Miracle-dz/UniFAR-FTUs huggingface dataset:
Design and Modeling of High gain DC-DC Converter in Mixed Signal Domain Control for PV based Microgrid Application

A high gain, modular and compact isolated DC-DC (Direct Current) converter with wireless power control scheme is proposed here. DC-DC converters have an important role in DC microgrid systems. Inputs from renewable energy sources like solar photo voltaic (PV) system and fuel cell is in the form of DC in the order of a few tens of volts. This low voltage cannot be used directly for microgrid applications. Hence, it needs to be boosted to the required high voltage (few hundreds of volts) by using DC-DC boost converters. However, the boosted voltage is limited to two to three times of input voltage due to the stability limitation of non-isolated converters. Hence, isolated high gain DC-DC converter control in mixed signal domain is proposed in this article. Further, the output voltage of the converter and current can be controlled wirelessly through digital signal processor (DSP) based on android/computer application. A detailed design of the converter, both in state space analysis and in hardware, is put forward. Further, the proposed converter is experimentally tested for various input conditions and its results are explained in detail.
Jocaml: mobile agents for Objective-Caml

Jocaml is a system for mobile agents built inside the Objective-Caml language. Jocaml eases the development of concurrent, distributed and mobile agent based applications, by expressing useful distribution abstractions using a small set of simple but powerful primitives taken from the Join-Calculus. The system provides total transparency for migration, application states (after migration, all threads resume their execution in the state before migration), communications (communication channels with other agents are kept during migration) and composition (sub-agents migrate with their parent agent). Other features of the Jocaml system are mobile objects with transparent remote method invocation, distributed garbage collection, failure detection and execution efficiency. Jocaml has already been used in several applications, such as a mobile editor, some distributed games and a distributed implementation of Ambients. This paper describes the Jocaml programming model and language, its current implementation and some interesting applications.
MRAS based Speed Sensorless Model Predictive Torque Control of Induction Motor Drive

This paper presents a speed sensorless operation of induction motor (IM) drive using model predictive torque control (MPTC) scheme. This emerging MPTC scheme selects the optimal switching vector that fulfils the user defined constraints for sensorless IM drive operation. The sensorless strategy adopted here is rotor flux based model reference adaptive system (MRAS). The overall scheme has been developed in Matlab/Simulink. Real-time results using a dSPACE -1103 based IM laboratory prototype are also presented to validate the tedious simulation study.
Small Signal Stability Assessment of an Inverter-Based Microgrid With Universal Droop and Internal Model-Based Controllers

In this paper, an internal model control (IMC)-based universal droop controller is proposed in order to improve the accuracy of the small signal model and subsequently the transient behaviour of the system. The universal droop control technique utilized for power sharing among the parallel operated inverters is based upon the droop phenomenon of voltage and frequency. An IMC-based controller is designed to maintain the system frequency and voltage within permissible limits. The non-linear differential and algebraic equations of the system are derived by including network, load, phase locked loop (PLL) and filter dynamics along with the proposed controller. These equations are linearised around operating points to form a state-space model of the microgrid system. An eigenvalue analysis is carried out using the linearised model to ascertain the small-signal stability of the system. The critical values of the controller gains are identified and the effectiveness of the proposed model is validated with time domain simulations. Also, the improvement in power sharing of the inverters is observed with the proposed model.
Kernel Adaptive Filtering Based on Maximum Versoria Criterion

Information theoretic learning based approaches have been combined with the framework of reproducing kernel Hilbert space (RKHS) based techniques for nonlinear and non-Gaussian signal processing applications. In particular, generalized kernel maximum correntropy (GKMC) algorithm has been proposed in the literature which adopts generalized Gaussian probability density function (GPDF) as the cost function in order to train the filter weights. Recently, a more flexible and computationally efficient algorithm called maximum Versoria criterion (MVC) which adopts the generalized Versoria function as the adaptation cost has been proposed in the literature which delivers better performance as compared to the maximum correntropy criterion. In this paper, we propose a novel generalized kernel maximum Versoria criterion (GKMVC) algorithm which combines the advantages of RKHS based approaches and MVC algorithm. Further, a novelty criterion based dictionary sparsification technique as suggested for kernel least mean square (KLMS) algorithm is proposed for GKMVC algorithm for reducing its computational complexity. Furthermore, an analytical upper bound on step-size is also derived in order to ensure the convergence of the proposed algorithm. Simulations are performed over various non-Gaussian noise distributions which indicate that the proposed GKMVC algorithm exhibits superior performance in terms of lower steady-state error floor as compared to the existing algorithms, namely the KLMS and the GKMC algorithms.
SyMon : Defending Large Structured P 2 P Systems Against Sybil

Sybil attack is one of the most challenging problems that plague current decentralized Peer-to-Peer systems. In Sybil attack, a single malicious user creates multiple peer identities known as sybils. These sybils are employed to target honest peers and hence subvert the system. In this paper, we propose a novel solution that enables all honest peers to protect themselves from sybils with high probability in large structured P2P systems. In our proposed sybil defense system, we associate every peer with another non-sybil peer known as SyMon. A given peer’s SyMon is chosen dynamically such that the chances of both of them being sybils are very low. The chosen SyMon is entrusted with the responsibility of moderating the transactions involving the given peer and hence makes it almost impossible for sybils to compromise the system. We show the effectiveness of our proposed system in defending against Sybil attack both analytically and experimentally.
Generation of an Rx-tTA: TetOp-Cre Knock-In Mouse Line for Doxycycline Regulated Cre Activity in the Rx Expression Domain

Genetic deletion of mouse genes has played a crucial role in our understanding of embryonic eye development. Transgenic, tissue specific Cre recombinase expression in various eye structures has facilitated these experiments. However, an early expressing, temporally-regulated, optic vesicle-specific Cre line has not been available. In this report, we detail the generation and analysis of a knock-in, inducible Cre line designed to drive recombination specifically within the Rx expression domain. Crossing this line with a reporter line demonstrates that recombination can be mediated within the early optic vesicle and throughout retinal development. Recombination can also be mediated in the Rx-expressing, ventral diencephalon and future posterior pituitary gland. Furthermore, it was demonstrated that dietary doxycycline could effectively modulate Cre activity. This line has the potential to facilitate conditional knock-out experimentation to study early retina and/or posterior pituitary development.
Computing repair trees for resolving inconsistencies in design models

Resolving inconsistencies in software models is a complex task because the number of repairs grows exponentially. Existing approaches thus emphasize on selected repairs only but doing so diminishes their usefulness. This paper copes with the large number of repairs by focusing on what caused an inconsistency and presenting repairs as a linearly growing repair tree. The cause is computed by examining the run-time evaluation of the inconsistency to understand where and why it failed. The individual changes that make up repairs are then modeled in a repair tree as alternatives and sequences reflecting the syntactic structure of the inconsistent design rule. The approach is automated and tool supported. Its scalability was empirically evaluated on 29 UML models and 18 OCL design rules where we show that the approach computes repair trees in milliseconds on average. We believe that the approach is applicable to arbitrary modeling and constraint languages.
Development Trends and Future Prospectus of Control Systems Serving to Hydropower Plant

Hydropower system is a complex system comprising of hydraulic, electric and mechanical components and their control systems. The modern hydropower system is more complex because of variable speed operation and a specific control system for starting of pump turbine in case of pump storage. So it needs an advanced modelling and control techniques for optimum utilization of hydropower plants. This paper gives an overview of various control systems applied to hydro generating equipment. Various control techniques and controllers for the hydro turbine governing system, excitation control system, smooth starting of the pump, electrical braking for hydro generator, CO2fire protection and electrical protection system have been reviewed. Further, future vision and design challenges associated with the hydropower control system are addressed.
Modelling and Control of High Step-Up Gain Multi-Phase Interleaved Coupled Inductor Boost Converter

Interleaved Coupled Inductor Boost Converter (ICIBC) is widely used for high step-up gain and high power application. Interleaved coupled inductor high step-up gain converters reduce the ripple of the input current and improve the efficiency. In a distributed generation system, Voltage Mode Control (VMC) is normally applied for regulating output voltage. Designing VMC with a feedback controller requires a small signal model of multi-phase ICIBC. This higher-order converter encountered significant challenges while modelling. This paper derives a mathematical model of multi-phase ICIBC using state space averaging method. It also presents step by step PI controller design using the root locus technique for voltage loop control. Simulation study of voltage loop control of two-phase ICIBC under variable load condition is analysed to attain regulated output voltage in PSIM.
Perception and Steering Control in Paired Bat Flight

Animals within groups need to coordinate their reactions to perceived environmental features and to each other in order to safely move from one point to another. This paper extends our previously published work on the flight patterns of Myotis velifer that have been observed in a habitat near Johnson City, Texas. Each evening, these bats emerge from a cave in sequences of small groups that typically contain no more than three or four individuals, and they thus provide ideal subjects for studying leader-follower behaviors. By analyzing the flight paths of a group of M. velifer, the data show that the flight behavior of a follower bat is influenced by the flight behavior of a leader bat in a way that is not well explained by existing pursuit laws, such as classical pursuit, constant bearing and motion camouflage. Thus we propose an alternative steering law based on virtual loom, a concept we introduce to capture the geometrical configuration of the leader-follower pair. It is shown that this law may be integrated with our previously proposed vision-enabled steering laws to synthesize trajectories, the statistics of which fit with those of the bats in our data set. The results suggest that bats use perceived information of both the environment and their neighbors for navigation.
A new control strategy for single phase cascaded H bridge multilevel inverter in stationary reference frame with nonlinear loads

This paper proposes a modified multiloop control strategy in stationary reference frame for the control of single phase multilevel converter in standalone mode. A new feedback method is proposed for the current control loop. The weighted sum of the filter inductor current and capacitor current is taken as the feedback to the inner current controller. Using this current measurement, a voltage control strategy using multiresonant voltage controllers is used to compensate for nonlinear loads. A cascaded H bridge multilevel converter is used for interfacing energy sources to load. Simulation and experimental results from a laboratory scale prototype is demonstrated to assess the performance of the suggested control scheme.
Using proximity and quantized RSS for sensor localization in wireless networks

For wireless sensor networks, received signal strength (RSS) and proximity (also known as connectivity) measurements have been proposed as simple and inexpensive means to estimate range between devices and sensor location. While RSS measurements are recognized to suffer from errors due to the random nature of the fading channel, proximity measurements, ie. , knowing only whether or not two devices are in communication range, are often discussed without considering that they are affected by the same fading channel. Proximity measurements are actually just a binary quantization of RSS measurements. We use the Cramér-Rao bound (CRB) to compare the minimal attainable variances of unbiased sensor location estimators for the cases of RSS and proximity measurements. For completeness, we also present the CRB for sensor localization with systems using K-level quantized RSS (QRSS) measurements, of which proximity measurements are the special case: K=2. Examples are presented for the case of one unknown-location sensor, and for the case of a 5 by 5 grid of sensors. These examples show that lower bounds for standard deviation in proximity-based systems are, as a rule of thumb, about 50% higher than the bounds for RSS-based systems. Furthermore, results are presented which show how many bits of quantization are necessary for a QRSS-based system to nearly achieve the bounds of an unquantized RSS system.
Associative Learning and CA3–CA1 Synaptic Plasticity Are Impaired in D1R Null, Drd1a−/− Mice and in Hippocampal siRNA Silenced Drd1a Mice

Associative learning depends on multiple cortical and subcortical structures, including striatum, hippocampus, and amygdala. Both glutamatergic and dopaminergic neurotransmitter systems have been implicated in learning and memory consolidation. While the role of glutamate is well established, the role of dopamine and its receptors in these processes is less clear. In this study, we used two models of dopamine D1 receptor (D1R, Drd1a) loss, D1R knock-out mice (Drd1a−/−) and mice with intrahippocampal injections of Drd1a-siRNA (small interfering RNA), to study the role of D1R in different models of learning, hippocampal long-term potentiation (LTP) and associated gene expression. D1R loss markedly reduced spatial learning, fear learning, and classical conditioning of the eyelid response, as well as the associated activity-dependent synaptic plasticity in the hippocampal CA1–CA3 synapse. These results provide the first experimental demonstration that D1R is required for trace eyeblink conditioning and associated changes in synaptic strength in hippocampus of behaving mice. Drd1a-siRNA mice were indistinguishable from Drd1a−/− mice in all experiments, indicating that hippocampal knockdown was as effective as global inactivation and that the observed effects are caused by loss of D1R and not by indirect developmental effects of Drd1a−/−. Finally, in vivo LTP and LTP-induced expression of Egr1 in the hippocampus were significantly reduced in Drd1a−/− and Drd1a-siRNA, indicating an important role for D1R in these processes. Our data reveal a functional relationship between acquisition of associative learning, increase in synaptic strength at the CA3–CA1 synapse, and Egr1 induction in the hippocampus by demonstrating that all three are dramatically impaired when D1R is eliminated or reduced.
Design of Piezoelectric Energy Harvester Using Intelligent Optimization Techniques

The design and optimization process for enhancement in the performance of MEMS Unimorph Piezoelectric energy harvester based on Genetic Algorithm (GA) and Grey Wolf optimization (GWO) is studied. The analytical equations of Unimorph Piezoelectric Energy harvester have been derived, to determine the amount of voltage and power harvested from the piezoelectric cantilever. These analytical equations are used as the fitness function of GA and GWO. Both of the algorithms are a design optimization technique for optimization problems to enhance power and output voltage, harvested from the unimorph piezoelectric energy harvester. This is achieved by using GA and GWO, to optimize the parameters of the piezoelectric cantilever, in which the fitness function, is taken as the power and voltage derived by analytical equations, and the techniques are compared with each other. Furthermore, the effects of mechanical and electrical properties (natural frequency, stress, load impedance and harvester efficiency) are analyzed. Finally, with the results obtained, un-optimized results are compared with the optimized results (GA and GWO) and the optimized results are proved to be efficient in all aspects, which have significantly improved the efficiency of the piezoelectric energy harvester from 24.9% to 58.9%. Finally, a comparison is made within the optimization techniques and GWO has proved to be more efficient than GA and this performance of MEMS piezoelectric energy harvester is simulated using the MATLAB software.
Judgment aggregation with consistency alone

All existing impossibility theorems on judgment aggregation require individual and collective judgment sets to be consistent and complete (in some recent results with completeness relaxed to deductive closure), arguably a demanding rationality requirement. They do not carry over to aggregation functions mapping profiles of (merely) consistent individual judgment sets to (merely) consistent collective ones. We prove that, whenever the agenda of propositions under consideration exhibits mild interconnections, any such aggregation function that is "neutral" between the acceptance and rejection of each proposition is dictatorial. We relate this theorem to the literature.
Design of Backstepping Controller for a Three-phase Shunt Active Filter Interfacing Solar Photovoltaic System to Distribution Grid

This paper presents a controller for a three-phase four-leg shunt active power filter (SAPF), interfacing solar photovoltaic system to distribution grid. The controller consists of a non-linear, robust dc-link voltage control loop based on backstepping algorithm. It also consists of a current harmonic mitigation loop based on dual self tuning filter instantaneous power theory (DSTF-pq theory). The limitations of conventional pq theory based current harmonic mitigation controller are addressed in this paper by employing self tuning filters (STF) to extract the fundamental components of load currents and grid voltages. The effectiveness of the algorithm under steady state and dynamic conditions are comprehensively studied and evaluated in MATLAB/Simulink. The proposed controller is implemented in XC7a35t-cpg236-1 FPGA. The performance of the controller is tested and verified on a laboratory prototype of shunt active power filter.
Riemann-Liouville Operator Based FNLMS Algorithm for 3 Phase- 4 Wire SyRG-PV-BES Based Microgrid

This paper deals with one three phase voltage source converter (VSC) integrated with renewable energy sources (RESs) such as photovoltaic (PV) array and pico-hydro turbine driven by synchronous reluctance generator (SyRG). The proposed VSC controller is a Riemann-Liouvilla operator centered fractional normalised least mean square (FNLMS) algorithm, which accomplishes improved convergence, flexibility in parameter tuning and steady state performance. The VSC control algorithm in addition, provides harmonics compensation by inserting harmonics current in reverse direction into the system and neutral current compensation to maintain balance in supply. Moreover, in three-phase four wire based microgrid, a bidirectional converter (BDC) is used to harness power from the sources by controlling charging and discharging of the battery. However, the SyRG is used for pico-hydro generation because of its reliability, and cost-effectiveness. The proposed microgrid is implemented in real time using modular DSP (d-SPACE 1006) control. Test results of proposed microgrid, show that the voltage and frequency of microgrid is maintained constant while the system is following a sudden change in loads and under intermittent penetration of solar energy source.
Low Source Current Ripple Buck-Boost Converter

The paper proposes a low source current ripple buck-boost converter which is feasible in point of load applications. This converter topology has reduced source current ripple which eliminates the need of filter damping network at the source side and reduces the EMI as well. The proposed converter’s performance is examined in time-domain together with steady-state analysis. The buck and boost feature of the converter are explained along with design equations of L, C elements. State-space analysis is done to yield transfer functions which are the basis for controller design. A 15/36 V, 36 Watt prototype point of load converter is built to supply power at constant load voltage. A DC source of $24\,{V}$ is used while a switching frequency of 100 kHz is adopted for the prototype converter operation both in simulation and experimentation. The results obtained from simulation and experiments are in line with the analytical predictions.
A Zero-voltage Zero-current Transition Network for Dual Phase Interleaved Converter

In this paper, a zero-voltage zero-current transition network is proposed for a dual phase interleaved converter. The proposed soft-switching network consists of an auxiliary transformer, an auxiliary switch, and a clamp diode. The enhanced gain of the converter over conventional interleaved boost converter is realized by utilizing a diode capacitor multiplier cell. The auxiliary transformer closely couples the current in the switch branches to achieve effective zero-current turn-OFF of the outgoing switch in addition to zero-voltage turn-ON of the incoming switch. Furthermore, zero-current turn OFF of all the diodes (main and auxiliary) is also achieved. Additionally, the proposed network facilitates zero current turn-ON of the auxiliary switch. A 60 to 270 V, 140 W prototype operating at 50 kHz is constructed and soft-transitions of the devices is demonstrated through experiments.