Matlab

Photovoltaic system is considered to be a renewable energy which is derived from solar energy. Solar energy is an abundant resource which is clean and green energy taken from nature. However, the amount of electric power generated by solar arrays varies according to the weather condition. This will bring inconsistency in generation of output power. This report proposes a maximum power point tracking (MPPT) of photovoltaic system based on adaptive neural fuzzy inference system (ANFIS) control with FPGA implementation. The performance of proposed method will be evaluated by using MATLAB/SIMULINK application. The proposed method is capable to maintain the consistency of power generated by solar panel under varies conditions.

Design of a robust controller for multi input-multi output (MIMO) nonlinear uncertain dynamical system can be a challenging work. This research paper focuses on the design and analysis of a high performance PID like fuzzy controller for flexible robot manipulator, in presence of uncertainties. In this research, fuzzy logic controller is a stable nonlinear controller, which selected to control of our nonlinear system. The proposed approach effectively combines of design methods from linear Proportional-Integral-Derivative (PID) controller and fuzzy logic theory to improve the performance, stability and robustness of the flexible robot manipulator. To solve system’s dynamic nonlinearity, the PID fuzzy logic controller is used as a PID like fuzzy logic controller. The PID like fuzzy logic controller is updated based on gain updating factor. In this methodology, fuzzy logic controller is used to estimate the dynamic uncertainties. In this methodology, PID like fuzzy logic controller is evaluated. PID like fuzzy logic controller has three inputs, Proportional (P), Derivative (D), and Integrator (I), if each inputs have 𝑁 linguistic variables to defined the dynamic behavior, it has 𝑁×𝑁×𝑁 linguistic variables. To solve this challenge, parallel structure of a PD-like fuzzy controller and PI-like fuzzy controller is evaluated. In the next step, the challenge of design PI and PD fuzzy rule tables are supposed to be solved. To solve this challenge PID like fuzzy controller is replaced by PD-like fuzzy controller with the integral term in output. This method is caused to design only PD type rule table for PD like fuzzy controller and PI like fuzzy controller.

We implemented the object-based method using marked point processes to generate a natural fracture network honoring an assumed fracture characteristics’ distribution where the fractures are two-dimensional zero-thickness circular disks. Fractures are divided into two groups based on their alignment which is acquired by Monte Carlo sampling from two Gaussian distributions with 90-degree shift in the mean value; this hypothesis is validated considering the frequently observed checker-board fracture patterns in the outcrops. The growth of the fractures in the second group or the secondary (daughter) fractures can be terminated by a criterion derived from the distribution of the fractures in the first group or the primary (parent) fractures. For data assimilation purposes, a smooth seismic distribution for fracture density is mimicked by simple krigging which inherently possesses a smoothing nature. Then, the generated seismic data is honored by revising the fracture distribution such that in areas with less fracture density we have fewer fractures. This work provides a novel, yet easy and fast workflow to stochastically model a natural fracture network following the attributes offered by seismic data and concludes an orthogonal or bidirectional fracture pattern. This pattern can be easily extended for multi-directional fracture patterns using the proposed framework.

Ce TP a pour objectif de prendre en main le logiciel MATLAB. Les notions traitées sont la manipulation de variables aléatoires et de vecteurs, l’utilisation de fonctions, la représentation graphique, la génération de nombres aléatoires, le calcul d’écart-type de la variance, le calcul de la variance et la corrélation et la génération des signaux aléatoires en utilisant des systèmes linéaires invariants dans le temps. En ce qui concerne la 2 ème  partie, on étudie les propriétés du filtrage adaptatif (filtre de Wiener) en utilisant l’algorithme LMS. 

Le  but  de  ce  travail  de  réaliser  une  simulation  sous  l’environnement  MATLAB/Simulink  du fonctionnement d’un moteur asynchrone (MAS), alimenté par un onduleur  triphasé commandé par modulation  de  largeur  d’impulsions  (MLI)  type  vectorielle  (Space  Vector  Modulation  SVM) performante qui permettra l'amélioration du rendement.

This paper deals with the methods employed for the detailed resource mapping of different high value crops in Caraga region, Philippines. The proposed methodology utilizes object-based image analysis and the use of optimal features from LiDAR data. Classification of the image-objects was done by developing rule sets in eCognition. LiDAR data was used to create a Normalized Digital Surface Model (nDSM) which is segmented using eCognition for feature extraction. Some classes of objects can’t be separated by simple thresholds from different features making it difficult to develop a rule set. To address this problem, the image-objects were subjected to a supervised learning algorithm. Among the machine learning algorithms, Support Vector Machine learning has recently received a lot of attention and the number of works utilizing this technique has increased exponentially. SVMs have gained popularity because of their ability to generalize well given a limited number of training samples. However, SVMs also suffer from parameter assignment issues that can significantly affect the classification results. More specifically, the regularization parameter C in linear SVM has to be optimized to increase the accuracy. After performing the segmentation in eCognition, the optimization procedure as well as the extraction of the equations of the hyper-planes was done in Matlab. The learned hyper-planes separating one class from another in the multi-dimensional feature space can be thought of as a super-feature which will then be used in developing the classifier rule set in eCognition. In this study, we report a classification accuracy of 95.3% using six features obtained from the segmented LiDAR nDSM namely; area, roundness, compactness, height, height standard deviation, and asymmetry. We also show the different feature-space plots that have driven us to using the six aforementioned features for the four different classes namely; Buildings, Coconut, Mango, and Other Tall Vegetation.

This paper presents an efficient architecture for various image filtering algorithms and tumor characterization using Xilinx System Generator (XSG). This architecture offers an alternative through a graphical user interface that combines MATLAB, Simulink and XSG and explores important aspects concerned to hardware implementation. Performance of this architecture implemented in SPARTAN-3E Starter kit (XC3S500E-FG320) exceeds those of similar or greater resources architectures. The proposed architecture reduces the resources available on target device by 50%.

A home energy management (HEM) system is mainly used to improve the performance of the smart grid with the help of demand response enabled application for residential customer preference. Various developing countries continuous power supply is one of the problems which prevent the growth rate. So different methods can be proposed to increase the power generation and reducing the power demand by increasing the energy efficiency .One of the innovative technique is demand shifting. This paper aims at
developing a demand shifting algorithm. The HEM system is developed in order to monitor the power consumption and time requirement for operation of various equipment & tries to shift the operation of certain non-essential and monitor the power consumption of individual equipment .It act as a modern home energy meter. The main aim of the system is reduce the peak power demand and tries to keep the load curve smooth without effecting customers comfort level. The HEM is developed using MATLAB and various scenarios are inputted into it and its output and its impact on the consumer is analyzed.

El control de los dispositivos funciona de forma local, teniendo los tres componentes (sensor, controlador y actuador) de estos dispositivos en una sola tarjeta de adquisición de datos que se conecta a una PC, debido a la complejidad que presenta este sistema de control desde diferentes puntos del área de trabajo, surge la necesidad de implementar una estrategia que permita el control de dispositivos de forma remota.

Multimedia files in general need plenty of disk space for storage apart from being unwieldy for communication purposes and sound files are no exception. Hence compression of these files has become a necessity and is a ripe subject for research. The field of signal processing has enjoyed several analysis tools in the past. One of the more recent developments in this field has been the emergence of a new transform, The Wavelet Transform. In fact, its use is not restricted to signal processing alone, but ranges over such diverse fields as image processing, communications, mathematics, computer science to name a few.
We accomplished the goal of compressing and decompressing the sound waveform by dividing our work into six modules: Sound compression, Sound compress, Compute threshold, 1-D DWT, Sound uncompress and Run project. Here we used Bi-orthogonal wavelet “bior 3.7” because it exhibits the property of linear phase, which is needed for signal reconstruction.

The number of red blood cells contributes more to clinical diagnosis with respect to blood diseases. The aim of this research is to produce a computer vision system that can detect and estimate the number of red blood cells in the blood sample image. Morphological is a very powerful tool in image processing, and it is been used to segment and extract the red blood cells from the background and other cells. The algorithm used features such as shape of red blood cells for counting process, and Hough transform is introduced in this process. The result presented here is based on images with normal blood cells. The tested data consists of 10 samples and produced the accurate estimation rate closest to 96% from manual counting.

Skripsi ini bertujuan untuk mempelajari seberapa besar pengaruh tegangan lebih akibat tegangan impuls pada transformator daya 150 kV serta memberikan solusi berupa sistem pengamanannya. Karena untuk memperbaiki kerusakan pada sebuah transformator pada umumnya memerlukan biaya yang tinggi, apalagi untuk sebuah transformator yang besar dan mahal. Hal ini menyebabkan perlunya cara penanggulangan dini pada sebuah transformator.Transformator digunakan secara luas, baik dalam bidang tenaga listrik maupun elektronika. Penggunaannya dalam sistem tenaga memungkinkan dipilihnya tegangan yang sesuai dan ekonomis untuk tiap-tiap keperluan, misalnya kebutuhan akan tegangan tinggi dalam pengiriman daya listrik jarak jauh. Dari hasil tampilan gelombang tegangan impuls dan analisis pada  kumparan transformator daya 150 kV. Semakin besar nilai perbandingan kapasitansi pada masing-masing lapisan kumparan, maka akan semakin membahayakan bagi transformator daya apabila terkena tegangan impuls khususnya pada lapisan yang mendekati titik netralnya. Dengan demikian program ini dapat sebagai referensi awal dalam pembuatan transformator daya 150 kV

Gamelan merupakan salah satu alat musik tradisional dari pulau Jawa. Seperangkat gamelan terdiri dari berbagai macam alat musik yang dimainkan secara bersama-sama. Karena perpaduan antara bunyi gamelan satu dengan bunyi gamelan yang lainnya menggambarkan keselaraasan dalam kehidupan bermasyarakat. Namun seiring berjalannya waktu, peminat gamelan semakin sedikit dan orang pembuat gamelan juga semakin sulit dijumpai.Gamelan yang digunakan dalam penelitian ini yaitu: Gong, Kempul, Kenong dan Bonang Penerus. Bunyi gamelan akan diidentifikasi dengan caramencari frekuensi-frekuensi bunyi gamelannya. Dengan menggunakan metode Fast Fourier Transform (FFT) suatu bunyi yang berdomain waktu dapat diubah menjadi domain frekuensi dengan salah satu software Matlab.Proses dalam jaringan syaraf tiruan Backpropagation ini menggunakan jumlah neuron yang bervariasi, diantaranya: 70, 80, 90, 100 dan 110 untuk mengetahui keakuratan jaringan dalam mengenali data yang diujikan. Hanya jumlah neuron 110 lah yang dapat mengenali data pengujian sebesar 99% untuk data pengujian pelatihan dengan MSE 0.0001233 pada epoch ke 1000. Maka hasil dalam penelitian ini jaringan dapat mengenali data pengujian dengan benar. Sehingga mengidentifikasi spektrum bunyi menggunakan jaringan syaraf tiruan dapat digunakan untuk mengenali berbagai bunyi gamelan bahkan bunyi yang lainnya.