Search results for: IMC-PID tuning method
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 18669

Search results for: IMC-PID tuning method

18639 Power System Stability Enhancement Using Self Tuning Fuzzy PI Controller for TCSC

Authors: Salman Hameed

Abstract:

In this paper, a self-tuning fuzzy PI controller (STFPIC) is proposed for thyristor controlled series capacitor (TCSC) to improve power system dynamic performance. In a STFPIC controller, the output scaling factor is adjusted on-line by an updating factor (α). The value of α is determined from a fuzzy rule-base defined on error (e) and change of error (Δe) of the controlled variable. The proposed self-tuning controller is designed using a very simple control rule-base and the most natural and unbiased membership functions (MFs) (symmetric triangles with equal base and 50% overlap with neighboring MFs). The comparative performances of the proposed STFPIC and the standard fuzzy PI controller (FPIC) have been investigated on a multi-machine power system (namely, 4 machine two area system) through detailed non-linear simulation studies using MATLAB/SIMULINK. From the simulation studies it has been found out that for damping oscillations, the performance of the proposed STFPIC is better than that obtained by the standard FPIC. Moreover, the proposed STFPIC as well as the FPIC have been found to be quite effective in damping oscillations over a wide range of operating conditions and are quite effective in enhancing the power carrying capability of the power system significantly.

Keywords: genetic algorithm, power system stability, self-tuning fuzzy controller, thyristor controlled series capacitor

Procedia PDF Downloads 394
18638 Self-Tuning Dead-Beat PD Controller for Pitch Angle Control of a Bench-Top Helicopter

Authors: H. Mansor, S.B. Mohd-Noor, N. I. Othman, N. Tazali, R. I. Boby

Abstract:

This paper presents an improved robust Proportional Derivative controller for a 3-Degree-of-Freedom (3-DOF) bench-top helicopter by using adaptive methodology. Bench-top helicopter is a laboratory scale helicopter used for experimental purposes which is widely used in teaching laboratory and research. Proportional Derivative controller has been developed for a 3-DOF bench-top helicopter by Quanser. Experiments showed that the transient response of designed PD controller has very large steady state error i.e., 50%, which is very serious. The objective of this research is to improve the performance of existing pitch angle control of PD controller on the bench-top helicopter by integration of PD controller with adaptive controller. Usually standard adaptive controller will produce zero steady state error; however response time to reach desired set point is large. Therefore, this paper proposed an adaptive with deadbeat algorithm to overcome the limitations. The output response that is fast, robust and updated online is expected. Performance comparisons have been performed between the proposed self-tuning deadbeat PD controller and standard PD controller. The efficiency of the self-tuning dead beat controller has been proven from the tests results in terms of faster settling time, zero steady state error and capability of the controller to be updated online.

Keywords: adaptive control, deadbeat control, bench-top helicopter, self-tuning control

Procedia PDF Downloads 299
18637 Performance Comparisons between PID and Adaptive PID Controllers for Travel Angle Control of a Bench-Top Helicopter

Authors: H. Mansor, S. B. Mohd-Noor, T. S. Gunawan, S. Khan, N. I. Othman, N. Tazali, R. B. Islam

Abstract:

This paper provides a comparative study on the performances of standard PID and adaptive PID controllers tested on travel angle of a 3-Degree-of-Freedom (3-DOF) Quanser bench-top helicopter. Quanser, a well-known manufacturer of educational bench-top helicopter has developed Proportional Integration Derivative (PID) controller with Linear Quadratic Regulator (LQR) for all travel, pitch and yaw angle of the bench-top helicopter. The performance of the PID controller is relatively good; however its performance could also be improved if the controller is combined with adaptive element. The objective of this research is to design adaptive PID controller and then compare the performances of the adaptive PID with the standard PID. The controller design and test is focused on travel angle control only. Adaptive method used in this project is self-tuning controller, which controller’s parameters are updated online. Two adaptive algorithms those are pole-placement and deadbeat have been chosen as the method to achieve optimal controller’s parameters. Performance comparisons have shown that the adaptive (deadbeat) PID controller has produced more desirable performance compared to standard PID and adaptive (pole-placement). The adaptive (deadbeat) PID controller attained very fast settling time (5 seconds) and very small percentage of overshoot (5% to 7.5%) for 10° to 30° step change of travel angle.

Keywords: adaptive control, deadbeat, pole-placement, bench-top helicopter, self-tuning control

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18636 Low-Surface Roughness and High Optical Quality CdS Thin Film Grown by Modified Chemical Surface Deposition Method

Authors: A. Elsayed, M. H. Dewaidar, M. Ghali

Abstract:

We report on deposition of smooth, pinhole-free, low-surface roughness ( < 4nm) and high optical quality cadmium sulfide (CdS) thin films on glass substrates using our new method based on chemical surface deposition principle. In this method, cadmium acetate and thiourea are used as reactants under special growth conditions for deposition of CdS films. X-ray diffraction (XRD) measurements were used to examine the crystal structure properties of the deposited CdS films. In addition, UV-vis transmittance and low-temperature (4K) photoluminescence (PL) measurements were performed for quantifying optical properties of the deposited films. Interestingly, we found that XRD pattern of the deposited films has dramatically changed when the growth temperature was raised during the reaction. Namely, the XRD measurements reveal a structural change of CdS film from Cubic to Hexagonal phase upon increase in the growth temperature from 75 °C to 200 °C. Furthermore, the deposited films show high optical quality as confirmed from observation of both sharp edge in the transmittance spectra and strong PL intensity at room temperature. Also, we found a strong effect of the growth conditions on the optical band gap of the deposited films; where remarkable red-shift in the absorption edge with temperature is clearly seen in both transmission and PL spectra. Such tuning of both optical band gap and crystal structure of the deposited CdS films; can be utilized for tuning the electronic bands alignments between CdS and other light harvesting materials, like CuInGaSe or CdTe, for potential improvement in the efficiency of all-solution processed solar cells devices based on these heterostructures.

Keywords: thin film, CdS, new method, optical properties

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18635 Experimental Study of Hyperparameter Tuning a Deep Learning Convolutional Recurrent Network for Text Classification

Authors: Bharatendra Rai

Abstract:

The sequence of words in text data has long-term dependencies and is known to suffer from vanishing gradient problems when developing deep learning models. Although recurrent networks such as long short-term memory networks help to overcome this problem, achieving high text classification performance is a challenging problem. Convolutional recurrent networks that combine the advantages of long short-term memory networks and convolutional neural networks can be useful for text classification performance improvements. However, arriving at suitable hyperparameter values for convolutional recurrent networks is still a challenging task where fitting a model requires significant computing resources. This paper illustrates the advantages of using convolutional recurrent networks for text classification with the help of statistically planned computer experiments for hyperparameter tuning.

Keywords: long short-term memory networks, convolutional recurrent networks, text classification, hyperparameter tuning, Tukey honest significant differences

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18634 A Clustering Algorithm for Massive Texts

Authors: Ming Liu, Chong Wu, Bingquan Liu, Lei Chen

Abstract:

Internet users have to face the massive amount of textual data every day. Organizing texts into categories can help users dig the useful information from large-scale text collection. Clustering, in fact, is one of the most promising tools for categorizing texts due to its unsupervised characteristic. Unfortunately, most of traditional clustering algorithms lose their high qualities on large-scale text collection. This situation mainly attributes to the high- dimensional vectors generated from texts. To effectively and efficiently cluster large-scale text collection, this paper proposes a vector reconstruction based clustering algorithm. Only the features that can represent the cluster are preserved in cluster’s representative vector. This algorithm alternately repeats two sub-processes until it converges. One process is partial tuning sub-process, where feature’s weight is fine-tuned by iterative process. To accelerate clustering velocity, an intersection based similarity measurement and its corresponding neuron adjustment function are proposed and implemented in this sub-process. The other process is overall tuning sub-process, where the features are reallocated among different clusters. In this sub-process, the features useless to represent the cluster are removed from cluster’s representative vector. Experimental results on the three text collections (including two small-scale and one large-scale text collections) demonstrate that our algorithm obtains high quality on both small-scale and large-scale text collections.

Keywords: vector reconstruction, large-scale text clustering, partial tuning sub-process, overall tuning sub-process

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18633 Miniaturized and Compact Monopole Corner Antenna with a Periodic Slot Truncated and T-Inverted Stub-Tuning for Ultra Wideband Applications

Authors: R. Dakir, J. Zbitou, Ahmed Mouhsen, A. Errkik, A. Tajmouati, M. Latrach

Abstract:

The design and analysis of a new compact and miniaturized monopole antenna structure for ultra wideband (UWB) wireless applications are presented and suggested in this paper. The proposed antenna structure is based on corner radiator patch with T-shaped slot and fed by mictostrip feed line with a partial ground plane combined a periodic rectangular slot and inverted T-stub tuning to increase the bandwidth. The design parameters and the performance of the suggested antenna are investigated by using 'CST Microwave Studio' and Advanced Design System. The final prototype of the proposed antenna operates from 3GHZ to 25GHz, corresponding to wide input impedance bandwidth around (157.14%) with a size of 16*24mm2 and can be easily integrated with radio-frequency or microwave circuits with low cost manufacturing. Details of the UWB antenna design and both simulated and measured results are described and discussed.

Keywords: UWB, T-shaped slots, improvement, bandwidth, stub tuning

Procedia PDF Downloads 274
18632 A CMOS Capacitor Array for ESPAR with Fast Switching Time

Authors: Jin-Sup Kim, Se-Hwan Choi, Jae-Young Lee

Abstract:

A 8-bit CMOS capacitor array is designed for using in electrically steerable passive array radiator (ESPAR). The proposed capacitor array shows the fast response time in rising and falling characteristics. Compared to other works in silicon-on-insulator (SOI) or silicon-on-sapphire (SOS) technologies, it shows a comparable tuning range and switching time with low power consumption. Using the 0.18um CMOS, the capacitor array features a tuning range of 1.5 to 12.9 pF at 2.4GHz. Including the 2X4 decoder for control interface, the Chip size is 350um X 145um. Current consumption is about 80 nA at 1.8 V operation.

Keywords: CMOS capacitor array, ESPAR, SOI, SOS, switching time

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18631 Weighted Rank Regression with Adaptive Penalty Function

Authors: Kang-Mo Jung

Abstract:

The use of regularization for statistical methods has become popular. The least absolute shrinkage and selection operator (LASSO) framework has become the standard tool for sparse regression. However, it is well known that the LASSO is sensitive to outliers or leverage points. We consider a new robust estimation which is composed of the weighted loss function of the pairwise difference of residuals and the adaptive penalty function regulating the tuning parameter for each variable. Rank regression is resistant to regression outliers, but not to leverage points. By adopting a weighted loss function, the proposed method is robust to leverage points of the predictor variable. Furthermore, the adaptive penalty function gives us good statistical properties in variable selection such as oracle property and consistency. We develop an efficient algorithm to compute the proposed estimator using basic functions in program R. We used an optimal tuning parameter based on the Bayesian information criterion (BIC). Numerical simulation shows that the proposed estimator is effective for analyzing real data set and contaminated data.

Keywords: adaptive penalty function, robust penalized regression, variable selection, weighted rank regression

Procedia PDF Downloads 434
18630 Localization of Mobile Robots with Omnidirectional Cameras

Authors: Tatsuya Kato, Masanobu Nagata, Hidetoshi Nakashima, Kazunori Matsuo

Abstract:

Localization of mobile robots are important tasks for developing autonomous mobile robots. This paper proposes a method to estimate positions of a mobile robot using an omnidirectional camera on the robot. Landmarks for points of references are set up on a field where the robot works. The omnidirectional camera which can obtain 360 [deg] around images takes photographs of these landmarks. The positions of the robots are estimated from directions of these landmarks that are extracted from the images by image processing. This method can obtain the robot positions without accumulative position errors. Accuracy of the estimated robot positions by the proposed method are evaluated through some experiments. The results show that it can obtain the positions with small standard deviations. Therefore the method has possibilities of more accurate localization by tuning of appropriate offset parameters.

Keywords: mobile robots, localization, omnidirectional camera, estimating positions

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18629 Reducing the Computational Overhead of Metaheuristics Parameterization with Exploratory Landscape Analysis

Authors: Iannick Gagnon, Alain April

Abstract:

The performance of a metaheuristic on a given problem class depends on the class itself and the choice of parameters. Parameter tuning is the most time-consuming phase of the optimization process after the main calculations and it often nullifies the speed advantage of metaheuristics over traditional optimization algorithms. Several off-the-shelf parameter tuning algorithms are available, but when the objective function is expensive to evaluate, these can be prohibitively expensive to use. This paper presents a surrogate-like method for finding adequate parameters using fitness landscape analysis on simple benchmark functions and real-world objective functions. The result is a simple compound similarity metric based on the empirical correlation coefficient and a measure of convexity. It is then used to find the best benchmark functions to serve as surrogates. The near-optimal parameter set is then found using fractional factorial design. The real-world problem of NACA airfoil lift coefficient maximization is used as a preliminary proof of concept. The overall aim of this research is to reduce the computational overhead of metaheuristics parameterization.

Keywords: metaheuristics, stochastic optimization, particle swarm optimization, exploratory landscape analysis

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18628 Practical Techniques of Improving State Estimator Solution

Authors: Kiamran Radjabli

Abstract:

State Estimator became an intrinsic part of Energy Management Systems (EMS). The SCADA measurements received from the field are processed by the State Estimator in order to accurately determine the actual operating state of the power systems and provide that information to other real-time network applications. All EMS vendors offer a State Estimator functionality in their baseline products. However, setting up and ensuring that State Estimator consistently produces a reliable solution often consumes a substantial engineering effort. This paper provides generic recommendations and describes a simple practical approach to efficient tuning of State Estimator, based on the working experience with major EMS software platforms and consulting projects in many electrical utilities of the USA.

Keywords: convergence, monitoring, state estimator, performance, troubleshooting, tuning, power systems

Procedia PDF Downloads 136
18627 Self Tuning Controller for Reducing Cycle to Cycle Variations in SI Engine

Authors: Alirıza Kaleli, M. Akif Ceviz, Erdoğan Güner, Köksal Erentürk

Abstract:

The cyclic variations in spark ignition engines occurring especially under specific engine operating conditions make the maximum pressure variable for successive in-cylinder pressure cycles. Minimization of cyclic variations has a great importance in effectively operating near to lean limit, or at low speed and load. The cyclic variations may reduce the power output of the engine, lead to operational instabilities, and result in undesirable engine vibrations and noise. In this study, spark timing is controlled in order to reduce the cyclic variations in spark ignition engines. Firstly, an ARMAX model has developed between spark timing and maximum pressure using system identification techniques. By using this model, the maximum pressure of the next cycle has been predicted. Then, self-tuning minimum variance controller has been designed to change the spark timing for consecutive cycles of the first cylinder of test engine to regulate the in-cylinder maximum pressure. The performance of the proposed controller is illustrated in real time and experimental results show that the controller has a reliable effect on cycle to cycle variations of maximum cylinder pressure when the engine works under low speed conditions.

Keywords: cyclic variations, cylinder pressure, SI engines, self tuning controller

Procedia PDF Downloads 457
18626 Speed Control of DC Motor Using Optimization Techniques Based PID Controller

Authors: Santosh Kumar Suman, Vinod Kumar Giri

Abstract:

The goal of this paper is to outline a speed controller of a DC motor by choice of a PID parameters utilizing genetic algorithms (GAs), the DC motor is extensively utilized as a part of numerous applications such as steel plants, electric trains, cranes and a great deal more. DC motor could be represented by a nonlinear model when nonlinearities such as attractive dissemination are considered. To provide effective control, nonlinearities and uncertainties in the model must be taken into account in the control design. The DC motor is considered as third order system. Objective of this paper three type of tuning techniques for PID parameter. In this paper, an independently energized DC motor utilizing MATLAB displaying, has been outlined whose velocity might be examined utilizing the Proportional, Integral, Derivative (KP, KI , KD) addition of the PID controller. Since, established controllers PID are neglecting to control the drive when weight parameters be likewise changed. The principle point of this paper is to dissect the execution of optimization techniques viz. The Genetic Algorithm (GA) for improve PID controllers parameters for velocity control of DC motor and list their points of interest over the traditional tuning strategies. The outcomes got from GA calculations were contrasted and that got from traditional technique. It was found that the optimization techniques beat customary tuning practices of ordinary PID controllers.

Keywords: DC motor, PID controller, optimization techniques, genetic algorithm (GA), objective function, IAE

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18625 Batteryless DCM Boost Converter for Kinetic Energy Harvesting Applications

Authors: Andrés Gomez-Casseres, Rubén Contreras

Abstract:

In this paper, a bidirectional boost converter operated in Discontinuous Conduction Mode (DCM) is presented as a suitable power conditioning circuit for tuning of kinetic energy harvesters without the need of a battery. A nonlinear control scheme, composed by two linear controllers, is used to control the average value of the input current, enabling the synthesization of complex loads. The converter, along with the control system, is validated through SPICE simulations using the LTspice tool. The converter model and the controller transfer functions are derived. From the simulation results, it was found that the input current distortion increases with the introduced phase shift and that, such distortion, is almost entirely present at the zero-crossing point of the input voltage.

Keywords: average current control, boost converter, electrical tuning, energy harvesting

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18624 Trajectory Tracking of a Redundant Hybrid Manipulator Using a Switching Control Method

Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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18623 Gaits Stability Analysis for a Pneumatic Quadruped Robot Using Reinforcement Learning

Authors: Soofiyan Atar, Adil Shaikh, Sahil Rajpurkar, Pragnesh Bhalala, Aniket Desai, Irfan Siddavatam

Abstract:

Deep reinforcement learning (deep RL) algorithms leverage the symbolic power of complex controllers by automating it by mapping sensory inputs to low-level actions. Deep RL eliminates the complex robot dynamics with minimal engineering. Deep RL provides high-risk involvement by directly implementing it in real-world scenarios and also high sensitivity towards hyperparameters. Tuning of hyperparameters on a pneumatic quadruped robot becomes very expensive through trial-and-error learning. This paper presents an automated learning control for a pneumatic quadruped robot using sample efficient deep Q learning, enabling minimal tuning and very few trials to learn the neural network. Long training hours may degrade the pneumatic cylinder due to jerk actions originated through stochastic weights. We applied this method to the pneumatic quadruped robot, which resulted in a hopping gait. In our process, we eliminated the use of a simulator and acquired a stable gait. This approach evolves so that the resultant gait matures more sturdy towards any stochastic changes in the environment. We further show that our algorithm performed very well as compared to programmed gait using robot dynamics.

Keywords: model-based reinforcement learning, gait stability, supervised learning, pneumatic quadruped

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18622 Tuning of Kalman Filter Using Genetic Algorithm

Authors: Hesham Abdin, Mohamed Zakaria, Talaat Abd-Elmonaem, Alaa El-Din Sayed Hafez

Abstract:

Kalman filter algorithm is an estimator known as the workhorse of estimation. It has an important application in missile guidance, especially in lack of accurate data of the target due to noise or uncertainty. In this paper, a Kalman filter is used as a tracking filter in a simulated target-interceptor scenario with noise. It estimates the position, velocity, and acceleration of the target in the presence of noise. These estimations are needed for both proportional navigation and differential geometry guidance laws. A Kalman filter has a good performance at low noise, but a large noise causes considerable errors leads to performance degradation. Therefore, a new technique is required to overcome this defect using tuning factors to tune a Kalman filter to adapt increasing of noise. The values of the tuning factors are between 0.8 and 1.2, they have a specific value for the first half of range and a different value for the second half. they are multiplied by the estimated values. These factors have its optimum values and are altered with the change of the target heading. A genetic algorithm updates these selections to increase the maximum effective range which was previously reduced by noise. The results show that the selected factors have other benefits such as decreasing the minimum effective range that was increased earlier due to noise. In addition to, the selected factors decrease the miss distance for all ranges of this direction of the target, and expand the effective range which leads to increase probability of kill.

Keywords: proportional navigation, differential geometry, Kalman filter, genetic algorithm

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18621 Exploring the Impact of Input Sequence Lengths on Long Short-Term Memory-Based Streamflow Prediction in Flashy Catchments

Authors: Farzad Hosseini Hossein Abadi, Cristina Prieto Sierra, Cesar Álvarez Díaz

Abstract:

Predicting streamflow accurately in flashy catchments prone to floods is a major research and operational challenge in hydrological modeling. Recent advancements in deep learning, particularly Long Short-Term Memory (LSTM) networks, have shown to be promising in achieving accurate hydrological predictions at daily and hourly time scales. In this work, a multi-timescale LSTM (MTS-LSTM) network was applied to the context of regional hydrological predictions at an hourly time scale in flashy catchments. The case study includes 40 catchments allocated in the Basque Country, north of Spain. We explore the impact of hyperparameters on the performance of streamflow predictions given by regional deep learning models through systematic hyperparameter tuning - where optimal regional values for different catchments are identified. The results show that predictions are highly accurate, with Nash-Sutcliffe (NSE) and Kling-Gupta (KGE) metrics values as high as 0.98 and 0.97, respectively. A principal component analysis reveals that a hyperparameter related to the length of the input sequence contributes most significantly to the prediction performance. The findings suggest that input sequence lengths have a crucial impact on the model prediction performance. Moreover, employing catchment-scale analysis reveals distinct sequence lengths for individual basins, highlighting the necessity of customizing this hyperparameter based on each catchment’s characteristics. This aligns with well known “uniqueness of the place” paradigm. In prior research, tuning the length of the input sequence of LSTMs has received limited focus in the field of streamflow prediction. Initially it was set to 365 days to capture a full annual water cycle. Later, performing limited systematic hyper-tuning using grid search, revealed a modification to 270 days. However, despite the significance of this hyperparameter in hydrological predictions, usually studies have overlooked its tuning and fixed it to 365 days. This study, employing a simultaneous systematic hyperparameter tuning approach, emphasizes the critical role of input sequence length as an influential hyperparameter in configuring LSTMs for regional streamflow prediction. Proper tuning of this hyperparameter is essential for achieving accurate hourly predictions using deep learning models.

Keywords: LSTMs, streamflow, hyperparameters, hydrology

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18620 Bayesian Optimization for Reaction Parameter Tuning: An Exploratory Study of Parameter Optimization in Oxidative Desulfurization of Thiophene

Authors: Aman Sharma, Sonali Sengupta

Abstract:

The study explores the utility of Bayesian optimization in tuning the physical and chemical parameters of reactions in an offline experimental setup. A comparative analysis of the influence of the acquisition function on the optimization performance is also studied. For proxy first and second-order reactions, the results are indifferent to the acquisition function used, whereas, while studying the parameters for oxidative desulphurization of thiophene in an offline setup, upper confidence bound (UCB) provides faster convergence along with a marginal trade-off in the maximum conversion achieved. The work also demarcates the critical number of independent parameters and input observations required for both sequential and offline reaction setups to yield tangible results.

Keywords: acquisition function, Bayesian optimization, desulfurization, kinetics, thiophene

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18619 Performance Analysis of Shunt Active Power Filter for Various Reference Current Generation Techniques

Authors: Vishal V. Choudhari, Gaurao A. Dongre, S. P. Diwan

Abstract:

A number of reference current generation have been developed for analysis of shunt active power filter to mitigate the load compensation. Depending upon the type of load the technique has to be chosen. In this paper, six reference current generation techniques viz. instantaneous reactive power theory(IRP), Synchronous reference frame theory(SRF), Perfect harmonic cancellation(PHC), Unity power factor method(UPF), Self-tuning filter method(STF), Predictive filtering method(PFM) are compared for different operating conditions. The harmonics are introduced because of non-linear loads in the system. These harmonics are eliminated using above techniques. The results and performance of system simulated on MATLAB/Simulink platform. The system is experimentally implemented using DS1104 card of dSPACE system.

Keywords: SAPF, power quality, THD, IRP, SRF, dSPACE module DS1104

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18618 Voltage Controlled Ring Oscillator for RF Applications in 0.18 µm CMOS Technology

Authors: Mohammad Arif Sobhan Bhuiyan, Zainal Abidin Nordin, Mamun Bin Ibne Reaz

Abstract:

A compact and power efficient high performance Voltage Controlled Oscillator (VCO) is a must in analog and digital circuits especially in the communication system, but the best trade-off among the performance parameters is a challenge for researchers. In this paper, a design of a compact 3-stage differential voltage controlled ring oscillator (VCRO) with low phase noise, low power and higher tuning bandwidth is proposed in 0.18 µm CMOS technology. The VCRO is designed with symmetric load and positive feedback techniques to achieve higher gain and minimum delay. The proposed VCRO can operate at tuning range of 3.9-5.0 GHz at 1.6 V supply voltage. The circuit consumes only 1.0757 mW of power and produces -129 dbc/Hz. The total active area of the proposed VCRO is only 11.74 x 37.73 µm2. Such a VCO can be the best choice for compact and low-power RF applications.

Keywords: CMOS, VCO, VCRO, oscillator

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18617 Assessment Power and Oscillation Damping Using the POD Controller and Proposed FOD Controller

Authors: Tohid Rahimi, Yahya Naderi, Babak Yousefi, Seyed Hossein Hoseini

Abstract:

Today’s modern interconnected power system is highly complex in nature. In this, one of the most important requirements during the operation of the electric power system is the reliability and security. Power and frequency oscillation damping mechanism improve the reliability. Because of power system stabilizer (PSS) low speed response against of major fault such as three phase short circuit, FACTs devise that can control the network condition in very fast time, are becoming popular. However, FACTs capability can be seen in a major fault present when nonlinear models of FACTs devise and power system equipment are applied. To realize this aim, the model of multi-machine power system with FACTs controller is developed in MATLAB/SIMULINK using Sim Power System (SPS) blockiest. Among the FACTs device, Static synchronous series compensator (SSSC) due to high speed changes its reactance characteristic inductive to capacitive, is effective power flow controller. Tuning process of controller parameter can be performed using different method. However, Genetic Algorithm (GA) ability tends to use it in controller parameter tuning process. In this paper, firstly POD controller is used to power oscillation damping. But in this station, frequency oscillation dos not has proper damping situation. Therefore, FOD controller that is tuned using GA is using that cause to damp out frequency oscillation properly and power oscillation damping has suitable situation.

Keywords: power oscillation damping (POD), frequency oscillation damping (FOD), Static synchronous series compensator (SSSC), Genetic Algorithm (GA)

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18616 Optimal Feedback Linearization Control of PEM Fuel Cell

Authors: E. Shahsavari, R. Ghasemi, A. Akramizadeh

Abstract:

This paper presents a new method to design nonlinear feedback linearization controller for polymer electrolyte membrane fuel cells (PEMFCs). A nonlinear controller is designed based on nonlinear model to prolong the stack life of PEM fuel cells. Since it is known that large deviations between hydrogen and oxygen partial pressures can cause severe membrane damage in the fuel cell, feedback linearization is applied to the PEM fuel cell system so that the deviation can be kept as small as possible during disturbances or load variations. To obtain an accurate feedback linearization controller, tuning the linear parameters are always important. So in proposed study NSGA_II method was used to tune the designed controller in aim to decrease the controller tracking error. The simulation result showed that the proposed method tuned the controller efficiently.

Keywords: nonlinear dynamic model, polymer electrolyte membrane fuel cells, feedback linearization, optimal control, NSGA_II

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18615 Reflection Phase Tuning of Graphene Plasmons by Substrate Design

Authors: Xiaojie Jiang, Wei Cai, Yinxiao Xiang, Ni Zhang, Mengxin Ren, Xinzheng Zhang, Jingjun Xu

Abstract:

Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Reflection phase of graphene plasmons (GPs) at an abrupt interface is very important, which determines the plasmon resonance of graphene structures of deep sub-wavelength scales. However, at an abrupt graphene edge, the reflection phase is always a constant, ΦR ≈ π/4. In this work, we show that the reflection phase of GPs can be efficiently changed through substrate design. Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides another way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.Specifically, the reflection phase is no longer π/4 at the interface formed by placing a graphene sheet on different substrates. Moreover, tailorable reflection phase of GPs up to 2π variation can be further achieved by scattering GPs at a junction consisting of two such dielectric interfaces with various gap width acting as a Fabry-Perot cavity. Besides, the evolution of plasmon mode in graphene ribbons based on the interface reflection phase tuning is predicted, which is expected to be observed in near-field experiments with scattering-type scanning near-field optical microscopy (s-SNOM). Our work provides a new way for in-plane plasmon control, which should find applications for integrated plasmon devices design using graphene.

Keywords: graphene plasmons, reflection phase tuning, plasmon mode tuning, Fabry-Perot cavity

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18614 A Robust PID Load Frequency Controller of Interconnected Power System Using SDO Software

Authors: Pasala Gopi, P. Linga Reddy

Abstract:

The response of the load frequency control problem in an multi-area interconnected electrical power system is much more complex with increasing size, changing structure and increasing load. This paper deals with Load Frequency Control of three area interconnected Power system incorporating Reheat, Non-reheat and Reheat turbines in all areas respectively. The response of the load frequency control problem in an multi-area interconnected power system is improved by designing PID controller using different tuning techniques and proved that the PID controller which was designed by Simulink Design Optimization (SDO) Software gives the superior performance than other controllers for step perturbations. Finally the robustness of controller was checked against system parameter variations

Keywords: load frequency control, pid controller tuning, step load perturbations, inter connected power system

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18613 Detection of COVID-19 Cases From X-Ray Images Using Capsule-Based Network

Authors: Donya Ashtiani Haghighi, Amirali Baniasadi

Abstract:

Coronavirus (COVID-19) disease has spread abruptly all over the world since the end of 2019. Computed tomography (CT) scans and X-ray images are used to detect this disease. Different Deep Neural Network (DNN)-based diagnosis solutions have been developed, mainly based on Convolutional Neural Networks (CNNs), to accelerate the identification of COVID-19 cases. However, CNNs lose important information in intermediate layers and require large datasets. In this paper, Capsule Network (CapsNet) is used. Capsule Network performs better than CNNs for small datasets. Accuracy of 0.9885, f1-score of 0.9883, precision of 0.9859, recall of 0.9908, and Area Under the Curve (AUC) of 0.9948 are achieved on the Capsule-based framework with hyperparameter tuning. Moreover, different dropout rates are investigated to decrease overfitting. Accordingly, a dropout rate of 0.1 shows the best results. Finally, we remove one convolution layer and decrease the number of trainable parameters to 146,752, which is a promising result.

Keywords: capsule network, dropout, hyperparameter tuning, classification

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18612 V0 Physics at LHCb. RIVET Analysis Module for Z Boson Decay to Di-Electron

Authors: A. E. Dumitriu

Abstract:

The LHCb experiment is situated at one of the four points around CERN’s Large Hadron Collider, being a single-arm forward spectrometer covering 10 mrad to 300 (250) mrad in the bending (non-bending) plane, designed primarily to study particles containing b and c quarks. Each one of LHCb’s sub-detectors specializes in measuring a different characteristic of the particles produced by colliding protons, its significant detection characteristics including a high precision tracking system and 2 ring-imaging Cherenkov detectors for particle identification. The major two topics that I am currently concerned in are: the RIVET project (Robust Independent Validation of Experiment and Theory) which is an efficient and portable tool kit of C++ class library useful for validation and tuning of Monte Carlo (MC) event generator models by providing a large collection of standard experimental analyses useful for High Energy Physics MC generator development, validation, tuning and regression testing and V0 analysis for 2013 LHCb NoBias type data (trigger on bunch + bunch crossing) at √s=2.76 TeV.

Keywords: LHCb physics, RIVET plug-in, RIVET, CERN

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18611 Low-Surface Roughness and High Optical Quality CdS Thin Film Deposited on Heated Substrate Using Room-Temperature Chemical Solution

Authors: A. Elsayed, M. H. Dewaidar, M. Ghali, M. Elkemary

Abstract:

The high production cost of the conventional solar cells requires the search for economic methods suitable for solar energy conversion. Cadmium Sulfide (CdS) is one of the most important semiconductors used in photovoltaics, especially in large area solar cells; and can be prepared in a thin film form by a wide variety of deposition techniques. The preparation techniques include vacuum evaporation, sputtering and molecular beam epitaxy. Other techniques, based on chemical solutions, are also used for depositing CdS films with dramatically low-cost compared to other vacuum-based methods. Although this technique is widely used during the last decades, due to simplicity and low-deposition temperature (~100°C), there is still a strong need for more information on the growth process and its relation with the quality of the deposited films. Here, we report on deposition of high-quality CdS thin films; with low-surface roughness ( < 3.0 nm) and sharp optical absorption edge; on low-temperature glass substrates (70°C) using a new method based on the room-temperature chemical solution. In this method, a mixture solution of cadmium acetate and thiourea at room temperature was used under special growth conditions for deposition of CdS films. X-ray diffraction (XRD) measurements were used to examine the crystal structure properties of the deposited CdS films. In addition, UV-VIS transmittance and low-temperature (4K) photoluminescence (PL) measurements were performed for quantifying optical properties of the deposited films. The deposited films show high optical quality as confirmed by observation of both, sharp edge in the transmittance spectra and strong PL intensity at room temperature. Furthermore, we found a strong effect of the growth conditions on the optical band gap of the deposited films; where remarkable red-shift in the absorption edge with temperature is clearly seen in both transmission and PL spectra. Such tuning of both optical band gap of the deposited CdS films can be utilized for tuning the electronic bands' alignments between CdS and other light-harvesting materials, like CuInGaSe or CdTe, for potential improvement in the efficiency of solar cells devices based on these heterostructures.

Keywords: chemical deposition, CdS, optical properties, surface, thin film

Procedia PDF Downloads 133
18610 Effect of Downstream Pressure in Tuning the Flow Control Orifices of Pressure Fed Reaction Control System Thrusters

Authors: Prakash M.N, Mahesh G, Muhammed Rafi K.M, Shiju P. Nair

Abstract:

Introduction: In launch vehicle missions, Reaction Control thrusters are being used for the three-axis stabilization of the vehicle during the coasting phases. A pressure-fed propulsion system is used for the operation of these thrusters due to its less complexity. In liquid stages, these thrusters are designed to draw propellant from the same tank used for the main propulsion system. So in order to regulate the propellant flow rates of these thrusters, flow control orifices are used in feed lines. These orifices are calibrated separately as per the flow rate requirement of individual thrusters for the nominal operating conditions. In some missions, it was observed that the thrusters were operated at higher thrust than nominal. This point was addressed through a series of cold flow and hot tests carried out in-ground and this paper elaborates the details of the same. Discussion: In order to find out the exact reason for this phenomenon, two flight configuration thrusters were identified and hot tested in the ground with calibrated orifices and feed lines. During these tests, the chamber pressure, which is directly proportional to the thrust, is measured. In both cases, chamber pressures higher than the nominal by 0.32bar to 0.7bar were recorded. The increase in chamber pressure is due to an increase in the oxidizer flow rate of both the thrusters. Upon further investigation, it is observed that the calibration of the feed line is done with ambient pressure downstream. But in actual flight conditions, the orifices will be subjected to operate with 10 to 11bar pressure downstream. Due to this higher downstream pressure, the flow through the orifices increases and thereby, the thrusters operate with higher chamber pressure values. Conclusion: As part of further investigatory tests, two numbers of fresh thrusters were realized. Orifice tuning of these thrusters was carried out in three different ways. In the first trial, the orifice tuning was done by simulating 1bar pressure downstream. The second trial was done with the injector assembled downstream. In the third trial, the downstream pressure equal to the flight injection pressure was simulated downstream. Using these calibrated orifices, hot tests were carried out in simulated vacuum conditions. Chamber pressure and flow rate values were exactly matching with the prediction for the second and third trials. But for the first trial, the chamber pressure values obtained in the hot test were more than the prediction. This clearly shows that the flow is detached in the 1st trial and attached for the 2nd & 3rd trials. Hence, the error in tuning the flow control orifices is pinpointed as the reason for this higher chamber pressure observed in flight.

Keywords: reaction control thruster, propellent, orifice, chamber pressure

Procedia PDF Downloads 178