Multiphase Brushless Wound Field Synchronous Machines offer superior performance compared to conventional three-phase generators in Wind Energy Conversion Systems through reduced converter stress, enhanced fault tolerance, and independent spatial harmonic control. However, existing multiphase modeling approaches using multiple d-q reference frames assume complete sequence plane decoupling and simplified magnetic circuit behavior, limiting their accuracy for advanced machine configurations. This paper presents a dynamic modeling framework for dual-pole Brushless Multiphase Synchronous Generators (BMSG) capable of simultaneous dual magnetic field generation with distinct pole-pair combinations. The modeling approach incorporates strategic phase sequence control for field and excitation generation, and optimizes winding configurations for dual-pole operation. The framework integrates voltage behind reactance modeling to accurately capture the generator’s electrical behavior under the rotating diode bridge rectifier. Unlike conventional models, this paper demonstrates the winding function theory, vector space decomposition and voltage behind reactance model of the BMSG.

With the growing scale of integration of solar power in the grid, the supply side uncertainties in the grid are increasing. The increase in supply side uncertainties can result in a large number of future states that need to be analyzed for secure and optimal grid operation within a short window of time. The uncertainties in solar power in the future can lead to grid congestion. The grid may force to remain congested until the grid operator solve the optimal power flow (OPF) to decide and implement nonrenewable generation dispatch to avoid congestion in response to the fluctuation in solar power. This requires an early and real-time estimation of congestion and then a real-time optimal power flow (RTOPF) to decide optimal dispatch decisions to avoid congestion. Therefore in this article, we propose a novel two-stage approach called OPF$k$nearest neighborhood (OPF$k$NN). In the first stage, we propose a machine learning (ML) binary classification problem and optimized ML model to estimate the congested/noncongested state of the grid directly from the generation data. The second stage is a neighborhood-based search approach for RTOPF to decide the optimal generation dispatch of the nonrenewable generation to avoid congestion. The proposed OPF$k$NN has been implemented on the IEEE 118 bus system and Polish 2383 bus system to demonstrate the effectiveness of our proposed approach.

This paper introduces an adaptive reconfigurable grid following (GFL)/grid forming (GFM) control technique for a photovoltaic (PV) multilevel inverter which is connected to a renewable energy source (RES) dominant lower inertia grid. An asymmetric cascaded H-bridge (CHB) based multilevel inverter with binary asymmetry ratio is considered for the PV inverter in this work. This inverter topology has minimum isolated DC voltage source count requiring one PV source for supplying DC link of only one isolated H-bridge cell in each phase and the remaining DC links of the H-bridge cells are connected to floating capacitors which have natural balancing capability. The control structure for the inverter has the ability to transit flexibly between GFL and GFM control modes emulating their individual characteristics. Furthermore, an adaptive reconfiguration control technique is proposed which optimally controls the inverter between GFL and GFM control modes when any contingency event is detected. The proposed adaptive reconfiguration controlled inverter is simulated in MATLAB/Simulink environment to investigate the system performance under frequency based contingency events. A comparative study between different control methods is also implemented which establishes the superiority of the proposed adaptive control.

Brushless and magnetless synchronous machines are gaining popularity due to their numerous advantages in wind energy applications. These machines typically have three phases with dual, special windings or require harmonic excitations to create decoupled fields in airgap for brushless excitation and power/torque production. Multiphase electric machines offer benefits such as fault tolerance and reduced converter switch ratings per phase. Additionally, they can independently control multiple fields with varying numbers of pole pairs (spatial harmonics) using a single winding. This advantage improves torque density, slot fill factor, and derating while wirelessly transferring power to excite the rotor of wound-field synchronous machines. In this paper, a generating mode of operation is proposed to design multiphase electric machine windings. These windings can control the magnitude and angular location of dual pole magnetic fields, each with a different desired number of pole pairs. For instance, a 4/8 pole, 5-phase example is provided, and through controlling these dual poles, excitations and power generation are varied independently. The machine is validated using finite element analysis (FEA).

A position estimation method for the Synchronous Reluctance Motor (SynRM) based on an inductance model is proposed for light loads operating within the low to medium speed range. Under these conditions, the inductance exhibits a linear relationship with rotor position in specific regions. This linear characteristic of the inductance is utilized to determine the rotor position accurately. Simulations are conducted on a 1.0 kW FEM Model of SynRM prototype, validating the feasibility and effectiveness of the proposed method.

This paper introduces a Reluctance Equivalent (RE) EMF model for sensorless position estimation of synchronous reluctance motors (SynRMs). The unique salient structure of the SynRM results in varying reluctance paths associated with the stator phases. These variations in reluctance cause continuous changes in phase inductance relative to the rotor position, leading to the generation of RE EMF in the stator phase. The RE EMF model is initially analyzed in the abc plane and subsequently transformed into the stationary αβ plane for position estimation. The model’s validity is demonstrated using a Finite Element Model of the developed SynRM prototype

Accurate detection of current polarity is an important issue to achieve proper compensation of dead-time distortion in PWM VSI. This paper analyses the shift of zero-crossing instants of the inverter output current with respect to the modulating waveform of the inverter, after implementing the compensation process. In case, the current zero-crossings are detected by noting the notch positions of the uncompensated output voltage waveform, and compensation is continued on that basis, such a ‘shift’ ensures that the zero-crossing detection, post compensation is erroneous. This causes an error in current polarity detection, resulting in the problem for continuing the compensation process successfully. Detailed analysis of this phenomenon of current zero-crossing shift has been given in this paper, which depends on different operating parameters such as load series impedance angle, amplitude modulation index etc. Digital simulation and experimental verification have been performed to validate the proposed concept. This paper also proposes the application of this concept to achieve successful compensation, especially in the current-sensor-less compensation methods.

The integration of Information and Communication Technology (ICT) has revolutionized the power grids by facilitating bidirectional energy and information flow. However, this widespread integration of modern ICTs also brings significant security concerns, exposing the power grids to potential cyber-attacks. A load redistribution (LR) attack is a more realistic and practical type of generalized false data injection attack that can severely disrupt the secure and economic operation of the smart grid. Since their introduction in 2011, research into LR attacks has grown significantly over the last decade. As a result, LR attacks have evolved in terms of their attack models, objectives, impacts, and stealthiness. This review article aims to comprehensively analyze the advancements in LR attacks over the last decade, emphasizing their attack models, impact on the grid, and the defense mechanisms available against the LR attacks. This article also outlines the potential research gaps and presents future research directions in the field of LR attacks.

This paper proposes a reconfigurable cascaded H-bridge (CHB) multilevel inverter (MLI) topology with binary asymmetry ratio for inertia support to power electronics dominated grid (PEDG). The considered MLI topology requires only one isolated DC voltage source in each phase with the remaining H-bridge cells being supplied from self-balancing capable floating capacitors. The H-bridge cell with highest voltage rating of the proposed MLI is constructed with GTO based devices with the remaining H-bridge cells contain IGBT devices forming the H-bridges and a GTO based bypass device for bypassing them during any contingency operation. A novel contingency detection technique is also proposed for proper coordination between the different modes of operation of the proposed reconfigurable MLI topology. The performance of the proposed reconfigurable MLI along with its control technique is validated in MATLAB/Simulink environment under sudden frequency event of a weak grid. The supremacy of the proposed topology is also justified when its operation is compared with the conventional topology under contingency duration.

Research on electrical motors is important while developing an overall efficient powertrain of electric vehicle. Even though permanent magnet synchronous motors (PMSMs) exhibit greater efficiency in the low and medium speed region, the performance of such motors degrade in the field weakening region. Therefore, there is a need to explore alternatives for extended speed range of operation. Traditional squirrel cage induction motors have limited speed range due to their high leakage factor. Use of pole reconfiguration techniques can help such motors to extend the speed range of operation. This work investigates the efficiency improvement of regenerative braking controller by extending the constant power region through the method of pole changing. Criteria for selection of pole in regenerative mode of operation has been proposed. Simulation studies conducted through MATLAB/Simulink has been reported. Experimental validation of pole-changing controller has been conducted and sample experimental result has been shown.

The capacitor requirement of any power electronic converter plays a vital role in determining the converter's cost, weight and volume. In recent days several multilevel inverters have been reported in the literature for different applications. A high-resolution multilevel converter can offer several advantages w.r.t PWM converters with limited levels. This paper investigates the potential of double Level Doubling Network (LDN) based multilevel converter topology for fan and similar (for e.g., pump and compressor) applications using induction machines. The torque ripple and capacitor requirement of the converter is investigated in detail. Load current (along with reactive power demand), frequency change, and torque requirement in a given speed for such load are considered to assess the worst-case capacitor requirement. To validate the concept, a simulation model is developed in MATLAB/Simulink.

To design an efficient fusion scheme for the generation of a highly informative fused image by combining multiple images is still a challenging task in computer vision. A fast and effective image fusion scheme based on multi-resolution singular value decomposition (MR-SVD) with guided filter (GF) has been introduced in this paper. The proposed scheme decomposes an image of two-scale by MR-SVD into a lower approximate layer and a detailed layer containing the lower and higher variations of pixel intensity. It generates lower and details of left focused (LF) and right focused (RF) layers by applying the MR-SVD on each series of multi-focus images. GF is utilized to create a refined and smooth-textured weight fusion map by the weighted average approach on spatial features of the lower and detail layers of each image. A fused image of LF and RF has been achieved by the inverse MR-SVD. Finally, a deep convolutional autoencoder (CAE) has been applied to segment the fused results by generating the trained-patches mechanism. Comparing the results by state-of-the-art fusion and segmentation methods, we have illustrated that the proposed schemes provide superior fused and its segment results in terms of both qualitatively and quantitatively.

Owing to several advantages like easy integration with renewable energy systems, requirement of less number of power conversion stages, better stability and inter-connectivity etc., dc grids are becoming popular. This paper presents an alternative generating systems for dc applications. A recently proposed brushless and permanent magnet-less synchronous generator is used for such purpose. The machine is basically a synchronous machine where an induction machine (that is embedded in the same machine structure) is used for providing controlled excitation to the synchronous machine. The synchronous and induction machines are wound for different number poles such that they remain magnetically decoupled. The field winding of the synchronous machine (SM) is fed by the rotor-induced-emf of the induction machine (IM) through a rotating diode rectifier. For any operating speed, the IM has the ability to operate in different modes simply by varying its stator frequency. In the present work, the synchronous generator (SG) is connected to a dc load through a diode bridge rectifier (DBR). A simple controller is proposed that maintains the load-side dc voltage under different loading conditions. The q-axis component of the stator current of IM is used to regulate the field-excitation of SM using rotor-flux-oriented-control technique. Extensive PLECS simulations are presented to demonstrate the working of the proposed controller. A sample experimental results from the prototype shows the usefulness of the developed generator for dc-grid application.

Right information about the rotor resistance of the induction motor (IM) is more important in indirect rotor flux-oriented vector control (IVC) algorithm during different temperature conditions. Because, this resistance value will be involved in rotor flux position calculations which will influence on performance of the drive. In this paper, a new configuration of reactive power-based model reference adaptive control (Q-MRAC) has been developed to estimate the rotor resistance more accurately for electrical vehicle (EV) applications. Moreover, in EVs, as the motor speed is increasing from the below base speed (constant torque mode) to above base speed (constant power mode), the value the magnetizing reactance of IM will change. In this work, the effect of this magnetic branch variation is also considered during the estimation. Therefore, the dynamics of the drive, will be improved in all speed ranges of EVs. The proposed Q-MRAC algorithm is tested in MATLAB/Simulink software platform and results are reported. These results confirm the effectiveness of the proposed estimation technique.

A cascaded H-bridge multilevel inverter is presented in this paper. The inverter uses only one H-bridge that is excited from an isolated DC source and will be connected in cascade with a number of H-bridges whose dc links are formed by floating capacitors. Floating capacitors work on the principle of level doubling and have the capability to converge to the desired steady-state voltages without demanding any closed loop control techniques. In steady-state, all the DC link voltages maintain a binary asymmetric ratio. The inverter generates a seventeen-level phase voltage and a thirty-three-level line voltage at unity modulation index. Regardless of the modulation index and power factor, self-balancing of capacitor voltage is achieved. Simulation of the proposed converter is carried out in MATLAB/ SIMULINK.

The interconnection of microgrids with common energy storage may eliminate the problems associated with uncertainty of renewable energy generation systems. In this paper, a Universal Active Power Flow Controller (UAPFC) is proposed to control the active power flow between two microgrids and a Common Battery Energy Storage (CBES) system. UAPFC is a three port converter, where port-1 is connected in parallel with the line, port-2 is connected in series with the line, and port-3 is connected to the CBES through a bidirectional dc-dc converter. The UAPFC introduce a regulated voltage in series with the distribution line to control the power-flow between the microgrids with appropriate direction. Working of the UAPFC is validated in MATLAB with OPAL-RT based real-time simulation platform to confirm the usefulness of the concept.

In this paper, we analyze the superframe structure of the Medium Access Control (MAC) sublayer of IEEE 802.15.4 protocol (ZigBee), designed for Low-Rate Wireless Personal Area Networks (LR-WPANs), and evaluate the effects of the inactive portion of a superframe on average delay, and average power consumption. The four-dimensional Markov chain-based analysis of the slotted Carrier Sense Multiple Access with Collision Avoidance (CSMA/CA) algorithm presented in this work considers backoff freezing and acknowledged packet transmission that are not studied in the existing works. The analytical results prove that the performance of LR-WPANs depends significantly on the length of a superframe's active portion. We introduce a variable-Superframe duration-Beacon interval Ratio (SBR), which is utilized by tuning a few MAC parameters to achieve 35 percent reduced delay, on an average, compared to the existing state of the art. The results show that the proposed model also yields improved performance in terms of power consumption, for short and medium contention windows. In addition to the proposed analysis, this work provides optimized superframe order values that achieve trade-offs between delay and power consumption as demanded by user-provided QoS requirements corresponding to different contexts.

This paper presents a cascaded H-bridge multilevel inverter with single dc source. The dc link voltages of the H-bridges maintain a trinary asymmetric ratio among them. The inverter generates a phase voltage with seven levels and a line voltage with thirteen levels at unity modulation index. Voltage of the floating capacitor is self-balanced in open loop irrespective of the initial conditions. This is achieved by utilizing the redundancies associated with the space vectors of a three-phase trinary asymmetric multilevel inverter. Regardless of the modulation index and power factor, self-balancing of capacitor voltage is achieved. Simulation of the proposed converter is carried out in MATLAB/ SIMULINK.

Modular multilevel converter (MMC) has become a promising technology for medium/high voltage high power applications. Electric vehicles on the other hand, have a large number of series connected battery cells to enhance the output voltage to drive the connected motor. This paper applies the concept of modular multilevel converter for low power electric vehicle applications where, the batteries of the EV help in exchanging power with the motor. The batteries can discharge when feeding power to the motor and get charged when the motor runs into regenerative mode. Multi-carrier PWM technique is employed to generate the multilevel voltage waveforms and sorting technique is used to balance the battery voltages. Simulation study has been done in MATLAB/SIMULINK platform and it is observed that the voltages and State-of-Charge (SOC) of batteries are well maintained.

We present an efficient deep learning framework for identifying, segmenting, and classifying cell membranes and nuclei from human epidermal growth factor receptor-2 (HER2)-stained breast cancer images with minimal user intervention. This is a long-standing issue for pathologists because the manual quantification of HER2 is error-prone, costly, and time-consuming. Hence, we propose a deep learning-based HER2 deep neural network (Her2Net) to solve this issue. The convolutional and deconvolutional parts of the proposed Her2Net framework consisted mainly of multiple convolution layers, max-pooling layers, spatial pyramid pooling layers, deconvolution layers, up-sampling layers, and trapezoidal long short-term memory (TLSTM). A fully connected layer and a softmax layer were also used for classification and error estimation. Finally, HER2 scores were calculated based on the classification results. The main contribution of our proposed Her2Net framework includes the implementation of TLSTM and a deep learning framework for cell membrane and nucleus detection, segmentation, and classification and HER2 scoring. Our proposed Her2Net achieved 96.64% precision, 96.79% recall, 96.71% F-score, 93.08% negative predictive value, 98.33% accuracy, and a 6.84% false-positive rate. Our results demonstrate the high accuracy and wide applicability of the proposed Her2Net in the context of HER2 scoring for breast cancer evaluation.

Topologically flying capacitor multilevel configuration is one of the basic versions and this has been widely researched. However, topological simplicity cannot be fully exploited due to the capacitor balancing issues. This paper proposes a simple open loop control strategy for balancing the voltages across the capacitors. Three-level flying-capacitor multilevel inverter is considered for the investigation. Level doubling network principle ensures capacitor balancing without any closed-loop algorithm or any extra hardware. The study is also extended to equalize device utilization and reduce floating-capacitor rating. The controller is extensively simulated using MATLAB/Simulink. Experimental results from a laboratory prototype confirm the usefulness of the proposed concept.

Reliability, efficiency and cost are the deciding factors for the selection of photovoltaic central inverters those are used to evacuate power in large solar parks. Inverters used can be 2-level, 3-level (such as NPC and its variation) and cascaded bridge (symmetrical and asymmetrical) etc. Elimination of leakage current has a role on the modification of topology. In most of the cases a transformer is used to step up the voltage. Recently level doubling network (LDN) based asymmetric multilevel inverter topology (as central inverter for photovoltaic application) is reported in literature. This paper evaluates the performance of such topology in terms of efficiency, reliability and passive component requirement. Performance of the topology is then compared with the well-known topologies for photovoltaic central-inverter in industry. A 100kVA central photovoltaic inverter is considered for the study. Efficiency is estimated by using Semisel software available online by selecting appropriate devices for each cell. Better performance is expected for higher rating of central converter.

The concept of a novel Series Voltage Regulator (SVR) for controlling DC bus voltage of a radial DC microgrid is presented in this paper. The proposed SVR uses a dual active bridge DC-DC converter. It injects dynamic voltage in series with the DC grid to compensate resistive drop over the network. As a result, the voltage level at the different points of the grid becomes independent of load variation and stays within the specified limit. Note that the required power rating of the SVR is very low (say 2.5%) compared to the load demand considering 5% voltage regulation. In this work, the voltage regulator is connected at the mid-point of the grid, but it may be connected in some other points to get an optimal rating of the same. The proposed configuration is simulated in PSIM to check the dynamic performance under various operating conditions. The results show the effectiveness of such voltage regulator for radial DC microgrid, especially under critical load condition.

Brushless Generation Systems are currently in great demand for remote area micro-grid application. Dual Stator Winding Induction Generator (DSWIG), having two windings on the stator of same pole configuration and a squirrel cage rotor, has been identified as one of the suitable candidates for such application. In most of the configurations proposed so far, one of the winding is responsible for power extraction and the other for maintaining desired excitation. This paper proposes a control algorithm which facilitates power extraction through both the stator windings. MATLAB/SIMULINK based simulation studies illustrate the efficacy of the control method. A dSPACE 1103 based laboratory prototype has been developed and experimental results are presented.

A Carrier Based Double Signal PWM (CB-DSPWM) scheme in conjunction with a zero sequence signal to mitigate voltage unbalances at neutral point (NP) for three-level NPC converters is proposed. The scheme compensates the dc link capacitor voltage unbalances and eliminates the low frequency voltage oscillations at NP that appear under certain operating conditions of the converter. The voltage balancing is achieved by adding a zero sequence current component with the zero sequence voltage. Injection of the modified zero sequence with the modulation signal produces substantial average neutral current for all power factor (PF) angles. By incorporating the proposed PWM scheme, improved NP voltage balancing for full PF range and at high modulation indices are achieved. The dynamic performances of the proposed scheme are evaluated through simulation in MATLAB/SIMULINK and the practicability of the proposed algorithm is validated through experimental results.

This paper proposes a new control strategy for the Voltage Source Converter based Distributed Generation units operating in a Microgrid under unbalanced load conditions. The objective of the proposed control strategy is to control the positive sequence components and the negative sequence components of the Voltage at the Point of Common Coupling (PCC) in dq - frame, so that the Voltage will be controlled to the reference command rapidly. The load in a distribution system is usually unbalanced and highly unpredictable. The main objective behind controlling the negative sequence components of the PCC Voltage is to make sure that the Voltage at the PCC is balanced always irrespective of the unbalance in this load. Therefore the negative sequence components at the load will be minimized to a great extent, such that the Voltage supplied to the loads is nearly balanced. The proposed controller employs feed forward compensation in order to compensate for the effects of the cross coupling terms and the dynamics of the load, thereby the control structure becomes completely decoupled. The effectiveness of the proposed control structure has been implemented on the detailed switched model representing the Distributed Generation unit modelled in PSCAD/EMTDC.

Recently, the IEEE 802.15.6 Task Group introduced a new wireless communication standard that provides a suitable framework specifically to support the requirements of wireless body area networks (WBANs). The standardization dictates the physical (PHY) layer and medium access control (MAC) layer protocols for WBAN-based communications. Unlike the pre-existing wireless communication standards, IEEE 802.15.6 standardization supports short-range, extremely low power wireless communication with high quality of service and support for high data rates upto 10 Mbps in the vicinity of living tissues. In this work, we construct a discrete-time Markov chain (DTMC) that efficiently depicts the states of an IEEE 802.15.6 CSMA/CA-based WBAN. Following this, we put forward a thorough analysis of the standard in terms of reliability, throughput, average delay, and power consumption. The work concerns non-ideal channel characteristics and a saturated network traffic regime. The major shortcoming of the existing literature on Markov chain-based analysis of IEEE 802.15.6 is that the authors did not take into consideration the time spent by a node awaiting the acknowledgement frame after transmission of a packet, until time-out occurs. Also, most of the work assume that ideal channel characteristics persist for the network which is hardly the case in practice. This work remains distinctive as we take into account the waiting time of a node after it transmits a packet while constructing the DTMC. Based on the DTMC, we perform a user priority (UP)-wise analysis, and justify the importance of the standard from a medical perspective.

This paper presents a priority-based MAC-frame payload tuning mechanism with reduced energy consumption for healthcare systems that use Wireless Body Area Networks (WBANs). A fundamental problem in WBANs is to prioritize the physiological sensors depending on several health and external criteria. The challenge is to design a dynamic decision making model that can optimize the energy consumption of each physiological sensor. To address this problem we employ the concept of Fuzzy Inference System (FIS) in order to calculate Criticality Index (CI), which signifies the severity or the priority of the physiological data sensed by each sensor. Considering the obtained CI value we proceed with designing a Markov Decision Process (MDP) based dynamic decision making model in order to tune MAC-frame payload by optimizing the energy consumption of each sensor node. We achieve around 25% decrease in the overall energy consumption using our proposed mechanism.

The standardization of the IEEE 802.15.6 protocol for wireless body area networks (WBANs) dictates the physical layer and medium access control layer standards from the communication perspective. The standard supports short-range, extremely low power wireless communication with high quality of service and data rates upto 10 Mbps in the vicinity of any living tissue. In this paper, we develop a discrete-time Markov model for the accurate analysis of reliability and throughput of an IEEE 802.15.6 CSMA/CA-based WBAN under saturation condition. Existing literature on Markov chain-based analysis of IEEE 802.15.6, however, do not take into consideration the time a node spends waiting for the immediate acknowledgement frame after transmission of a packet, until time-out occurs. In this work, we take into consideration the waiting time for a node after its transmission, and accordingly modified the structure of the discrete-time Markov chain (DTMC). We also show that as the payload length increases, the reliability of a node decreases; whereas its throughput sharply increases.

Asymmetrical cascaded multilevel converters can generate more number of voltage levels for the same number of switching devices. Binary, Trinary and other different forms are available in literature. This paper has critically investigated such converters from the point of view of optimizing the number of levels. A mathematical tool to analyze the possibility of any asymmetric ratio for various three-phase topological configurations is developed. This mathematical tool is then used to find the ratio of asymmetry for three phase cascaded multilevel converters. Operation of the identified asymmetry is validated through simulation and experimental results using laboratory prototype.

Asymmetrical multilevel inverters can generate very high number of levels in output voltage. However, power shared by lower voltage bridges is very small compare to the bridges with highest voltage. To optimize hardware implementation, these lower voltage auxiliary bridges are usually fed by the dc bus of the main bridge by using isolated converter. This paper proposes a non-isolated buck-boost converter to feed the auxiliary bridges. Motivation of this work is to reduce the number of switches and better passive element (inductor) utilization. Function of the proposed non-isolated power supply and its control is verified in MATLAB/Simulink.

This paper deals with the problem of stator and rotor resistance variation due to prolonged operation in vector controlled induction motor drives. An online adaptation method is developed using Higher Order Sliding mode control principles and Lyapunov Stability theory to simultaneously estimate the stator and rotor resistances online and compensate them in order to achieve the flux orientation and hence the decoupled control of the machine. Matlab/Simulink based simulation results are presented to confirm the effectiveness of the proposed algorithm.

A unique formation of model reference adaptive reference (MRAS) using, active power (P), reactive power (Q) and fictitious quantities (X and Y) as the functional candidates is presented. The formulation of MRAS in the proposed form has the advantage that, no machine parameters are involved, except the rotor resistance. The reference and adjustable model of modified MRAS are computed in rotating reference frame, using reference value of voltages and currents in the reference model, whereas, reference voltages and actual currents in the adjustable model. Stability analysis of the modified P, Q, X and Y based MRAS is performed in all the four quadrants of speed-torque domain. It is found that P and Y MRAS have unstable points, whereas, Q and X MRAS are stable in all the four quadrant of operation. The algorithm can be implemented without the need of any extra hardware, thus making it suitable for retrofit applications. The proposed MRAS based speed sensorless vector controlled IM drive have been simulated in MATLAB/SIMULINK and is experimentally validated with the laboratory developed prototype. The prototype is built around a dSPACE 1104 controller board.

This paper presents a new approach for small-signal analysis of all types of dc-dc converters with any number of topological modes within a switching cycle. So far, sampled-data modeling and sensitivity analysis are mostly used for such a purpose. In both cases, the switching conditions implicitly appear in the small-signal matrices which increases the complexity of the computation for the system with a larger number of topological modes. Here, we propose an alternative approach based on Filippov's method, which studies the effects of each switching separately. It uses a shooting method with an event detector to locate a periodic steady-state, and, when the Newton-Raphson search process of the shooting method converges, it also gives the Jacobian matrix. The algorithm can be easily implemented in a software program as an analytical tool which is expected to be useful for fast and accurate frequency-domain analysis (by small-signal transfer functions) to facilitate controller design. Moreover, since it uses the Filippov's method, this algorithm can also predict the slow- and fast-timescale instabilities.

In this paper the analysis, design and fabrication of 3-coil based DC attraction type levitation scheme has been presented. In vehicle applications majority works have been reported based on four actuators based electromagnetic levitation system (EMLS). But in this prototype three electromagnets have been used at the three sides of the platform. The use of one magnet-coil, power amplifier and associated gate driver, controller circuit, position and current sensor is dispensed with the prototype. So there is considerable reduction of cost and weight of the proposed system and the hardware circuit is also simpler than four-coil structure. The objective is to levitate a platform under ferromagnetic guide-way normally used in electromagnetically levitated vehicle structure. The prototype (total mass 7.528kg) consists of three identical electromagnets placed at the three sides of a platform and the structure is made to remain suspended at different air-gap positions under a ferromagnetic guide-way - the arrangement that is normally used for EMLS. The structure of the levitated system has been constructed in-house. The three actuators have been controlled simultaneously by three similar single input single output (SISO) controllers utilizing the cascade Lead compensation control scheme. The design and implementation of the controller for such an unstable and non-linear system is the main aim of this study. The stable levitation has been demonstrated of the platform around an operating point.

A novel model reference adaptive system based stator resistance estimation algorithm has been proposed in this paper. A new functional candidate is introduced which is positive definite and does not depend on speed information for resistance estimation. This formulation decouples stator resistance and speed estimation in case of a Q-MRAS based sensorless drive. Also, restriction on selection of estimator gains becomes less rigid when the proposed estimator is used for stator resistance compensation in an X-MRAS based drive. Extensive simulation using MATLAB/SIMULINK and experimentation in dSPACE 1104 based laboratory prototype has confirmed the effectiveness of the proposed technique.

Increasing number of levels has always been a major motivation in the research of multi level inverters. This paper proposes a level doubling network and use this to almost double the number of levels of a multilevel inverter topology. While the approach is suitable to almost all the existing configurations, the unit works best for cascaded H-bridge topology. It has been shown that the level doubling network (LDN) does not consume any power over a complete cycle. The LDN is basically a capacitor fed half bridge topology where the capacitor voltage is self regulated. The proposal of the LDN opens up a new topological variation for the existing configurations. Operation of the circuit is verified by simulation result using MATLAB/Simulink and experiments from laboratory prototype.

This paper presents a novel approach to control power flow inside a high frequency transformer based multiport DC-DC converter. A multiport converter can interface a number of power sources and sinks with control of power flow among them. In a renewable energy sources (RES) integration scheme, the multiport converter operates like an accumulator where it collects power from each RES and dispatches it to the load port. Typically, power flow between any two ports happens through the leakage inductance of the transformer by imposing a required phase shift between fundamental component of two square wave voltages, impressed at the ports. However, each port is connected with the other ports by some inductance and hence the power flow from a particular source port to load port is not decoupled and can not be controlled independently. This paper proposes decoupling of source ports by eliminating the load port leakage inductance with a negative inductance, emulated by voltage injection in series with leakage inductance. A three port transformer based system is simulated to validate the principle. A scaled prototype of the three port transformer is designed and the effect of load port leakage inductance is analyzed through experiment.

In this paper, a fast and simple time domain technique is developed to generate the current reference for a Shunt Active Power Filter (APF) to compensate harmonics, reactive power and load unbalance. Using the proposed technique, the control logic is developed for a Shunt APF topology where a 2-level VSI Inverter is employed. MATLAB / Simulink - based simulations are performed to verify the effectiveness of the logic for all three compensations. Using simulations and experiments, it is shown that the proposed technique performs compensation much faster than other time domain techniques. Extensive simulations are performed to test the validity of the logic for a three phase three wire system.

Electrocardiogram (ECG) is the electrical activity of the heart indicated by P, Q-R-S and T wave. The minute changes in the amplitude and duration of ECG depicts a particular type of cardiac abnormality. It is very difficult to decipher the hidden information present in this nonlinear and nonstationary signal. An automatic diagnostic system that characterizes cardiac activities in ECG signals would provide more insight into these phenomena thereby revealing important clinical information. Various methods have been proposed to detect cardiac abnormalities in ECG recordings. Application of higher order spectra (HOS) features is a seemingly promising approach because it can capture the nonlinear and dynamic nature of the ECG signals. In this paper, we have automatically classified five types of beats using HOS features (higher order cumulants) using two different approaches. The five types of ECG beats are normal (N), right bundle branch block (RBBB), left bundle branch block (LBBB), atrial premature contraction (APC) and ventricular premature contraction (VPC). In the first approach, cumulant features of segmented ECG signal were used for classification; whereas in the second approach cumulants of discrete wavelet transform (DWT) coefficients were used as features for classifiers. In both approaches, the cumulant features were subjected to data reduction using principal component analysis (PCA) and classified using three layer feed-forward neural network (NN) and least square-support vector machine (LS-SVM) classifiers. In this study, we obtained the highest average accuracy of 94.52%, sensitivity of 98.61% and specificity of 98.41% using first approach with NN classifier. The developed system is ready clinically to run on large datasets.

Hybrid multilevel inverter topology is proposed for high power transformer less grid interactive photovoltaic power plant. Cascaded H-Bridge & Neutral Point Clamp topologies are hybridized to form this topology. Trinary asymmetric ratio of dc bus voltage is adapted for increasing the number of levels. Only three basic switching stages (two single phase H bridge cell and an NPC structure with common source for all phases) are used in each phase to obtain 53 levels in line to line voltage using trinary voltage rato. NPC structure with a common DC bus for all phases is connected to main photovoltaic (PV) array. This is kept at highest voltage to optimize the DC bus capacitor rating, and to reduce dc bus voltage ripple to increase MPPT efficiency. Third harmonic voltage is injected in order to increase the number of voltage levels further, and to increase the DC bus utilization. Increasing the number of voltage levels gives more flexibility to reduce Total Harmonic Distortion (THD) of the system and in turn reduction in cost and size of the power filter. Switching loss is optimized by operating the inverter at fundamental frequency. Nearest voltage level control modulation technique is adapted. The converter is simulated in MATLAB/Simulink. The results are validated through prototype experimentation in the laboratory.

The complex behavior of load resonant converters is investigated by using a newly developed stability analysis tool. In this paper we specifically consider the series-parallel load resonant converter with L-C output filter, controlled by the frequency modulation technique. The close loop variable frequency control consists of a feedback loop and a PI controller with voltage controlled oscillator (VCO). The VCO is used to convert the error in output voltage into a change of frequency to control the voltage in close loop system. Two converter designs are considered with different combinations of L-C output filter. With the variation of the proportional gain, Neimark-Sacker and symmetry-breaking bifurcations are observed.

This paper addresses the development of content-based medical image retrieval system for automated leukocyte recognition from microscopic images of peripheral blood smears. The proposed methodology ensembles Quaternion Fourier transform based segmentation and Gabor-wavelet describing textural features of leukocytes. This technique is computationally efficient because it captures local image information. The meaningful local regions of an image are segmented automatically without prior information. Gabor-wavelet based textural features are extracted from segmented leukocytes for image retrieval. Experimental results show 73.6% precision and 77.8% recall with respect to normal query image of leukocyte and 76.1% precision and 78.4% recall with respect CML query image.

An artificial neural network (ANN) based adaptive estimator is presented in this paper for the estimation of rotor speed in a sensorless vector-controlled induction motor (IM) drive. The model reference adaptive system (MRAS) is formed with instantaneous and steady state reactive power. Selection of reactive power as the functional candidate in MRAS automatically makes the system immune to the variation of stator resistance. Such adaptive system performs satisfactorily at very low speed. However, it is observed that an unstable region exists in the speed-torque domain during regeneration. In this work, ANN is applied to overcome such stability related problem. The proposed method is validated through computer simulation using MATLAB/SIMULINK. Sample results from a laboratory prototype (using dSPACE-1104) have confirmed the usefulness of the proposed estimator.

This paper reports the occurrence of symmetry-breaking bifurcation in the series-parallel load-resonant dc-dc converter with L-C output filter. The constant frequency phase shift modulation technique is employed with proportional- integral controller in the output voltage regulation. It is shown that the dynamics are not only related to the resonant components but are also heavily dependent on the output filter design. The first instability can be caused by smooth and nonsmooth symmetry breaking bifurcations. Stable as well as unstable periodic orbits are identified by a newly developed algorithm based on fundamental solution matrix. As a significant result of this paper, it is shown that the symmetry-breaking can be caused by a grazing event.

The paper demonstrates, both numerically and experimentally, the quasiperiodic and subharmonic operation in a load resonant DC-DC converter. The output voltage of the converter is controlled by a closed loop, applying constant-frequency pulse width modulation. The complexity of the system is contributed by fact that the state space is five-dimensional, with four switching surfaces dividing it into 9 subsystems. A method is developed to perform the stability analysis and to investigate the bifurcation sequences following the first instability in such a complex switching system.

In developing so called fuzzy expert systems, fuzzy rule bases have been considered with greater importance. In fact, a fuzzy rule base is a knowledgebase that models human cognitive factors. Fuzzy rules are linguistic ‘IF-THEN’ constructions where ‘IF’ part consists of a set of fuzzy variables and ‘THEN’ part includes a dependent fuzzy variable. In order to identify the underlying mathematical structure in the fuzzy rule base, we develop fuzzy linear and fuzzy polynomial regression techniques in this paper. And the estimation of model parameters is also shown using least-square approach. Finally, examples are illustrated to demonstrate the proposed model.