gabor-Wigner transform, S transform, and Hilbert-Haung transform. This paper presents a new method for detection and classification of single and combined PQ disturbances using a sparse signal decomposition (SSD) on overcomplete hybrid dictionary (OHD) matrix. The method first decomposes a PQ signal into detail and approximation signals using the proposed SSD technique with an OHD matrix containing impulse and sinusoidal elementary waveforms. The output detail signal adequately captures morphological features of transients (impulsive and oscillatory) and waveform distortions (harmonics and notching). Whereas the approximation signal contains PQ features of fundamental, flicker, dc-offset, and short- and long-duration variations (sags, swells, and interruptions). Thus, the required PQ features are extracted from the detail and approximation signals. Then, a hierarchical decision-tree algorithm is used for classification of single and combined PQ disturbances. The proposed method is tested using both synthetic and microgrid simulated PQ disturbances. Results demonstrate the accuracy and robustness of the method in detection and classification of single and combined PQ disturbances under noiseless and noisy conditions. The method can be easily expanded for compressed sensing based PQ monitoring networks. © 2014 IEEE.

IEEE Transactions on Instrumentation and Measurement

Detection and classification of power quality disturbances using sparse signal decomposition on hybrid dictionaries

Voltage fed Dual Active Bridge (VF-DAB) is the simplest isolated bidirectional DC-DC converter topology with least number of high frequency tank elements. This paper addresses the issue of Phase Shift operated VF-DAB when used for energy storage applications due to their variable nature in terminal voltage based on the state of charge. Circulation currents and limitations in the softswitching range are the main drawbacks of VF-DAB when operated with phase shift control within the two active bridges and widely varying voltage at one port. This affect their overall efficiencies at low and mid loads. In this paper, a modification in VF-DAB is proposed which reduces the drawbacks of the conventional phase shift controlled DAB by having variable transformer turns ratio, thereby improving the efficiency of the overall converter at medium and light loads. The analysis and design guidelines for the proposed converter are briefly explained and validated with experimental results. © 2015 Korean Institute of Power Electronics.

9th International Conference on Power Electronics - ECCE Asia: "Green World with Power Electronics", ICPE 2015-ECCE Asia

Tap changing transformer based dual active bridge bi-directional DC-DC converter

A novel mechanism is proposed for transistors that exploits the negative differential capacitance of piezoelectric gate barriers. Electric field induced electrostriction modulates the thickness of a piezoelectric barrier. Piezoelectricity and electrostriction in a compliant piezoelectric barrier combine to provide negative differential capacitance (NDC) with internal charge amplification. The effect of the NDC in the gate capacitor of a FET is to boost the on-current, and to provide an opportunity for switching steeper than the 60 mV/decade Boltzmann limit, both highly desirable. © 2014 IEEE.

Technical Digest - International Electron Devices Meeting, IEDM

Sub-60 mV/decade steep transistors with compliant piezoelectric gate barriers

This paper presents a frequency tunable 5-bit true-time-delay digital phase shifter using radio frequency microelectromechanical system (RF MEMS) technology. The phase shifter is based on the distributed MEMS transmission line (DMTL) concept utilizing a MEMS varactor. The main source of frequency tuning in this work is a bridge actuation mechanism followed by capacitance variation. Two stages of actuation mechanisms (push and pull) are used to achieve a 2:1 tuning ratio. Accurate control of the actuation voltage between the pull to push stages contributes differential phase shift over the band of interest. The functional behavior of the push-pull actuation over the phase shifter application is theoretically established, experimentally investigated and validated with simulation. The phase shifter is fabricated monolithically using a gold based surface micromachining process on an alumina substrate. The individual primary phase-bits (11.25°/22.5°/45°/90°/180°) that are the fundamental building blocks of the complete 5-bit phase shifter are designed, fabricated and experimentally characterized from 10-25 GHz for specific applications. Finally, the complete 5-bit phase shifter demonstrates an average phase error of 4.32°, 2.8°, 1° and 1.58°, an average insertion loss of 3.76, 4.1, 4.2 and 4.84 dB and an average return loss of 11.7, 12, 14 and 11.8 dB at 10, 12, 17.2 and 25 GHz, respectively. To the best of the authors' knowledge, this is the first reported band tunable stand alone 5-bit phase shifter in the literature which can work over the large spectrum for different applications. The total area of the 5-bit phase shifter is 15.6 mm2. Furthermore, the cold-switched reliability of the unit cell and the complete 5-bit MEMS phase shifter are extensively investigated and presented. © 2015 IOP Publishing Ltd.

Journal of Micromechanics and Microengineering

10-25 GHz frequency reconfigurable MEMS 5-bit phase shifter using push-pull actuator based toggle mechanism

In recent years, automatic signal detection and modulation classification play a vital role in the field of cognitive radio applications. The majority of the existing signals detection and classification methods assume that the received signal is contaminated by additive white Gaussian noise. Under impulsive noise condition, the performance of the traditional modulation classification methods may be degraded. Therefore, in this paper, we investigate the application of sparse signal decomposition using an overcomplete dictionary for detection and classification of digital modulation signals. The overcomplete hybrid dictionary consists of impulse waveform and sine and cosine waveform for effectively capturing morphological components of the impulse noise and deterministic modulated signals. The proposed modulation classification method includes the following steps: sparse signal decomposition (SSD) on hybrid dictionaries, modulated signal extraction, matched filtering, and maximum likelihood (ML) classification. The performance of the direct ML and SSD-based ML classification methods are tested and validated using different modulation techniques under different Gaussian and impulse noise conditions. The proposed system achieves a classification accuracy of 89 percent at 0 dB SNR and hence outperforms the direct ML method. © 2015 IEEE.

2015 21st National Conference on Communications, NCC 2015

Digital modulation classification under non-Gaussian noise using sparse signal decomposition and maximum likelihood

Atmospheric profiles of water vapor and temperature can be estimated using appropriate retrieval algorithms based on radiometric measurements and atmospheric statistics. Radiometric measurements at multiple frequencies contribute information to profile retrieval, although at some frequencies the information they provide can be highly correlated with that at other frequencies due to similar sensitivities to changes in atmospheric pressure, temperature, and water vapor mixing ratio as a function of altitude. The goal for profile retrieval is to obtain as many independent measurements as possible, both to maximize the vertical resolution and to minimize the retrieval error of the profile. The goal of this study is to determine sets of frequencies in the range from 10 to 200 GHz that provide the largest amount of mutually independent information on water vapor and temperature profiles from ground and airborne instruments for clear sky measurements. Results of such a study are important and useful for frequency selection and design of microwave and millimeter-wave radiometers for humidity and temperature profiling. A branch and bound feature selection algorithm has been used to determine sets of frequencies between 10 and 200 GHz that have the greatest number of degrees of freedom (DOF) for water vapor and temperature retrieval. In general, it has been found that the frequency ranges of 20-23, 85-90, and 165-200 GHz are useful for water vapor profile retrieval, whereas the frequency ranges of 55-65 and 116-120 GHz are useful for temperature profile retrieval. Finally, an analysis has been performed to determine the impact of measurement uncertainty on the number of DOF of measurement and also on the vertical resolution. It was also found that vertical resolution is directly related to the number of DOF. © 2008-2012 IEEE.