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Design of Experiments by Examples Using Matlab

Design of Experiments by Examples Using Matlab
Author: Perez C.
Publisher: Createspace Independent Publishing Platform
Total Pages: 196
Release: 2017-07-31
Genre:
ISBN: 9781974098101

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MATLAB provides apps and design tools for optimally calibrating complex engines and powertrain subsystems. You can work with design of experiments, define optimal test plans, automatically fit statistical models, and generate calibrations and lookup tables for complex high-degree-of-freedom engines that would otherwise require exhaustive testing using traditional methods. Calibrations can be optimized at individual operating points or over drive cycles to identify the optimal balance of engine fuel economy, performance, and emissions. Using apps or MATLAB(R) functions, you can automate the calibration process for similar engine types. The Key Features in this book are the following: -Apps that support the entire workflow: designing experiments, fitting statistical models to engine data, and producing optimal calibrations -Design-of-Experiments methodology for reducing testing time through classical, space-filling, and optimal design techniques -Accurate engine modeling with data fitting techniques including Gaussian process, radial basis function, and linear regression modeling -Boundary modeling to keep optimization results within the engine operating envelope Generation of lookup tables from optimizations over drive cycles, models, or test data -Export of performance-optimized models to Simulink for use in simulation and HIL testing This book develops the following topics: - "Model-Based Calibration Toolbox" - "Design of Experiments" - "Empirical Engine Modeling" - "Selecting Data and Models to Fit" - "Selecting Global and Two-Stage Models" - "Using Validation Data" - "Exporting the Models" - "Optimized Calibration" - "Importing Additional Models into CAGE" - "Setting Up and running the Optimization" - "Composite Models and Modal Optimization" - "Use Optimization Results"


Design of Experiments With Matlab

Design of Experiments With Matlab
Author: Perez C.
Publisher: Createspace Independent Publishing Platform
Total Pages: 252
Release: 2017-07-31
Genre:
ISBN: 9781974098668

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MATLAB can create Experimental Design Models with Model-Based Calibration Toolbox. This models can be exported to Simulink(R) to support control design, hardware-in-the-loop testing, and powertrain simulation activities across the powertrain design team. The toolbox has two main user interfaces for model-based calibration workflows: - Model Browser for design of experiment and statistical modeling - CAGE Browser for analytical calibration The Model Browser part of the toolbox is a powerful tool for experimental design and statistical modeling. The models you build with the Model Browser can be imported into the CAGE Browser part of the toolbox to produce optimized calibration tables. The command-line interface to the Model-Based Calibration Toolbox product enables the design of experiments and modeling tolos available in the toolbox to be accessible from the test bed. You can use these commands to assemble your specific engine calibration processes into an easy to use script or graphical interface. Calibration technicians and engineers can use the custom interface without the need for extensive training. The Model Browser is a flexible, powerful, intuitive graphical interface for building and evaluating experimental designs and statistical models. This tools enables: - Design of experiment tools can drastically reduce expensive data collection time. - You can create and evaluate optimal, space-filling, and classical designs, and constraints can be designed or imported. - Hierarchical statistical models can capture the nature of variability inherent in engine data, accounting for variation both within and between tests. - The Model Browser has powerful, flexible tools for building, comparing, and evaluating statistical models and experimental designs. - There is an extensive library of prebuilt model types and the capability to build userdefined models. - You can export models to CAGE or to MATLAB or Simulink software. - Faster calibration - Improved calibration quality - Improved system understanding - Reduced development time CAGE (CAlibration GEneration) is an easy-to-use graphical interface for calibrating lookup tables for your electronic control unit (ECU). As engines get more complicated, and models of engine behavior more intricate, it is increasingly difficult to rely on intuition alone to calibrate lookup tables. CAGE provides analytical methods for calibrating lookup tables. CAGE uses models of the engine control subsystems to calibrate lookup tables. With CAGE, you fill and optimize lookup tables in existing ECU software using Model Browser models. From these models, CAGE builds steady-state ECU calibrations. CAGE also compares lookup tables directly to experimental data for validation. This book develops the following topics: - "Model-Based Calibration Toolbox" - "Design of Experiments" - "Design and Modeling Scripts" - "Model-Based Calibration Toolbox Command-Line Interface" - "Automate Design and Modeling With Scripts" - "Statistical Modeling and Optimization" - "Two-Stage Modeling" - "Create Multiple Models to Compare" - "Create a Constrained Space-Filling Design" - "Create Optimal and Classical Designs" - "Use the Design Evaluation Tool" - "Data Manipulation for Modeling" - "Match Data to Experimental Designs" - "Feature Calibration"


Programming Behavioral Experiments with MATLAB and Psychtoolbox

Programming Behavioral Experiments with MATLAB and Psychtoolbox
Author: Erman Misirlisoy
Publisher: Routledge
Total Pages: 63
Release: 2016-11-10
Genre: Psychology
ISBN: 1317205626

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Human behavior is fascinating so it’s no surprise that psychologists and neuroscientists spend their lives designing rigorous experiments to understand it. MATLAB is one of the most widely used pieces of software for designing and running behavioral experiments, and it opens up a world of quick and flexible experiment programming. This book offers a step-by-step guide to using MATLAB with Psychtoolbox to create customisable experiments. Its pocket size and simple language allow you to get straight to the point and help you to learn fast in order to complete your work in great time. In nine simple steps, it guides you all the way from setting parameters for your experiment to analysing the output. Gone are the daunting days of working through hundreds of irrelevant and complicated documents, as in this handy book, Erman Misirlisoy coaxes you in the right direction with his friendly and encouraging tricks and tips. If you want to learn how to develop your own experiments to collect and analyse behavioral data, then this book is a must-read. Whether you are a student in experimental psychology, a researcher in cognitive neuroscience, or simply someone who wants to run behavioral tasks on your friends for fun, this book will offer you the skills to succeed.


Design of Experiments and Calibration Models. Examples with MATLAB

Design of Experiments and Calibration Models. Examples with MATLAB
Author: J Lopez
Publisher:
Total Pages: 348
Release: 2019-10-14
Genre:
ISBN: 9781699744185

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With today's ever-increasing complexity of models, design of experiment has become an essential part of the modeling process. The Design Editor within the Model-Based Calibration Toolbox product is crucial for the efficient collection of engine data. Dyno-cell time is expensive, and the savings in time and money can be considerable when a careful experimental design takes only the most useful data. Dramatically reducing test time is growing more and more important as the number of controllable variables in more complex engines is growing. With increasing engine complexity, the test time increases exponentially.Model-Based Calibration Toolbox provides apps and design tools for optimally calibrating complex engines and powertrain subsystems. You can define optimal test plans, automatically fit statistical models, and generate calibrations and lookup tables for complex high-degree-of-freedom engines that would otherwise require exhaustive testing using traditional methods. Calibrations can be optimized at individual operating points or over drive cycles to identify the optimal balance of engine fuel economy, performance, and emissions. Using apps or MATLAB functions, you can automate the calibrationprocess for similar engine types.Models created with Model-Based Calibration Toolbox can be exported to Simulink to support control design, hardware-in-the-loop testing, and powertrain simulation activities across the powertrain design team. Calibration tables can be exported to ETAS INCA and ATI Vision. This book develops examples of design of experiments and calibration models.


Design of Experiments and Modeling Using Matlab

Design of Experiments and Modeling Using Matlab
Author: P. Braselton
Publisher: Createspace Independent Publishing Platform
Total Pages: 438
Release: 2017-05-26
Genre:
ISBN: 9781546888871

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MATLAB Model-Based Calibration Toolbox provides apps and design tools for optimally calibrating complex experimental designs models. This Toolbox use un Apps that support the entire workflow: designing experiments, fitting statistical models to engine data, and producing optimal calibrations. Also support Design-of-Experiments methodology for reducing testing time through classical, space-filling, and optimal design techniques, This Toolbox accurate engine modeling with data fitting techniques including Gaussian process,radial basis function, and linear regression modeling. Other options are: Boundary modeling to keep optimization results within the engine operating envelope, Generation of lookup tables from optimizations over drive cycles, models, or test data. Also is posible export of performance-optimized models to Simulink for use in simulation and HIL testing


Operation Research With Matlab

Operation Research With Matlab
Author: Perez C.
Publisher: Createspace Independent Publishing Platform
Total Pages: 156
Release: 2017-08-07
Genre:
ISBN: 9781974301188

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In MATLAB you can work with design of experiments, define optimal test plans, automatically fit statistical models, and generate calibrations and lookup tables for complex high-degree-of-freedom engines that would otherwise require exhaustive testing using traditional methods. Calibrations can be optimized at individual operating points or over drive cycles to identify the optimal balance of engine fuel economy, performance, and emissions. Using apps or MATLAB(R) functions, you can automate the calibration process for similar engine types. The Model Browser is a flexible, powerful, intuitive graphical interface for building and evaluating experimental designs and statistical models: - Design of experiment tools can drastically reduce expensive data collection time. - You can create and evaluate optimal, space filling, and classical designs, and constraints can be designed or imported. - Hierarchical statistical models can capture the nature of variability inherent in engine data, accounting for variation both within and between tests. - The Model Browser has powerful, flexible tools for building, comparing, and evaluating statistical models and experimental designs. - There is an extensive library of prebuilt model types and the capability to build userdefined models. This book develops the following topics: - "Model-Based Calibration Toolbox" - "Design of Experiments" - "Workflows For Modeling" - "Selecting Data and Models to Fit" - "Projects and Test Plans" - "Desing Editor and Design Constraints" - "Creating a Space-Filling Design" - "Creating an Optimal Design" - "Creating a Classical Design" - "Manipulate Designs" - "Saving, Exporting, and Importing Designs" - "Fit Models to Collected Design Data - "Data Loading Application Programming Interface"


Robust Control Design with MATLAB®

Robust Control Design with MATLAB®
Author: Da-Wei Gu
Publisher: Springer Science & Business Media
Total Pages: 832
Release: 2005-06-20
Genre: Technology & Engineering
ISBN: 9781852339838

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Shows readers how to exploit the capabilities of the MATLAB® Robust Control and Control Systems Toolboxes to the fullest using practical robust control examples.


Advanced Statistical Modeling and Design of Experiments Using Matlab

Advanced Statistical Modeling and Design of Experiments Using Matlab
Author: P. Braselton
Publisher: Createspace Independent Publishing Platform
Total Pages: 396
Release: 2017-05-29
Genre:
ISBN: 9781547002313

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The MATLAB software include eficient tools for develop the design of experiments. The Model-Based Calibration Toolbox product contains tools for design of experiment, statistical modeling, and calibration of complex systems. The toolbox has two main apps: Model Browser for design of experiment and statistical modeling and CAGE Browser for analytical calibration. The Model Browser is a flexible, powerful, intuitive graphical interface for building and evaluating experimental designs and statistical models. Design of experiment tools can drastically reduce expensive data collection time. With MATLAB you can create and evaluate optimal, space filling, and classical designs, and constraints can be designed or imported. Hierarchical statistical models can capture the nature of variability inherent in engine data, accounting for variation both within and between tests. The Model Browser has powerful, flexible tools for building, comparing, and evaluating statistical models and experimental designs. There is an extensive library of prebuilt model types and the capability to build userdefined models.


Robust Control Design with MATLAB®

Robust Control Design with MATLAB®
Author: Da-Wei Gu
Publisher: Springer Science & Business Media
Total Pages: 473
Release: 2014-07-08
Genre: Technology & Engineering
ISBN: 1447146824

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Robust Control Design with MATLAB® (second edition) helps the student to learn how to use well-developed advanced robust control design methods in practical cases. To this end, several realistic control design examples from teaching-laboratory experiments, such as a two-wheeled, self-balancing robot, to complex systems like a flexible-link manipulator are given detailed presentation. All of these exercises are conducted using MATLAB® Robust Control Toolbox 3, Control System Toolbox and Simulink®. By sharing their experiences in industrial cases with minimum recourse to complicated theories and formulae, the authors convey essential ideas and useful insights into robust industrial control systems design using major H-infinity optimization and related methods allowing readers quickly to move on with their own challenges. The hands-on tutorial style of this text rests on an abundance of examples and features for the second edition: • rewritten and simplified presentation of theoretical and methodological material including original coverage of linear matrix inequalities; • new Part II forming a tutorial on Robust Control Toolbox 3; • fresh design problems including the control of a two-rotor dynamic system; and • end-of-chapter exercises. Electronic supplements to the written text that can be downloaded from extras.springer.com/isbn include: • M-files developed with MATLAB® help in understanding the essence of robust control system design portrayed in text-based examples; • MDL-files for simulation of open- and closed-loop systems in Simulink®; and • a solutions manual available free of charge to those adopting Robust Control Design with MATLAB® as a textbook for courses. Robust Control Design with MATLAB® is for graduate students and practising engineers who want to learn how to deal with robust control design problems without spending a lot of time in researching complex theoretical developments.


Using MATLAB to Solve Statistical Problems

Using MATLAB to Solve Statistical Problems
Author: Yuri A.W. Shardt
Publisher: Springer Nature
Total Pages: 74
Release: 2023-11-01
Genre: Technology & Engineering
ISBN: 3031402995

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This companion book to the textbook Statistics for Chemical and Process Engineers−A Modern Approach provides a complete overview of how to use Matlab to solve typical statistical problems in engineering. In addition to short sections on the required theory, the focus of the book is on detailed, line-by-line MATLAB code for solving the specific problems. Furthermore, solutions are provided for standard problems that can then be re-used and modified as necessary. End-of-chapter questions allow the reader to independently test the knowledge acquired.