Department of Electrical Engineering

&ldquo;IIT Jodhpur is committed to impart quality education to facilitate the creation of qualified, competent and responsible human resources to meet the emerging technological challenges of the world. It is working towards creating an equitable learning platform that is positive, accessible and effective in the face of the modern societal and scientific advancements.

Flexibility in curriculum, in all its academic programs, encompassing elements of teaching, research, creativity, innovation and entrepreneurship is the most unique feature of IIT Jodhpur. The Department of Science and Technology (DST), under the National Mission on Cyber Physical Systems, has identified IIT Jodhpur as a Technology &amp; Innovation Hub in the area of Augmented Reality and Virtual Reality. The institute has also been nominated as the coordinator for the Jodhpur City and Knowledge Cluster by the Office of Principal Scientific Adviser, Government of India.

The sprawling 852-acre IIT Jodhpur campus is a majestic tribute to the deep-rooted diverse cultural heritage of the region. The campus is an architectural masterpiece, which is slated to become an international exemplar of sustainability with net-zero energy, and advanced water and waste management strategies.&rdquo;

IIT Jodhpur

This study deals with a new version of hill-climbing (HC) algorithm for maximum power peak estimation of the solar photovoltaic (PV) panel, which has self-estimation (SEn) and decision-taking ability. Moreover, it is based on a single sensor, which is applicable for the PV array-fed battery charging. The working principle of Self-Estimated HC (SEHC) algorithm is based on three consecutive operating points on the power-current characteristic. By using perpendicular line analogy (PLA), these points decide direction, and an optimised operating position for next iteration, which is responsible for quick maximum power point tracking as well as improved dynamic performance. Moreover, in every new iteration, the step size is reduced by 90% from the previous step size, which provides an oscillation-free steady-state performance. Owing to a single sensor, the computational burden, as well as calculation complexity of the SEHC algorithm is less, so it can be simply implemented on a cheaper microcontroller. The effectiveness of the proposed technique is validated by MATLAB simulation as well as tested on the experimental prototype. Moreover, the performance of SEHC algorithm is compared with recent state-of-the-art techniques. The highly suitable and satisfactory results of SEHC algorithm show the superiority over the state-of-the-art methods. © The Institution of Engineering and Technology 2017

World University root node

IET Renewable Power Generation

Quick and oscillation free peak power estimation using SEHC algorithm for single-sensor-based PV-fed battery charging

In this paper, we proposes a discrete-time intermittent control to obtain a periodically monotonic tracking response using output feedback for a discretized linear time invariant system. In periodic intermittent control, the control is applied for some time interval and then we are not able to apply the control for the next few time interval. This cycle is repeated periodically. The periodically monotonic tracking is achieved by the periodically intermittent control by exploiting the Moore's algorithm for the eigen-structure assignment. Then a multirate output feedback technique is proposed for the designed control such that we are able to compute the control only using the output information. The simulation results are given to verify the theoretical analysis. © 2018 IEEE.

Proceedings of the IEEE International Conference on Industrial Technology

Periodically monotonic tracking using intermittent control with multirate output feedback

In this paper, we propose the periodic event-triggering based design of sliding mode control (SMC) for the linear time-invariant (LTI) systems. In this technique, the triggering instants are generated by a triggering mechanism which is evaluated periodically at those time instants when the state measurements are available. So, the continuous state measurement, as it is usually needed in the continuous event-triggering strategy, is no longer required in this proposed triggering strategy. The main advantages of this triggering mechanism are: (1) a uniform positive lower bound for the inter event time is guaranteed and (2) this technique is more economical and realistic than its continuous counterpart due to the relaxation of continuous measurements. In this work, we use SMC to design the periodic event-triggering condition where SMC is designed in such a way that it allows periodic evaluation of triggering rule while guaranteeing the robust performance of the system. Moreover, an upper bound of the sampling period for the periodic measurements is also obtained in this design. Finally, the simulation results are given to demonstrate the design methodology and performance of the system with the proposed event-triggering strategy. © 2018 Elsevier Ltd

Automatica

Periodic event-triggered sliding mode control

In this study, the authors present a robust trajectory tracking control for a class of uncertain Euler–Lagrange (EL) systems using event-triggered-based sliding mode strategy. Here, the sliding mode-based tracking control is designed to ensure the robust stability of EL systems in the presence of external disturbances/uncertainties. Unlike periodic implementation, in event-triggering strategy, the control signal is updated on demand subject to system stability, so the frequent periodic execution of control tasks is avoided. Here, the event-triggered implementation of the sliding mode-based tracking control achieves the robust stability with desired steady-state performance and reduced computations of control. To realise this, sufficient conditions are derived using Lyapunov analysis such that the proposed controller yields desired tracking performance. It is shown that the triggering condition proposed here ensures Zeno free execution of triggering sequence. Finally, the theoretical development of the study is illustrated through numerical simulation on a two-link robotic manipulator. © The Institution of Engineering and Technology 2018.

IET Control Theory and Applications

Event-triggered sliding mode-based tracking control for uncertain Euler–Lagrange systems

This paper presents a modified version of coupled neutronics-thermal hydraulics model of Advanced Heavy Water Reactor (AHWR) for control studies. Earlier reported models assume, for the sake of simplicity, that the steam drum level and pressure are being strictly regulated at their respective set points, thereby neglecting these dynamics. However, such models are not suitable for analysis / controller design for the normal mode (load following mode) of operation of AHWR wherein the demand power setpoint is adjusted with respect to fluctuations in steam pressure. The work reported in this paper bridges this gap by including the steam drum pressure and level dynamics in the model. This leads to a model suitable for investigating control related aspects of all operational modes of the reactor. Efficacy of the proposed model is demonstrated through nonlinear simulations. © The Authors, published by EDP Sciences, 2018.

Fulltext

MATEC Web of Conferences

Improved model of Advanced Heavy Water Reactor(AHWR)for Control studies

Single-phase inverter suffers an unwanted second-order ripple at DC input of it. A substantial amount of this ripple may propagate through the system components and inject into the DC source. This causes several problems; related to system efficiency, life, cost, size, reliability and stability. This paper proposes an adaptive non-linear sliding mode controller for quasi-switched boost inverter used mainly in microinverter applications. The proposed controller shapes the output-impedance of the boost circuit of quasi-switched boost inverter such that the propagation of the ripple to DC source is resisted. The proposed control technique is verified using Matlab-Simulink. © 2018 IEEE

2018 IEEE Industry Applications Society Annual Meeting, IAS 2018

Second-order harmonic ripple mitigation: A solution for the micro-inverter applications

This brief proposes an event-triggered composite control of a two time scale system. A periodic sampling requirement is relaxed and both slow and fast states of the system decide independently when transmitting their current measurements based on a time-dependent triggering rule. The distinct feature of this scheme is that it does not require synchronized measurement updates of its slow and fast dynamics. Further, the theory of singular perturbation is used to decouple the system into slow and fast subsystems, and stability of the system is established. The proposed control strategy guarantees convergence of system states to an adjustable region around origin excluding the Zeno behavior. Simulation results manifest the effectiveness of the proposed approach. © 2004-2012 IEEE.

Department of Chemistry

IEEE Transactions on Circuits and Systems II: Express Briefs

Event-Triggered Composite Control of a Two Time Scale System

Functional groups in organic compounds determine the properties of the compounds/molecules. When multiple functional groups are present, the dominant functional group determines majority of the properties of the compound. Hence priority based identification of functional groups is an important problem in chemistry. Fourier-transform Infrared spectroscopy (FTIR) is a commonly used spectroscopic method for identifying the presence or absence of functional groups within a compound, and the current approach for this task mainly relies on visual inspection and analysis of the FTIR spectral data. However, such visual identification process by humans is error prone, especially when patterns in the FTIR spectrum overlap, resulting in loss of uniqueness of features which help in identification of different functional groups in the unknown sample. Therefore, the main goal of this paper is to develop a machine-learning based classification system which can perform priority based functional group identification of organic molecules. To the best of our knowledge, this is the first effort to address this problem using machine learning (ML), and a unique aspect of our study is the incorporation of domain specific information into the process of classification by employing a set of priority rules generated from expert knowledge. We have carried out extensive study on real IR spectral data, first using a rule based approach and then using ML in an effort to improve the classification accuracy. Our analysis indicates that the basic rule based method is reasonably effective in predicting the presence (or absence) of functional groups. However, such approach is practically not accurate enough for the more challenging problem of priority based identification, and ML based classification offers much higher identification accuracies in this case. The primary reason is that ML algorithm can adaptively exploit data patterns to classify the functional group unlike the rule-based approach which uses a fixed set of rules for the said purpose. Finally, we have also carried out extensive statistical analysis of the results by using confidence intervals and permutation tests, in an effort to gain more descriptive information about the learning process, and not simply treat it as a black box. © 2018 Association for Computing Machinery.

ACM International Conference Proceeding Series

Priority based functional group identification of organic molecules using machine learning

Negative capacitance field-effect transistors (NCFETs) boost the electric field at the semiconductor-channel interface by virtue of the gate voltage amplification effect of a ferroelectric (fe) layer. NCFETs should be designed in such a way that this elevated field does not exceed the maximum electric field (Emax) determined by the reliability limit of the interfacial dielectric or NBTI/PBTI reliability. In this letter, a compact model-based methodology is presented to determine the NCFET design space considering several variables of the fe-layer and the baseline transistor, including the fe-layer thickness (Tfe), coercive field (Ec), remnant polarization (Pr), baseline transistor equivalent oxide thickness, supply voltage (Vdd), threshold voltage (Vth), and Emax. Using this methodology, an NC-FDSOI transistor is designed in TCAD, and the result shows that even without raising the maximum interface field as compared with the baseline transistor, NCFET achieves much better ION/IOFF ratio and sub-threshold swing while operating at lower Vdd. © 2018 IEEE.

IEEE Electron Device Letters

NCFET Design Considering Maximum Interface Electric Field

A unified compact model for gate-all-around (GAA) FETs is discussed. This single unified model can accurately model different shapes of GAA FETs. In this work, we present its validation with the reported GAA FETs: stacked GAA nanosheet, stacked nanowire MOS-FETs, Multi-bridge-channel MOSFETs and Twin silicon nanowire MOSFETs. This study shows that the BSIM-CMG unified multi-gate MOSFET model is ready for production design of silicon GAA based circuits and technology-product co-development for future technology nodes. © 2018 by TechConnect. All rights reserved.