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检索条件"机构=Instrumentation and Control Engineering Netaji Subhas University of Technology"

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Comparative Study of Conventional PD and Fuzzy PD controllers for a Non-linear Active Suspension System

Comparative Study of Conventional PD and Fuzzy PD Controller...

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International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Sukhsagar Misra Vineet Kumar K. P.S. Rana Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

This paper presents a comparative study of conventional PD and Fuzzy PD (FPD) controllers for a nonlinear active suspension system for quarter car. The control purpose is to upgrade ride quality of quarter car by reducing the root mean square of vertical acceleration (RMSVA) while keeping all hard constraints like suspension movement, dynamic and static load on tyre and actuator saturation within limits. The gains of PD and FPD controllers are tuned by Genetic Algorithms (GA) optimization technique for random road profiles by minimizing a cost function consist of integral of time-weighted absolute error and RMSVA and a comparative study is carried out. Further, controllers tuned with random road surface are tested on bump road profile for various amplitude. It has been noted that FPD controller out performed conventional PD controller and provided superior ride comfort.

关键词： Roads PD control Automobiles Tires Force Acceleration Cost function

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Comparative Study of Optimization Techniques for Tuning of PI Gains for Greenhouse Climate control

Comparative Study of Optimization Techniques for Tuning of P...

引用

International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Amit Sangwan Abhinav Gupta Divya Tiwari Vineet Kumar K. P. S. Rana Department of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

ISBN: (纸本)9781728100173

Greenhouses are highly nonlinear, non-isolated systems which are very difficult to model and control. For desired plant growth, such greenhouses demand a very specific form of climatic conditions which can vary due to the impact of highly stochastic disturbances in the form of solar radiation, temperature and humidity of outside environment. Greenhouse climate control designs are often put into use to increase the quality of growth of the plants cultured inside the greenhouse while keeping a check on the production costs. Such designs need to be efficient at setpoint tracking while providing good disturbance rejection. In this paper a greenhouse's climate is controlled with conventional PI controller. The controller is tuned with different global optimization algorithms, namely Genetic Algorithm (GA), Cuckoo Search Algorithm (CSA) and Grey Wolf Optimization (GWO) Algorithm. The tuning has been performed through minimization of a weighted sum of integral of the absolute error. Simulation study clearly reveals that the GWO tuned PI controller offers much better results.

关键词： Green products Optimization Mathematical model PI control Humidity Genetic algorithms

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Hyper Smoothing Function based Edge Detection for Prediction of Fat Content in Marble Meat

Hyper Smoothing Function based Edge Detection for Prediction...

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International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Navdeep Navdeep Vijander Singh Asha Rani Sonal Goyal Department of Instrumentation and Control Engineering Netaji Subhas Institute of Technology Delhi University Delhi India

Intramuscular fat is one of the crucial quality indices in meat grading. The traditional intramuscular fat detection methods like chemical, visual, nuclear magnetic resonance etc. are tedious, costly and time-consuming whereas edge detection techniques are fast and non-destructive testing methods. In this paper hyper smoothing function-based edge detection technique is proposed for intramuscular fat detection. The proposed method utilizes an improved counting scheme and the relationship between surrounding pixels and centric pixel. The scheme calculates fat percentage, fat fleck size distribution and homogeneity. The quantitative analysis of results shows that the fat percentage measured by HLBP is more accurate as compared to black and white method and energy and skewness based fat detection method.

关键词： Fats Image edge detection Chemicals Smoothing methods Muscles Visualization

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Effect of Higher Order DC-DC Converter on Solar fed BLDC Motor Driven Water Pumping System

Effect of Higher Order DC-DC Converter on Solar fed BLDC Mot...

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Students Conference on engineering and Systems (SCES)

作者： Mohd Juned Manisha Prerna Gaur Instrumentation and Control Engineering Netaji Subhas Institute of Technology (NSIT) New Delhi INDIA Instrumentaion and Control Engineering Netaji Subhas University of Technology (formerly NSIT) New Delhi INDIA

ISBN: (纸本)9781728105789

Standalone BLDC motor system for applications such as household water pumping, irrigation, electric vehicle etc has been commercialized. In this system, closed loop power electronic converters control the speed of BLDC motor and track maximum power drawn from solar panel. Zeta converter with inductor on the load side is used to track maximum power. This paper presents design of power electronic converters for driving BLDC motor using solar PV source. Design of converters is done according to the ratings of BLDC motor and required solar PV array. The performance of Zeta converter is shown through simulated results of 2. S9kW, 3000 rpm BLDC motor. The effect of higher order converter is shown in terms of comparison with second order buck boost converter.

关键词： brushless DC motors DC motor drives maximum power point trackers photovoltaic power systems pumps solar cell arrays brushless direct current motor maximum power point trackers Solar cell arrays DC motor drives photovoltaic power systems Converters Pumps load side Maximum power

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EEG Signal based Seizure Classification Using Wavelet Transform

EEG Signal based Seizure Classification Using Wavelet Transf...

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International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Mayank Kumar Jareda Rajneesh Sharma Amit Kukker Instrumentation and Control Division Netaji Subhas University of Technology New Delhi India

Seizure is an uncontrolled neurological disturbance in brain. Electroencephalogram (EEG) which records the electrical activities of the brain can be used to identify an epileptic seizure. EEG signals are non-stationary and non-linear in nature which makes their analysis difficult. In this paper, an EEG based method for seizure classification based on brain activities is presented. Wavelet transform has been used to decompose EEG signal. Features are extracted from the decomposition coefficients of Wavelet. Further, feature input vector and target vector are created for classification and prediction of seizure. Support Vector Machines (SVM) and K-Nearest Neighbor (KNN) classifiers have been used for seizure prediction and classification. In the proposed method, we have gained 89.60% accuracy with cubic SVM and 87.00% accuracy with weighted KNN.

关键词： Electroencephalography Support vector machines Feature extraction Wavelet transforms Epilepsy

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Wavelet Transform Based Pneumonia Classification of Chest X- Ray Images

Wavelet Transform Based Pneumonia Classification of Chest X-...

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International Conference on Computing, Power and Communication Technologies (GUCON)

作者： Nitin Singh Rajneesh Sharma Amit Kukker Instrumentation and Control Division Netaji Subhas University of Technology New Delhi India

ISBN: (纸本)9781728100173

Pneumonia is a contagious disease that inflames the sac of air in either of our lungs. It occurs mainly due to microbial infection. In proposed work, we have used normal and abnormal (infected with pneumonia) data set of chest x-ray for detection of pneumonia. With Wavelet Transform method and Gray level Co- Occurrence Matrix (GLCM) , total 6 time-frequency domain features are extracted for approximately 3000 X-Ray images of data set of normal and infected *** is mainly used for extracting texture features like contrast, energy, correlation & homogeneity. Then we form feature matrix and train our classifier. Support Vector Machine (SVM) and K-nearest neighbors (KNN) scheme is adopted to detect the pneumonia. There are various type of SVM and KNN based on Kernel. From these, SVM and KNN, we achieved accuracy 94.6% with cubic SVM and 92.6% with weighted KNN. The results of using the Wavelet Transform based SVM classification are quite promising when compared to another classification techniques as K-NN classification.

关键词： Lung Diseases Support vector machines Feature extraction Wavelet transforms X-ray imaging

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AlexaPi3-An economical Smart Speaker 1

AlexaPi3-An economical Smart Speaker

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1st International Conference on Data Science and Analytics, PuneCon 2018

作者： Kumar, Archiev Instrumentation and Control Engineering Netaji Subhas Institute of Technology New Delhi India

ISBN: (纸本)9781538672785

In the recent years, smart electronics have seen a rapid rise in the field of home automation and wireless digital technology. But the high costs of these devices restrict many people to use the features of these technologies. In this paper, I present an economical solution for a smart speaker such as Amazon Echo Dot. The Alexa AWS is used and incorporated with Raspberry Pi 3 with a Bluetooth speaker (Logitech X100). Anyone with an internet connection can make their own Amazon Echo Dot with any speaker. This is significantly cheaper than buying the commercially available products. Moreover, this device can be interfaced with almost any electrical equipment to make a voice controlled home automation system. This paper helps readers to explore the Internet of Things without spending much money. © 2018 IEEE.

关键词： Bluetooth

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Pitch angle control of variable speed wind turbine by using fuzzy logic 2

Pitch angle control of variable speed wind turbine by using ...

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2nd IEEE International Conference on Power Electronics, Intelligent control and Energy Systems, ICPEICES 2018

作者： Kumar, Akshiv Kumar, Bhavnesh Netaji Subhas Institute of Technology Division of Instrumentation Control Engineering New Delhi India

ISBN: (纸本)9781538666258

Wind energy conversion systems have to handle the variations in the wind speed for efficient energy conversion. This paper presents an analysis made on the controller effectiveness system for pitch angle control of a wind turbine which changes performance of the wind energy conversion system. A fuzzy logic controller is proposed in place of classical PI controller for controlling the pitch angle to have maximum available power from the wind energy conversion system and the comparisons are made between PI controller, fractional order PI controller and fuzzy logic controller. The system is tested for different realistic environmental conditions using MATLAB/Simulink Software. © 2018 IEEE.

关键词： Fuzzy logic

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Application of Newton iterative process in approximation of fractional differentiator and integrator

Application of Newton iterative process in approximation of ...

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International Conference on Intelligent Computing, instrumentation and control Technologies (ICICICT)

作者： Nitisha Shrivastava Pragya Varshney Inderprastha Engineering College NCR-Delhi Ghaziabad India Division of Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India

The band specific realization of fractional order controllers and filters find its way into implementation through the approximated value as its realization in the original form is very difficult. The integer-order passive structure of the fractional operator is built based upon its approximated integer-order transfer function. Therefore, approximation is an essential part of fractional order elements which are ideally characterized by constant phase and constant slope in the entire frequency range. The realizable approximated solutions are obtained by either finding alternate placement of real poles and zeros on the left half of s-plane, so that the slope of the approximated transfer function remains constant or by performing iterations and using continued fraction expansion. In this paper the authors have studied two techniques of approximation viz. Carlson and NPC techniques, both of which are based on Newton iterations. All the mathematical steps involved in each of the method to obtain the solution is presented in detail. A comparison of the two methods is also presented. Two fractional operators, one-fourth differentiator and nine-tenth integrator are chosen for simulation purpose. The results obtained in terms of frequency response are compared with the ideal response using MATLAB.

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Predictive Maintenance of Air Conditioning Systems Using Supervised Machine Learning

Predictive Maintenance of Air Conditioning Systems Using Sup...

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International Conference on Intelligent Systems Applications to Power Systems (ISAP)

作者： Shrishti Trivedi Sahil Bhola Archit Talegaonkar Prerna Gaur Shreya Sharma Instrumentation and Control Engineering Netaji Subhas University of Technology New Delhi India Computer Science Engineering Indraprastha Institute of Information Technology New Delhi India

ISBN: (数字)9781728131924

ISBN: (纸本)9781728131931

Various types of faults can occur in an air conditioner resulting in a decrease in efficiency, a rise in energy consumption, and increasing maintenance costs. Hence predictive maintenance becomes important. In this paper, the two most common types of faults - gas leakage and capacitor malfunction have been detected using the decision tree machine learning algorithm. The data for faulty and operating air conditioners have been collected using distributed sensors, microcontroller, and dedicated circuitry and analyzed using MATLAB Classification App Learner Toolbox. The results obtained by the decision tree for fault detection and diagnosis and load monitoring were then compared with results obtained by support vector machine and the prediction accuracy for the decision tree was found to be higher. The presented research work can identify the air conditioner which is faulty as well as predicts the type of fault at an early stage to do maintenance beforehand.

关键词： Circuit faults Decision trees Machine learning algorithms Intelligent sensors Air conditioning Fault detection

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