Sudhansu MishraBirla Institute of Technology, Mesra | BIT Mesra · Department of Electrical and Electronics Engineering
Sudhansu Mishra
Doctor of Philosophy
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119
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Publications (119)
The study aims to introduce a novel machine learning approach for the prediction of product lengths by addressing diverse data types including numeric, textual and categorical data and extracting valuable information from the dataset to enhance prediction accuracy. This is achieved by employing methods that combine text vectorization, gradient boos...
The agriculture industry continues to expand, showing significant potential in meeting the escalating food demand. Renowned for its plentiful resources and substantial agricultural yield, India is progressively leveraging advancements in technology for mass production of superior quality goods. Notably, the integration of robotics has revolutionize...
In the domain of autonomous vehicle technology, the call for advanced, dependable methods to ensure secure, proficient road navigation is of utmost importance. This paper elucidates an innovative approach to mid-lane estimation, exploiting the strength of contour-based approaches. Our procedure incorporates image processing techniques and contour a...
In this paper, the development of an Indoor Autonomous Mobile Bot has been presented where the HC SR-04 Ultrasonic Sensor (US) and two HW 201 Infrared Sensors (IR) in addition to a NodeMCU ESP12E Module Controller has been used. The US is used to measure obstacle distance, while the two IR sensors measure the left and right wheel velocity. The ESP1...
Accurate and reliable control of a magnetic levitation (maglev) plant is challenging due to position tracking irregularities, parameter perturbations, external disturbances, and stringent dynamic requirements. In this study, a radial basis function neural network-based adaptive gain super-twisting sliding mode controller (RBF-ASTC) is proposed to a...
In this paper, an economically feasible and reliable operation of the IEEE 57 bus system for Optimal Power Flow (OPF) is proposed. The Improved Symbiotic Organisms Search (ISOS) algorithm is proposed for effective reactive power planning as an OPF issue. Further, the optimal position of Flexible AC Transmission Systems (FACTS) is taken into conside...
Androgen deprivation therapy (ADT) is frequently used to treat prostate cancer which is a widespread disease having a very low survival rate. A prolonged course of ADT can increase toxicity and drug resistance. This study proposes an adaptive therapy combining chemotherapy or immunotherapy with the discontinuation of hormone therapy to overcome the...
Reactive Power Problem (RPP) in power systems has been addressed using an effective bio-inspired meta-heuristic method called the Improved Krill Herd Algorithm (IKHA), in this paper. The IKHA improves upon the original Krill Herd (KH) algorithm by incorporating an elitism framework and a new levy flight distribution, enabling faster convergence rat...
Design, tuning and implementation of various control structures, such as one-degree of freedom (DOF) and two-DOF structures of both integer-order and fractional-order proportional integral derivative controller to stabilize the magnetic levitation plant, is proposed in this paper. The two-DOF structure has been formulated by incorporating a separat...
In this paper, a unique Machine Learning (ML) model namely, Adaptive Block Coordinate Descent Logistic Regression (ABCDLR), is proposed for segregating the movement of an Autonomous Mobile Robot (AMR) by framing it as three class problem, i.e., no, left, and right turn. The velocities of the left and right wheels, as well as the distance of the obs...
System identification techniques have proved to be the most effective methodologies for the modeling highly non-linear and system. For the purpose of real-time parameter estimation of a Maglev system, a Teaching Learning Based Optimization (TLBO) for updating the weights of Functional Link Artificial Neural Network (FLANN) model is proposed and imp...
Planning a collision-free path while preserving processing time and minimizing cost and time is a significant challenge in developing an autonomous mobile robot. Various optimization techniques for avoiding obstacles and path planning problems have been proposed in recent years. In this paper, the State Estimation Obstacle Avoidance (SEOA) algorith...
In recent times, satellite images are gaining popularity in the monitoring of agricultural fields, forest ranges, surveillance, and public commute convenience. In many places, it is difficult to implant cameras; thus in that scenario, satellite images establish to be very helpful. However, the raw image taken by the satellite needs to be preprocess...
As there is great demand in self-operating driving cars, probabilistic-based model is one of the emerging areas while considering the estimation of position of vehicles. In this paper, two probabilistic models are implemented in application to autonomous ground vehicles. Bayesian-state estimator has been repeatedly used for estimating the position...
In this paper, a novel approach based on Machine Learning (ML) concept, i.e., the Adaptive Stochastic Gradient Descent Linear Regression (ASGDLR) algorithm, is developed to segregate an AMR's directional movement as right and left turn. Moreover, the developed algorithm is employed for path planning and navigational purposes. Here, real-time veloci...
The widespread deployment of wind power generation (WPG) has adversely affected the flexibility and reliability of the power system during the operational period. Variable wind speed leads to the variable generation of wind energy systems (WES), which directly affects the operational reliability. This necessitates assessing WES's situational awaren...
The design of a Fractional Order PID controller (FOPID), to stabilize a second-order unstable magnetic levitation plant (MLP) with time delay, is proposed in this paper. The proposed two stage approach involves estimating the lower and upper bounds of the controller gains using an extension of the Hermite-Biehler theorem. Further, the optimal gains...
Mixed noise suppression from color Doppler ultrasound (CDUS) images is always a challenging task because the noise distribution usually does not have a parametric model and heavy tail. It affects the inherent features of the image awkwardly. Consequently, identifying an internal blockage or hemorrhage of the patient becomes arduous in such conditio...
This paper deals with the realistic combined environmental economic dispatch (CEED) problem, considering the running fuel cost along with emission as objectives taking power balance and operating limits of the generators as constraints. A new dynamic algorithm for multi-objective optimization, namely the modified multi-objective cat swarm optimizat...
In recent times, autonomous vehicle is gaining popularity in several of applications ranging from conventional transport system to nuclear reactor. The importance of autonomous vehicle increases manifold for those applications where it is not possible or very much risky for human to reach out. Many Artificial Intelligence techniques have been succe...
This work presents the design of a two Degree of Freedom fractional order PID (2-DOF FOPID) controller to stabilize a second order unstable magnetic levitation plant having time delay. To achieve the optimum performance of the system, the controller gains have been tuned using Monarch Butterfly Optimization (MBO), a recently developed evolutionary...
A Vertical Take-Off and Landing (VTOL) system is highly unstable and hence a robust controller is needed to stabilize it in finite time. This work presents the design of a Fractional Order Proportional-Integral-Derivative (FOPID) controller to stabilize the VTOL system. The applied FOPID controller has been tuned, to achieve the desired performance...
In this paper, an Interactive Teaching Learning Based Optimization (In-TLBO) algorithm is proposed for tracking multiple objects with several challenges. The performance of the four other competitive approaches, such as the Mean Shift (MS), Particle Swarm Optimization (PSO), Sequential PSO (SPSO), and Adaptive Gaussian Particle Swarm Optimization (...
In this paper, the teaching–learning-based optimization-based functional link artificial neural network (FLANN) has been proposed for the real-time identification of Maglev system. This proposed approach has been compared with some of the other state-of-the-art approaches, such as multilayer perceptron–backpropagation, FLANN least mean square, FLAN...
Electrocardiogram (ECG) signals are damaged by various types of noise during acquisition and transmission which may mislead the analysis. In this paper, an automated denoising technique based on time–frequency filtering approach is proposed. The S-transform based time–frequency method with morphological processing is employed to visualize the spect...
Abstract Multiplicative speckle is a dominant type of noise that spoils the inherent features of the medical ultrasound (US) images. Apart from the speckle, impulse and Gaussian noises also appear in the US image due to the error encountered during the data transmission and transition of switching circuits and sensors. The noise not only deteriorat...
This paper addresses the realistic economic emission dispatch (EED) problem of power system by considering the operating fuel cost and environmental emission as two conflicting objectives, and power balance and generator limits as two constraints. A novel dynamic multi-objective optimization algorithm, namely the multi-objective differential evolut...
Multi-Agent Systems are susceptible to external disturbances, sensor failures or collapse of communication channel/media. Such failures disconnect the agent network and thereby hamper the consensus of the system. Quick recovery of consensus is vital to continue the normal operation of an agent-based system. However, only limited works in the past h...
In this paper, Lagrangian-based method has been proposed for tuning the parameters of fractional order [Formula: see text] controller. In this method, the five parameters ([Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and [Formula: see text]) of fractional order [Formula: see text] controller (FOPID) are suitabl...
Abstract:
Background: The Gaussian and impulse noise corrupts the Computed Tomography (CT) images either individually or collectively, and the conventional fixed filters does not have the potential to supress these noise. These spurious noises affect the inherent features of CT image awkwardly. Hence, to handle such a situation adaptive Cat Swarm...
Background: Various kind of medical imaging modalities are available for providing noninvasive view and for analyzing any pathological symptoms of human beings. Different noise may appear in those modalities at the time of acquisition, transmission, scanning, or at the time of storing. The removal of noises from the digital medical images without l...
This work proposes a Multi Agent based Symbiotic Organisms Search (MASOS) by incorporating multi agent system (MAS) into the Symbiotic Organisms Search (SOS) algorithm. Each organism in MASOS acts as an agent participating in local interactions, to search for the optimum solution. In doing so, the conventional operations, namely, mutualism, commens...
The design of a two degree of freedom (DOF) proportional–integral–derivative (PID) controller is proposed in this paper to stabilize an unstable second-order plant having time delay. The lower and upper bounds of the controller gains for which the compensated system will exhibit a stable response, is determined using Hermite–Biehler theorem. In ord...
The design of a two degree of freedom (DOF) proportional–integral–derivative (PID) controller is proposed in this paper to stabilize an unstable second-order plant having time delay. The lower and upper bounds of the controller gains for which the compensated system will exhibit a stable response, is determined using Hermite–Biehler theorem. In ord...
Energy consumption in wireless sensor network (WSN) is one of the most critical issues. WSNs are conventionally battery operated sensor nodes which have short lifetime due to limited battery power and replacement of battery regularly is a costly and complicated task. Furthermore, in case of Wireless Body Area Sensor Network (WBASN), the problem ari...
In recent years, there has been substantial
research scope for Autonomous Unmanned Ground
Vehicles (AUGV) which is a burning topic for
researchers and scientists. The concept of AUGV had
been introduced way back to the 1920s and at that time
it was mainly applied in war fronts, such as in
Teletanks, Infantry Tanks, Goliath tracked mine etc....
Proper tuning along with design of Fractional
Order PID (FOPID) controllers is a problem that has received
immense attention and has been studied extensively since last
few decades. The FOPID controller has been proved superior
to the Integer Order PID (IOPID) controller in several aspects
which has led to its application in various nonlinear syste...
Designing a controller for the Twin Rotor MIMO System (TRMS) is a challenging task due to the presence of high non-linearity and cross-coupling between different elements. In this paper, a Fractional Order Integral-Proportional Derivative (FOI-PD) controller has been realized and implemented in both simulation and real-time for the control of pitch...
In this paper, a parameterless Jaya optimization based neural network filter named as Jaya-functional link multilayer perceptron (Jaya-FLMLP) is proposed for the elimination of Poisson noise from X-ray images. In this proposed adaptive filter, Jaya is applied for updating the weights of the FLMLP network. The proposed neural filter is a combination...
In this paper, 1-Degree of Freedom (1-DOF) and 2-Degree of Freedom (2-DOF) Integer Order (IO) and Fractional Order (FO) Proportional-Integral-Derivative (PID) Controller has been designed for the Magnetic Levitation (Maglev) system. Maglev is one of the most versatile research-oriented laboratory instruments in the field of control systems engineer...
This paper deals with the designing of linear optimal controller for Magnetic Levitation system (Maglev) in both simulation and real time. The Hamilton-Jacobi-Bellman (HJB) equation is employed to design the closed loop optimal control of infinite-time as well as finite-time Linear Quadratic Regulator (LQR) system with quadratic performance measure...
The application of Kalman Filter in the process of state estimation and thereby tracking a single object in motion is explored in this paper. A collection of images consisting of 200 different instances of the single object's position has been taken into consideration, whose location has been found with the help of background subtraction technique....
This paper has proposed a comprehensive coordinated planning framework for solving the network reconfiguration with simultaneous installation of distribution generation (DG) units, with an objective of minimizing the feeder power loss and boosting the voltage profile of the electric distribution system. A meta-heuristic bit-shift operator–based par...
Designing a suitable controller for a nonlinear and unstable plant is always very challenging to the control system practitioners. In this article, Integral - Proportional Derivative (I-PD) controller has been designed and implemented in simulation and real time for the Magnetic levitation (Maglev) system which is both nonlinear and unstable in nat...
Background:
The clinical magnetic resonance imaging (MRI) images may get corrupted due to the presence of the mixture of different types of noises such as Rician, Gaussian, impulse, etc. Most of the available filtering algorithms are noise specific, linear, and non-adaptive.
Objective:
There is a need to develop a nonlinear adaptive filter that...
This paper represents a novel method to find total harmonic reduction (THD) for photovoltaic cell with fuzzy logic. The proposed method is based on fuzzy controller method. In contrast to previous method, it gives more THD, whereas fuzzy controller method gives less THD compared to P&O and I&C method. The proposed method involves some processes of...
This study focuses on the design of controllers for inverted cart-pendulum system. This cart-pendulum system, a nonlinear one, has been linearized around the equilibrium point to obtain linearized model transfer function. In this paper, the design of two-loop proportional integral derivative (PID) controller that gives more flexibility to control t...
In this paper, a novel Set Point Weighted Proportional Integral Derivative (SPWPID) controller has been proposed for the Magnetic levitation (Maglev) system in Simulink and real time. The recently evolved Teaching Learning Based Optimization (TLBO) has been used to identify the suitable controller parameter values by optimizing the objective functi...
Fractional calculus has been a topic of great interest for the last few decades. The applications of fractional calculus can be found in the area of viscoelastic and chaotic systems, whose dynamics is expressed in the form of fractional differential equations. The ongoing research work is based on the design of 1- Degree of Freedom (1-DOF) and 2-De...
This article explores the methodology to design an effi cient controller for electric furnace temperature control system. Because of the presence of signifi cant amount of nonlinearity and time variability, it becomes very diffi cult to design a suitable controller to control the temperature of the electric furnace system. But in many practical pro...
This paper proposes a bit shift based Particle Swarm Optimization (PSO) technique to solve the problem of feeder reconfiguration for different load models in a power distribution system (PDS). The objective of feeder reconfiguration is to find the best possible radial network configuration in terms of minimum power loss. Feeder reconfiguration is t...
This paper is about the design of controllers for Magnetic Levitation (Maglev) system in both simulation and real time. Local linearization around the equilibrium point has been done for the nonlinear Maglev system to obtain a linearized model transfer function. In this study, the design of Integral-Tilted-Derivative (I-TD) controller has been prop...
In this paper, the design of a Proportional-Integral-Derivative (PID) controller for the cruise control system has been proposed. The cruise control system, which is a highly nonlinear, has been linearized around the equilibrium point. The controller has been designed for the linearized model, by taking the dominant pole concept in the closed loop...
This paper presented the application of genetic algorithm (GA) and simulated annealing (SA) for parameter optimization of parallel hybrid electric vehicle (PHEV). The proper selection of optimal size of vehicle’s power train components not only improves its performance but also increases the fuel efficiency and hence enhances the cost-effectiveness...
Gaussian noise is one of the dominant noises, which degrades the quality of acquired Computed Tomography (CT) image data. It creates difficulties in pathological identification or diagnosis of any disease. Gaussian noise elimination is desirable to improve the clarity of a CT image for clinical, diagnostic, and postprocessing applications. This pap...
With the increment utilisation of electrical motors in industry and commercial applications, the modelling of machine sizing involves a wide design of parameters. The incrementing size integrates the cost of the material and low power factor. This causes reduced in machine efficiency and it becomes bulky. In order to design a three-phase linear ind...
A power system with many generating units should run under economic condition. The operating cost must be minimized for any feasible load demand. However, along with the cost, the environmental emissions should also be considered, that make it multiobjective optimization problem. In this paper, we have used the standard IEEE test bus systems as a m...
The electrical short term load forecasting has been emerged as one of the most essential field of research for efficient and reliable operation of power system in last few decades. It plays very significant role in the field of scheduling, contingency analysis, load flow analysis, planning and maintenance of power system. This paper addresses a rev...
The scheduling of generation of a multiple unit power system for economic load dispatch has been approached in this paper in the environmental perspective. The minimum operating cost does not ensure a minimum emission condition. Thus it is considered as a multi-objective problem with the power balance and generator power limits as constraints. The...
This paper gives idea about neural network based non-linear adaptive filter, and the training of filter is executed using evolutionary computing.
. In this paper a very simple and efficient technique to tune a PID controller using fuzzy logic, in order to control a cart-pole type inverted pendulum system, has been proposed. Due to its high nonlinearity, inherent instability and multiple outputs, controlling the inverted pendulum is a challenging task. Here, the Simulink model of the inverted...
In this paper, the clonal particle swarm optimization (C-PSO)-based functional link artificial neural network model (FLANN) has been applied for the identification of a nonlinear system. System identification in different challenging situations such as noisy and time varying environments has been a matter of great concern for researchers and scient...
In this paper, a new computationally fast and efficient adaptive digital image filter has been proposed for denoising of digital medical image corrupted with additive white Gaussian noise. A particle swarm optimization-based functional link artificial neural network (FLANN) has been applied for this interesting and challenging problem. The three ot...
The modeling of electrical machine is approached as a system optimization, more than a simple machine sizing. Hence wide variety of designs are available and the task of comparing the different options can be very difficult. A number of parameters are involved in the design optimization of the induction motor and the performance relationship betwee...
In this paper, the induction motor variables have been optimized using modified Genetic Algorithm (GA). Selection of design variables for designing induction motor, not only decreases the losses but also improves the efficiency. A small increase in efficiency can leads to a big difference in energy saving. Here the optimized values of design variab...