Faculty Publications
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Item This paper deals with the cost analysis of a two-unit repairable system subject to on-line preventive maintenance (on-line PM) and/or repair. The policy adopted here is that the on-line PM work of the operating unit is undertaken first on its completion, the repair work of the failed unit, if any, is subsequently carried out. All the random variables that arise in the analysis are assumed to be independently and arbitrarily distributed. An expression for the expected total cost incurred by the system in a specified time interval is obtained by considering the expected busy period of the server spent on various actions. The analysis is carried out using the regeneration point technique. © 1992.(Cost analysis of a two-unit repairable system subject to on-line preventive maintenance and/or repair) Gopalan, M.N.; Bhanu, K.S.; Murulidhar, N.N.1992Item Nonlinear system identification using memetic differential evolution trained neural networks(2011) Subudhi, B.; Jena, D.Several gradient-based approaches such as back propagation (BP) and Levenberg Marquardt (LM) methods have been developed for training the neural network (NN) based systems. But, for multimodal cost functions these procedures may lead to local minima, therefore, the evolutionary algorithms (EAs) based procedures are considered as promising alternatives. In this paper we focus on a memetic algorithm based approach for training the multilayer perceptron NN applied to nonlinear system identification. The proposed memetic algorithm is an alternative to gradient search methods, such as back-propagation and back-propagation with momentum which has inherent limitations of many local optima. Here we have proposed the identification of a nonlinear system using memetic differential evolution (DE) algorithm and compared the results with other six algorithms such as Back-propagation (BP), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Differential Evolution (DE), Genetic Algorithm Back-propagation (GABP), Particle Swarm Optimization combined with Back-propagation (PSOBP). In the proposed system identification scheme, we have exploited DE to be hybridized with the back propagation algorithm, i.e. differential evolution back-propagation (DEBP) where the local search BP algorithm is used as an operator to DE. These algorithms have been tested on a standard benchmark problem for nonlinear system identification to prove their efficacy. First examples shows the comparison of different algorithms which proves that the proposed DEBP is having better identification capability in comparison to other. In example 2 good behavior of the identification method is tested on an one degree of freedom (1DOF) experimental aerodynamic test rig, a twin rotor multi-input-multi-output system (TRMS), finally it is applied to Box and Jenkins Gas furnace benchmark identification problem and its efficacy has been tested through correlation analysis. © 2011 Elsevier B.V.Item Depth-Based Selective Blurring in Stereo Images Using Accelerated Framework(3D Research Center 3drc@kw.ac.kr, 2014) Mukherjee, S.; Guddeti, R.M.R.Abstract: We propose a hybrid method for stereo disparity estimation by combining block and region-based stereo matching approaches. It generates dense depth maps from disparity measurements of only 18 % image pixels (left or right). The methodology involves segmenting pixel lightness values using fast K-Means implementation, refining segment boundaries using morphological filtering and connected components analysis; then determining boundaries’ disparities using sum of absolute differences (SAD) cost function. Complete disparity maps are reconstructed from boundaries’ disparities. We consider an application of our method for depth-based selective blurring of non-interest regions of stereo images, using Gaussian blur to de-focus users’ non-interest regions. Experiments on Middlebury dataset demonstrate that our method outperforms traditional disparity estimation approaches using SAD and normalized cross correlation by up to 33.6 % and some recent methods by up to 6.1 %. Further, our method is highly parallelizable using CPU–GPU framework based on Java Thread Pool and APARAPI with speed-up of 5.8 for 250 stereo video frames (4,096 × 2,304). © 2014, 3D Research Center, Kwangwoon University and Springer-Verlag Berlin Heidelberg.Item Efficient Coherent Direction-of-Arrival Estimation and Realization Using Digital Signal Processor(Institute of Electrical and Electronics Engineers Inc., 2020) Dakulagi, V.; Alagirisamy, M.; Singh, M.A novel efficient coherent direction-of-arrival (DOA) estimation method is devised in this article. First, a new cost function without the knowledge of source number is developed exploiting the Toeplitz matrices' joint diagonalization structure. Then, the revised steering vectors are used in the place of projection weights of the steering vectors to reconstruct the power spectrum in both noise and signal subspaces. The coherent DOAs are estimated using the 1-D search. Furthermore, the computational complexity of the proposed method is significantly reduced using the Nystrom approximation. Finally, the developed theoretical model is implemented on the TMS320C6678 digital signal processor (DSP) to exemplify the efficacy of the novel method. © 1963-2012 IEEE.Item Navigation in GPS spoofed environment using m-best positioning algorithm and data association(Institute of Electrical and Electronics Engineers Inc., 2021) Pardhasaradhi, B.; Srihari, P.; Aparna., P.Intentionally misguiding a global positioning system (GPS) receiver has become a potential threat to almost all civilian GPS receivers in recent years. GPS spoofing is among the types of intentional interference, in which a spoofing device transmits spoofed signals towards the GPS receiver to alter the GPS positioning information. This paper presents a robust positioning algorithm, followed by a track filter, to mitigate the effects of spoofing. It is proposed to accept the authentic GPS signals and spoofed GPS signals into the positioning algorithm and perform the robust positioning with all possible combinations of authentic and spoofed pseudorange measurements. The pseudorange positioning algorithm is accomplished using an iterative least squares (ILS). Further, to efficiently represent the robust algorithm, the M-best position algorithm is proposed, in which a likelihood-based cost function optimizes the positions and only provides M-best positions at a given epoch. However, during robust positioning, the positions evolved due to spoofed pseudorange measurements are removed to overcome GPS spoofing. In order to remove the fake positions being evolved owing to wrong measurement associations in the ILS, a gating technique is applied within the Kalman filter (KF) framework. The navigation filter is a three-dimensional KF with a constant velocity (CV) model, all the position estimates evolved at a specific epoch are observations. Besides, to enhance this technique's performance, the track to position association is performed by using two data association algorithms: nearest neighbor (NN) and probabilistic data association (PDA). Simulations are carried out for GPS receiver positioning by injecting different combinations of spoofed signals into the receiver. The proposed algorithm's efficiency is given by a success rate metric (defined as the navigation track to follow the true trajectory rather than spoofing trajectory) and position root mean square error (PRMSE). © 2013 IEEE.Item A finite control set model predictive controller for single-phase transformerless T-type dynamic voltage restorer(Springer Science and Business Media Deutschland GmbH, 2023) Rajkumar, K.; Grimm, F.; Parthiban, P.; Baghdadi, M.; Lokesh, N.This paper presents a five-level T-type multilevel inverter (MLI) with a finite control set model predictive control (FCS-MPC) scheme for a single-phase transformerless dynamic voltage restorer (DVR). Typical two-level voltage source inverters are not suitable for high-power and medium-voltage applications due to high dv/dt, large size, and high cost of the filter, as well as high voltage stress on all switches. To overcome these issues, a reduced switch count T-type MLI-based transformerless DVR is proposed. The literature does not yet describe an FCS-MPC control scheme for transformerless T-type DVR. The FCS-MPC controller predicts the future of the trajectory of the controlled variables based on a prediction model. The optimal state is then selected using a cost function that is formed by combining predicted and reference variables. The proposed control technique minimizes the total harmonic distortion to a very low value compared to a linear PI controller. In addition, this control scheme is not dependent on a modulation scheme and linear control technique. The proposed system is validated by both simulation and experimental results. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.Item A Reduced Component Count Self-Balance Quadruple Boost Seventeen-Level Switched Capacitor Inverter(Institute of Electrical and Electronics Engineers Inc., 2024) Ahmed, S.; Raushan, R.; Ahmad, M.W.A switched capacitor multilevel inverter (SCMLI) enables high-quality output voltage waveforms for various industrial and renewable energy applications. SCMLI uses a combination of capacitors and switches to generate multiple voltage levels from a single dc source, thereby reducing the overall cost and size of the system. This article proposes a novel configuration of a 17-level SCMLI. The proposed converter can boost four times the input voltage by exploiting the series-parallel connection of capacitors with the dc voltage source. With simple pulsewidth modulated (PWM) control, the capacitor voltages are inherently balanced under different loading conditions. Furthermore, for 11 switches, only seven independent switching signals are required. Loss analysis reveals that the proposed SCMLI has significantly reduced conduction losses, capacitor ripple voltage, voltage stress, and cost function (CF) when compared with other topologies available in the literature. Finally, the simulation results are obtained at different loads and modulation indexes. The results are experimentally validated with a scaled-down laboratory prototype. © 2024 Institute of Electrical and Electronics Engineers Inc.. All rights reserved.Item Implementation of novel toroidal transformer-based single-phase multilevel inverter(Springer Science and Business Media Deutschland GmbH, 2024) Nageswar Rao, B.; Yellasiri, Y.; Shiva Naik, B.; Aditya, K.Multilevel inverters (MLIs) have gained traction for their application in high-voltage AC systems and renewable energy. They use fewer DC sources and switches in transformer-based designs to attain the necessary output voltage magnitude. Creating an efficient, high-gain MLI with reduced sources and switches demands meticulous design and substantial effort. This paper introduces a new multilevel inverter design utilizing a toroidal transformer with a reduced number of components. The new topology incorporates ten transistors and a single toroidal transformer. These components are arranged as two H-bridge modules and a bidirectional switch with a transformer to generate nine voltage levels. Notably, the inclusion of three complementary switch pairs in the inverter circuit simplifies the control strategy of the proposed inverter. This configuration enables the inverter to achieve more voltage levels and higher voltage gain using fewer components. Comparison with other existing nine-level inverters highlights the effectiveness of the new design in minimizing the cost function value. The performance assessment of the proposed inverter employs a cost-effective solution. Simulation and experimental results are provided to showcase the practicality and efficiency of the proposed nine-level inverter. © The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024.