Department of Electrical Engineering

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Defocus based Depth estimation has been widely applied for constructing 3D setup from 2D image(s), reconstructing 3D scenes and image refocusing. Using defocus enables us to infer depth information from a single image using visual clues which can be captured by a monocular camera. In this paper, we propose an application of Depth from Defocus to a novel, portable keyboard design. Our estimation technique is based on the concept that depth of the finger with respect to our camera and its defocus blur value is correlated, and a map can be obtained to detect the finger position accurately. We have utilised the near-focus region for our design, assuming that the closer an object is to our camera, more will be its defocus blur. The proposed keyboard can be integrated with smartphones, tablets and Personal Computers, and only requires printing on plain paper or projection on a flat surface. The detection approach involves tracking the finger’s position as the user types, measuring its defocus value when a key is pressed, and mapping the measured defocus together with a precalibrated relation between the defocus amount and the keyboard pattern. This is utilised to infer the finger’s depth, which, along with the azimuth position of the stroke, identifies the pressed key. Our minimalistic design only requires a monocular camera, and there is no need for any external hardware. This makes the proposed approach a cost-effective and feasible solution for a portable keyboard. © 2020, Springer Nature Switzerland AG.

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Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

A Defocus Based Novel Keyboard Design

This paper analyzes the physical layer secrecy (PLS) performance of a hybrid free space optical and radio frequency (FSO/RF) communication system under a modified selection combining scheme. The transmission scheme takes into account secrecy performance as well as diversity gain and ease of implementation. The effects of FSO link, namely the FSO atmospheric turbulence and the FSO receiver pointing error, are included in the analysis while the power amplifier (PA) inefficiency for the RF transmission is considered to have more realistic understandings on the system performance. The exact analytical expressions for the performance indicators including the average secrecy capacity (ASC) and secrecy outage probability (SOP) of the investigated mixed FSO/RF system are derived. The asymptotic SOP analysis reveals useful insights into the performance of the investigated mixed system. Analytical and simulation results are presented to evaluate the PLS performance of the proposed mixed system as well as to compare the performance of other hybrid systems with different setups. © 2020 The Author(s)

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Optics Communications

Secrecy enhancement of RF backhaul system with parallel FSO communication link

In this paper, we are proposing current-controlled hill-climbing strategy used in Maximum power point tracking (MPPT) of the solar photovoltaic array to Charge OFF Board Electric vehicle lithium-ion batteries within the safety limits and supported rating of batteries so that EV battery does not get damaged and can also increase the life of the battery. Here, a current sensor and potential difference sensor-based electric vehicle off-board battery charging by hill-climbing strategy is tested on MATLAB simulation. The satisfactory steady-state battery is charging within the rated charging limit, under variable solar irradiance. © 2020 IEEE.

2020 7th International Conference on Signal Processing and Integrated Networks, SPIN 2020

Current controlled charging scheme for off board electric vehicle batteries from solar PV array

In this study, an intuitive control technique based on 'fifth-order generalised-integrator (FOGI)' is proposed for gridconnected solar photovoltaic (PV) energy conversions system (SECS). In the grid-tied SECS, a single-phase single-stage topology is considered. Moreover, on solar PV array, partially shaded condition is considered, where for global maximum power point tracking, the human psychology optimisation is utilised. The prime intention of the control technique is, feed all the generated solar power at the unity power factor into the grid, which is successfully achieved by the FOGI-based control method. During the evaluation of the performance of control based on FOGI, different adverse conditions related to the grid and dynamic change of solar insolation are considered, where the proposed control technique's performance illustrates the fulfilment of the motive of the work. © The Institution of Engineering and Technology 2019.

IET Renewable Power Generation

Intuitive control technique for grid connected partially shaded solar PV-based distributed generating system

This study presents a novel leaky least mean logarithmic fourth (LLMLF) based control technique and learning based perturb and observe (LPO) maximum power point tracking (MPPT) algorithm, for optimal control of grid-tied solar photovoltaic (PV) system. Here, a novel LLMLF algorithm is developed for active component extraction from load current, and a novel LPO MPPT algorithm is developed for optimal MPPT operation. The proposed LPO is the improved form of perturb and observe (P&O) algorithm, where inherent problems of traditional P&O algorithm like steady-state oscillation, slow dynamic responses, and fixed step size issues are successfully mitigated. The prime objective of proposed LLMLF control is to fulfill the active power requirement of the loads from generated solar PV power, and excess power is fed to the grid. However, when generated PV power is less than the required load power, then LLMLF fulfills the load by taking extra required power from the grid. During this process, power quality is improved at the grid. The controller action provides reactive power compensation, power factor correction, harmonics filtering, and mitigation of other power quality issues. Moreover, when the solar irradiation is zero, then the dc link capacitor and voltage source converter act as distribution static compensator, which enhances the utilization factor of the system. The proposed techniques are modeled and their performances are verified experimentally on a developed prototype, in solar insolation variation condition, imbalance loading condition for linear/nonlinear loads, as well as in different grid disturbances such as over-voltage, under-voltage, phase imbalance, harmonics distortion in the grid voltage etc., where it has shown a very good performance. © 2010-2012 IEEE.

IEEE Transactions on Sustainable Energy

LLMLF-Based Control Approach and LPO MPPT Technique for Improving Performance of a Multifunctional Three-Phase Two-Stage Grid Integrated PV System

We propose the design of event-triggered (ET) discrete-time sliding mode (DTSM) control for a high-order discrete-time system via a reduced-order model-based approach. This design includes a triggering mechanism using a reduced-order state vector and a controller based on the modified Bartoszewicz' reaching law for a reduced-order model of the system, to stabilize the uncertain high-order system. The main advantages of using a reduced-order vector in the event condition are the low-order synthesis of the controller and the sampling pattern, which may be sparser than the full vector-based design. This motivation arises from the fact that relaxing a few components of the state vector in the triggering mechanism may decrease its rate of violation. An added advantage of the proposal is that the transmission of the reduced-order vector, particularly in a network-based implementation, can outperform the full-order based design due to the severe challenges that exist in the data network. The robust performance for the closed-loop system is achieved using the DTSM control. We show that our proposal guarantees the stability of the full-order plant with the reduced-order triggering mechanism. The control execution is Zeno-free because of the inherent discrete nature of the control. The efficiency of the proposed method is shown using the simulation results of a numerical example. © 2020 The Authors. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0)

IFAC-PapersOnLine

Event-triggered discrete-time sliding mode control for high-order systems via reduced-order model approach

The objective of this work is to achieve equal load sharing among parallel-connected converters by estimating the line resistance. Difference in line resistance leads to unequal power sharing in parallel-connected converters. Unequal load sharing is eliminated by droop control method. However, voltage regulation at the DC bus puts a limit on value of droop constant. To eliminate unequal power sharing estimation of the value of resistance of interconnecting cable is done by local voltage and current values of a converter. The estimated value is used to adjust the voltage reference so as to compensate the voltage drop on the connecting cable. This improves voltage at the DC bus and also leads to equal load sharing among converters. The proposed method has been validated through simulation of three parallel-connected boost converters. © 2020, Springer Nature Singapore Pte Ltd.

Lecture Notes in Electrical Engineering

Equal Load Sharing in DC Microgrid Using Line Resistance Estimation

We propose an updated compact model for mobility in Nanosheet FETs. This is necessary since Nanosheet FETs exhibit significant mobility degradation with thickness and width scaling caused by centroid shift, changing effective mass due to quantum confinement as well as various crystal orientations of the various conduction planes. The model takes all of these effects into account. It has been implemented in Verilog-A and validated with experimental data. To the best of our knowledge, this is the first compact model capturing the effect of nanosheet scaling on mobility. © 1980-2012 IEEE.

IEEE Electron Device Letters

Compact Model for Geometry Dependent Mobility in Nanosheet FETs

Distinguishing artwork from digital photographs is a simple task for a human observer. However, imparting this ability to a machine requires quantification of the quality of naturalness. In particular, the quality of 'glossiness' of a scene in a digital photograph as opposed to that in artwork or a painting of the same scene, is a challenging parameter to quantify. In this paper, a classification-based approach is proposed to quantify this glossiness of an image. The authors propose and validate the hypothesis that features extracted from the curvelet transform contain information regarding glossiness of an image. By training a support vector machine (SVM) classifier using curvelet coefficient features of images of varying naturalness, a framework to predict no-reference glossiness index for any general query image is proposed. The reliability of the proposed metric was then gauged by obtaining its correlation with subjective scores on naturalness provided by human observers. Results exhibit noteworthy performance of this metric in representing image glossiness, and could be further improved by using a larger training database and advanced classifiers. © 2020 IEEE.

Image glossiness from curvelet features using SVM-based classification

We propose a compact model for nanosheet FETs that take the effects of quantum confinement into account. The model captures the nanosheet width and thickness dependence of the electrostatic dimension, density of states, effective mass, subband energies, and threshold voltages and includes them in the charge calculation, resulting in an accurate terminal charge and current characteristics. The model has been implemented using Verilog-A in the BSIM-CMG framework for all simulations. It has been validated with band-structure calculation-based TCAD simulations as well as measured data. We have also highlighted the significance of quantum mechanical effects on analog and RF performance of the device. © 1963-2012 IEEE.