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Abstrak :
Gives the reader hands on example-base experience for simulating dynamical models in MATLAB®/simulink® and animating them in VRML. More than 150 images describe each step in the model realizations helping readers to understand them visually. Diverse examples and profound problem treatment enable the reader to animate complex dynamical problems m-files, Simulink models, VRML files and jpegs available for download provide full solutions for the end-of-chapter problems Virtual Reality and Animation for MATLAB® and simulink® Users demonstrates the simulation and animation of physical systems using the MATLAB® virtual reality toolbox (virtual models are created in V-realm builder). The book is divided into two parts; the first addresses MATLAB® and the second Simulink®. The presentation is problem-based with each chapter teaching the reader a group of essential principles in the context of a step-by-step solution to a particular issue. Examples of the systems covered include mass-spring-dampers, a crank-slider mechanism and a moving vehicle.

Abstrak :
Cet ouvrage permet d’apprendre à utiliser les Outils Simscape et SimpowerSystems pour modéliser et simuler des circuits électroniques, électromécaniques et électronique de puissance. Pour utiliser ces deux outils, la connaissance de MATLAB et SIMULINK est indispensable. Cet ouvrage possède trois types de chapitres : prise en main de l’outil, description des différentes bibliothèques avec quelques applications et enfin chapitre d’applications très utilisées dans les domaines universitaires et industriels.

Abstrak :
Parallel MATLAB for Multicore and Multinode Computers is the first book on parallel MATLAB and the first parallel computing book focused on the design, code, debug, and test techniques required to quickly produce well-performing parallel programs.MATLAB is currently the dominant language of technical computing with one million users worldwide, many of whom can benefit from the increased power offered by inexpensive multicore and multinode parallel computers. MATLAB is an ideal environment for learning about parallel computing, allowing the user to focus on parallel algorithms instead of the details of implementation.

Abstrak :
Learn how to use PTC® Mathcad Prime® 3.0, one of the world?s leading tools for technical computing, in the context of engineering, science, and math applications. Quickly harness the power of PTC Mathcad Prime 3.0 to solve both simple and complex problems. Essential PTC® Mathcad Prime® 3.0 is perfect for college students, first-time users, and experienced Mathcad 15 users who are moving to PTC Mathcad Prime 3.0.Updated from maxfield?s popular essential mathcad, this book introduces the most powerful functions and features of the new PTC Mathcad Prime 3.0 software and teaches how to apply them to create comprehensive calculations for any quantitative subject. Examples from several fields demonstrate the power and utility of PTC Mathcad?s tools while also demonstrating how users can eff ectively incorporate Microsoft® Excel spreadsheets into the software.

Abstrak :
MATLAB has become the standard software tool for solving scientific and engineering problems due to its powerful built-in functions and its ability to program. Assuming no knowledge of programming, this book guides the reader through both programming and built-in functions to easily exploit MATLAB's extensive capabilities for tackling engineering problems.The book starts with programming concepts, such as variables, assignments, and selection statements, moves on to loops, and then solves problems using both the programming concept and the power of MATLAB. In-depth coverage is given to input/output, a topic fundamental to many engineering applications.The third edition of MATLAB: A Practical Introduction to Programming and Problem Solving has been updated to reflect the functionality of the current version of MATLAB. It features new and revised end-of-chapter exercises, stronger coverage of loops and vectorizing, and more engineering applications to help the reader learn this software tool in context.

Abstrak :
MATLAB by example guides the reader through each step of writing MATLAB programs. The book assumes no previous programming experience on the part of the reader, and uses multiple examples in clear language to introduce concepts and practical tools. Straightforward and detailed instructions allow beginners to learn and develop their MATLAB skills quickly.

The book consists of ten chapters, discussing in detail the integrated development environment (IDE), scalars, vectors, arrays, adopting structured programming style using functions and recursive functions, control flow, debugging, profiling, and structures. A chapter also describes Symbolic Math Toolbox, teaching readers how to solve algebraic equations, differentiation, integration, differential equations, and Laplace and Fourier transforms. Containing hundreds of examples illustrated using screen shots, hundreds of exercises, and three projects.

Abstrak :
This monograph presents teaching material in the field of differential equations while addressing applications and topics in electrical and biomedical engineering primarily. The book contains problems with varying levels of difficulty, including Matlab simulations. The target audience comprises advanced undergraduate and graduate students as well as lecturers, but the book may also be beneficial for practicing engineers alike.

Abstrak :
Penggunaan inverter untuk mengubah tegangan masukan searah (DC) menjadi tegangan keluaran arus bolak-balik (AC) saat ini sangat banyak digunakan terutama di industri, kantor, maupun di perumahan. Bahkan dengan munculnya energi alternatif seperti solar sel, turbin angin, fuel cell, tidak lepas dari penggunaan inverter. Inverter yang dibuat dengan menggunakan metode algoritma Phase Locked Loop (PLL) digital satu fasa ini diaplikasikan untuk menghasilkan sinyal keluaran yang sudut fasa dan frekuensinya sama dengan suatu sinyal referensi tertentu. Namun, hasil sinyal keluaran dari inverter masih memiliki distorsi harmonik yang tinggi. Oleh karena itu perlu digunakan filter untuk menghilangkan distorsi harmoniknya agar lebih baik bentuk sinyal keluarannya. Untuk melakukan simulasi dan real time monitoring terhadap sinyal keluaran PLL digunakan sebuah Simulink library browser pada Matlab yaitu xPC Target. Algoritma program PLL yang dibuat menggunakan S-function C-MEX terletak pada komputer host dan hasil simulasi dari real time monitoring ditampilkan pada komputer target secara real time.

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The use of an inverter to convert the input voltage direct current (DC) into output voltage alternating current (AC) is now very widely used, especially in the industrial, office, and residential. Even with the advent of alternative energy such as solar cells, wind turbines, fuel cells, can not be separated from the use of an inverter. Inverters are made by using the algorithm Phase Locked Loop (PLL) digital single phase was applied to produce an output signal frequency and phase angle equal to a given reference signal. However, the output signal of the inverter still has high harmonics. Therefore it is necessary to use filters to eliminate harmonics distortion in order to better shape the output signal. To perform the simulation and real time monitoring of the output signal PLL used a Simulink library browser on Matlab is xPC Target. PLL program algorithms created using S-function C-MEX is located on the host computer and the results of real time monitoring simulation displayed on the target computer in real time.

Abstrak :
Debit air (flowrate) yang bernilai konstan merupakan besaran fisis fundamental dalam sistem transportasi fluida dari satu tempat ke tempat lain. Untuk mencapai hal tersebut, dibutuhkan suatu sistem kendali yang mampu menghasilkan debit air bernilai konstan. Pada penelitian ini, transportasi fluida dibuat dalam sebuah rangkaian plant miniatur dengan menerapkan sistem kendali didalamnya. Pada plant tersebut terdapat actuator control valve, flow transmitter, dan Programmable Logic Controller (PLC). OPC Server merupakan perangkat lunak antarmuka menggunakan mode client/server berbasis COM/ DCOM yang memungkinkan MATLAB dapat berkomunikasi dengan PLC. Dalam proses komunikasi antara PLC dengan MATLAB digunakan OPC server yang berfungsi sebagai "jembatan" antara keduanya. Sistem kendali yang diterapkan berupa PID-Controller dan soft computing Neural Network (NN) dengan menggunakan MATLAB SIMULINK. Penerapan soft computing Neural Network (NN) bertujuan untuk mengoptimasi performa sistem kendali PID-Controller yang telah umum digunakan. Faktor-faktor performa yang dijadikan parameter pembanding adalah nilai rise time, settling time, maximum overshoot, dan steady-state error. Berdasarkan hasil percobaan, Neural Network Controller memiliki nilai permformansi yang lebih baik daripada PID-Controller. Nilai performansi Neural Network Controller yang didapatkan yakni maximum overshoot = 5.36% dan steady-state error = 0.85%.

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Flowrate is a fundamental physical quantity in the fluid transportation system from one place to another. To achieve this, a control system is needed that is able to produce a constant flow of water. In this study, fluid transport was made in a miniature plant series by implementing a control system in it. At the plant there is a control valve actuator, flow transmitter, and Programmable Logic Controller (PLC). OPC Server is interface software using COM / DCOM-based client / server mode that allows MATLAB to communicate with the PLC. In the process of communication between PLC and MATLAB, the OPC server is used as a "bridge" between the two. The control system applied is in the form of PID-Controller and soft computing Neural Network (NN) using MATLAB SIMULINK. The application of soft computing Neural Network (NN) aims to optimize the performance of the PID-Controller control system that has been commonly used. Performance factors that are used as comparison parameters are the value of rise time, settling time, maximum overshoot, and steady-state error. Based on the results of the experiment, the Neural Network Controller has a better value of permformance than PID-Controller. The performance value of the Neural Network Controller obtained is maximum overshoot = 5.36% and steady-state error = 0.85%.

Abstrak :
Proses Thermal Mixing adalah jenis dari proses pencampuran yang penting di berbagai industri, seperti industri pangan, pupuk, farmasi, material sampai petrochemical. Proses Thermal Mixing merupakan proses Multi input multi ouput (MIMO), karena bekerja dengan mengendalikan dua flow air panas dan air dingin untuk mengendalikan temperatur dan level campuran. Meskipun memiliki respon yang kurang baik untuk mengendalikan MIMO, namun PID masih banyak digunakan karena kesederhanaannya. Algoritma non konvensional yang lebih baik seperti fuzzy control memiliki kerumitan yang tinggi dibanding PID. Algoritma Adaptive Fuzzy PID Controller (AFPIDC) merupakan gabungan dari keduanya, memiliki basis PID yang cukup sederhana namun ditambahkan aspek Fuzzy untuk mempercepat pengendalian dengan cara mengubah konstanta PID secara real-time (on the fly). Algoritma AFPIDC ini diterapkan pada simulasi sistem pengendalian temperatur dan level air pada proses water Thermal Mixing dan dilakukan pada program MATLAB/SIMULINK di PC. Fuzzy yang digunakan memiliki dua input berupa error dan perubahan error, dan memiliki tiga output berupa perubahan nilai konstanta PID. Pengujian sistem dilakukan dengan simulasi perubahan setpoint dan gangguan berupa kebocoran flow. Dari hasil pengujian sistem, pengendali AFPIDC memiliki performa yang lebih baik dari PID dalam mengendalikan temperatur dan level pada sistem. Dalam pengendalian temperatur, didapatkan nilai settling time PID sebesar 830 detik, AFPIDC sebesar 328 detik dan untuk nilai overshoot PID 6,3% dan AFPIDC 0%. Untuk pengendalian level didapatkan settling time PID 3221 detik dan AFPIDC 235 detik dengan nilai overshoot PID 10,5% dan AFPIDC 0%. Dari pengujian sistem terhadap gangguan kebocoran, pengendali temperatur membutuhkan waktu untuk kembali stabil pada PID 780 detik, AFPIDC 250 detik. Sedangkan untuk pengendalian level untuk kembali stabil membutuhkan waktu PID 4510 detik, AFPIDC 225 detik.

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The Thermal Mixing Process is a type of mixing process that is important in various industries, such as the food, fertilizer, pharmaceutical, material to petrochemical industries. The Thermal Mixing Process is a multiple-input multiple-output process (MIMO), because it works by controlling hot water and cold-water flows to control the temperature and level of the mixture. Although it has a poor response to control MIMO system, PID is still widely used because of its simplicity. There are some better control algorithm, such as fuzzy control, but have higher complexity than PID. The Adaptive Fuzzy PID Control (AFPIDC) algorithm is a combination of the two, has a simple PID basis with added Fuzzy aspects to speed up control by changing the PID constant in realtime. The AFPIDC algorithm is applied to the simulation of temperature and water level control systems in the process of water Thermal Mixing and is done on the MATLAB/SIMULINK program on a PC. The fuzzy algorithm uses two inputs in the form of errors and changes in errors and has three outputs in the form of changes in the value of the PID constant. System testing is done by simulating setpoint changes and disruption in the form of leakage flow. From the results of system testing, AFPIDC controllers have better performance than PID in controlling temperature and level in the system. In temperature control, the PID settling time is 830 seconds, AFPIDC is 328 seconds and the PID overshoot is 6,3% and AFPIDC is 0%. In level control, the settling time of PID is 3221 seconds while AFPIDC is 235 seconds with PID overshoot is 10,5% while AFPIDC 0%. From testing the system with leakage disturbance, the temperature controller needs time to regain stability at PID 780 seconds, AFPIDC 250 seconds. Meanwhile the level controlling stabilizes at PID 4510 seconds, and AFPIDC at 225 seconds.