Bio-inspired evasion strategies under variable evader speed Lairenjam Obiroy Singh, Devanathan Rajagopalan International Journal of Automation and Control, 2024 The pursuit evasion game (PEG) is a natural phenomenon with implications for civilian and military applications. Researchers have developed methods to analyse PEG dynamics under various bio-inspired strategies, providing valuable insights into possible applications. Studies assume constant speeds for both the pursuer and evader, but this can result in less agile pursuit. This paper explores the trade-off between higher speed and less agility when the evader increases speed as the pursuer approaches. By simulating PEG trajectories, nine combinations of bio-inspired pursuer-evader strategies were tested using computer simulations. Results showed that a higher average speed may delay the evader's capture or even result in their escape in some instances. However, computer simulations indicate a mixed outcome for evader escape performance in cases of sudden turns and non-reactive evader strategies. The paper's results contrast existing results that rely solely on numerical computation of PEG outcomes under varying evader speeds.
Evaluation of pan-sharpening techniques using lagrange optimization Mutum Bidyarani Devi, Rajagopalan Devanathan Advances in Technology Innovation, 2020 Earth’s observation satellites, such as IKONOS, provide simultaneously multispectral and panchromatic images. A multispectral image comes with a lower spatial and higher spectral resolution in contrast to a panchromatic image which usually has a high spatial and a low spectral resolution. Pan-sharpening represents a fusion of these two complementary images to provide an output image that has both spatial and spectral high resolutions. The objective of this paper is to propose a new method of pan-sharpening based on pixel-level image manipulation and to compare it with several state-of-art pansharpening methods using different evaluation criteria. The paper presents an image fusion method based on pixel-level optimization using the Lagrange multiplier. Two cases are discussed: (a) the maximization of spectral consistency and (b) the minimization of the variance difference between the original data and the computed data. The paper compares the results of the proposed method with several state-of-the-art pan-sharpening methods. The performance of the pan-sharpening methods is evaluated qualitatively and quantitatively using evaluation criteria, such as the Chi-square test, RMSE, SNR, SD, ERGAS, and RASE. Overall, the proposed method is shown to outperform all the existing methods.
Pansharpening using data-centric optimization approach Mutum Bidyarani Devi, R Devanathan International Journal of Remote Sensing, 2019 Earth’s observation satellites provide simultaneously both multispectral (XS) and panchromatic (pan) images but XS image has a lower spatial resolution when compared to pan image. Pansharpening is a pixel-level fusion technique resulting in a high-resolution multispectral image in terms of both spatial and spectral resolution. The problem lies in maintaining the spectral characteristics of each channel of the XS image when pan image is used to estimate the high spatial XS image. Many techniques have been proposed to address the problem. A popular method involves a sensor-based approach where correlation among the XS channels and correlation between the pan and spectral channels are incorporated. In this paper, we take a wholesome approach based on the reflectance data irrespective of the sensor physics. A linear regression model is formulated between the XS channel and the panchromatic data. We formulate an optimization problem in terms of Lagrange multiplier to maximise the spectral consistency of the fused data with respect to the original XS data, and to minimise the error in variance between the reference data and the computed data. We validate and compare our method with IHS and Brovey methods based on evaluation metrics such as Chi-square test and the R 2 test. The implementation is done and presented using IKONOS satellite data.
Tuning linearization transformation using back-propagation algorithm S Janakiraman*, , Rajagopalan Devanathan, and International Journal of Engineering and Advanced Technology, 2019 The objective of linearization of a nonlinear system is to ensure smooth control of the linearized system through well-proven linear control methods. However, residual nonlinearities may still be present in a system after linearization either by design or due to mismatch between the system model and the actual plant. If the residual nonlinearities are not very significant, one can attempt to remove these by tuning the linearizing transformation by comparing the system to a linear canonical form. In this paper, we show how quadratic linearizing transformations of a three-phase horizontal gravity separator (TPS) model derived in an earlier paper by the authors can be tuned as in a neural network using error back-propagation by comparing it to a canonical linear model thus removing the nonlinearities within the tuning error limit.
Pansharpening of remote sensing data of earth satellite images Procedia Environmental Science Engineering and Management, 2019
Comparative study of the performance of application of bio-inspired strategies to pursuit evasion game under feedback laws International Conference on Control Automation and Systems, 2018
Quadratic linearization of three phase horizontal gravity separator S. Janakiraman, Rajagopalan Devanathan Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy Exploring Energy Solutions for an Intelligent Power Grid Tap Energy 2017, 2018
Closed loop decoupling control of a computer server system Journal of Advanced Research in Dynamical and Control Systems, 2018
Fusion of panchromatic and multispectral images using Lagrange optimization Proceedings 39th Asian Conference on Remote Sensing Remote Sensing Enabling Prosperity Acrs 2018, 2018
An analysis of variation of model parameters of text rank -frequency data with corpus size Journal of Advanced Research in Dynamical and Control Systems, 2018
Radix-2h online floating point multipliers Georgina Binoy Joseph, R. Devanathan 2014 IEEE Dallas Circuits and Systems Conference Enabling an Internet of Things from Sensors to Servers Dcas 2014, 2014
Analysis and application of quadratic linearization to the control of permanent magnet synchronous motor EEE Department, Hindustan Institute of Technology, Science, Chennai, India, A K Parvathy, Rajagopalan Devanathan, EEE Department, Hindustan Institute of Technology, Science, Chennai, India, V Kamaraj, EEE Department, SSN College of Engineering, Chennai, India, International Journal on Electrical Engineering and Informatics, 2014
Energy efficient dynamic multi-level hierarchical clustering technique for network discovery in wireless sensor networks International Congress on Ultra Modern Telecommunications and Control Systems and Workshops, 2011
Fieldbus for control and diagnostics H.K. Goh, R. Devanathan Proceedings of the 7th International Conference on Control Automation Robotics and Vision Icarcv 2002, 2002
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