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Search results “Modelling and analysis for process control”
Mod-01 Lec-03 Lecture-03-Mathematical Modeling (Contd...1)
 
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Process Control and Instrumentation by Prof.A.K.Jana,prof.D.Sarkar Department of Chemical Engineering,IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 92343 nptelhrd
Mod-01 Lec-24 Process Modelling
 
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Principles of Engineering System Design by Dr. T Asokan,Department of Engineering Design,IIT Madras.For more details on NPTEL visit http://nptel.ac.in
Views: 4356 nptelhrd
Mathematical Model of Control System
 
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Mathematical Model of Control System watch more videos at https://www.tutorialspoint.com/videotutorials/index.htm Lecture By: Mrs. Gowthami Swarna, Tutorials Point India Private Limited
Mod-01 Lec-27 System modeling and simulation
 
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Principles of Engineering System Design by Dr. T Asokan,Department of Engineering Design,IIT Madras.For more details on NPTEL visit http://nptel.ac.in
Views: 40086 nptelhrd
Intro to Control - 6.1 State-Space Model Basics
 
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Explanation of state-space modeling of systems for controls.
Views: 265129 katkimshow
Mod-01 Lec-01 Lecture-01-Introduction to Process Control
 
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Process Control and Instrumentation by Prof.A.K.Jana,prof.D.Sarkar Department of Chemical Engineering,IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 208037 nptelhrd
Teaching MATLAB & Simulink Modeling and Process Control
 
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Speaker: Zuyi (Jacky) Huang received his Ph.D. at Texas A&M University in 2010. He is now an Assistant Professor in the Department of Chemical Engineering at Villanova University. He teaches Chemical Process Control (for senior students) and Systems Biology (for graduate students). He is enthusiastic in applying innovative teaching methods in class to educate students with modeling and control skills. He and his colleagues at Villanova got 2016 ASEE Joseph J. Martin Award. He is the director of the Biological & Environmental Systems Engineering Lab (BESEL). His research is focused on developing advanced modeling and systems analysis techniques to manipulate microbial biological systems for generating biofuels from wastewater and for combating biofilm-associated pathogens. Description: The inverted-classroom teaching format and the application of MATLAB/Simulink have recently generated considerable research interest in chemical engineering education. MATLAB/Simulink was introduced in mathematics-intensive courses due to its user-friendly interface for mathematical model simulations. Inverted classroom approach has been reported to be generally beneficial for engineering courses, but it has not been applied to MATLAB/Simulink education in a single course. The aim of the first project in this work is to examine the effectiveness of the inverted-classroom approach in developing MATLAB/Simulink skills of upper-division undergraduates in Villanova’s chemical process control course. Teaching modules include solving ODE models, performing Laplace transform, and designing PID controllers. Surveys of students’ evaluation revealed that the three inverted-classroom teaching modules were effective in enhancing students’ understanding of mathematics-intensive process control concepts and improving their MATLAB simulation skills. Students’ overall feedback on the inverted-classroom format was positive as they gradually adapted to inverted-classroom learning format. USA high-school students are falling behind their peers from other countries such as Finland and Korea in their mathematical performance. Solving ordinary differential equations (ODEs) is especially challenging to USA high-school and college students. It is thus necessary to re-generate the momentum of inspiring or stimulating high-school students to participate in more math-related trainings or projects. In the second project of this work, we developed a web-based training approach to train high-school students modeling skills to simulate the dynamics of microbial fuel cells (MFCs) in MATLAB Simulink. Due to its capability of digesting organic compounds from waste water to generate electricity, the MFC is regarded as one of the most sustainable approaches to treat waste water and generate bioenergy at the same time. MATLAB Simulink makes solving ODE models as interesting as building Lego projects. Two junior students from local high-schools watched the training videos and built the MFC ODE model in MATLAB Simulink with the help from the instructor via chat software Skype and Teamviewer. A survey was given at the end of the project to evaluate the improvement students’ knowledge in MFC and gather what students like and dislike the pseudo inverted-classroom approach. The result shows that it is promising to attract and train high school students with modeling skills by providing web-based training modules and Skype meetings.
Views: 1593 APMonitor.com
Mod-01 Lec-04 Lecture-04-Mathematical Modeling (Contd...2)
 
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Process Control and Instrumentation by Prof.A.K.Jana,prof.D.Sarkar Department of Chemical Engineering,IIT Kharagpur. For more details on NPTEL visit http://nptel.iitm.ac.in
Views: 29291 nptelhrd
Transfer Functions in Simulink for Process Control
 
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An introduction on deriving transfer functions from a linearized state space model via Laplace Transforms, and how we can input transfer functions into Simulink to model the response of a system to a given perturbation.
Views: 2784 Vincent Stevenson
1st order modelling 5 - fluid tank systems
 
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Lectures aimed at engineering undergraduates. Presentation focuses on understanding key prinicples, processes and problem solving rather than mathematical rigour. Derives models for the depth of simple tank systems with in-flow and out-flow based on pipe flow models. Considers high pressure input or direct inflow and analogies with electrical circuits.
Views: 34196 John Rossiter
Estimating a mediation model including covariates with PROCESS (V2.16)
 
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Estimating a mediation model including covariates with PROCESS.
Views: 4381 Wouter SMCR
Mathematical Modeling: Energy Balances
 
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Develops a mathematical model for a chemical process using energy balances. Made by faculty at Lafayette College and produced by the University of Colorado Boulder, Department of Chemical & Biological Engineering. Check out our Process Control playlist: https://www.youtube.com/playlist?list=PL4xAk5aclnUhfXrHhv_ZQfbQ6w6ahwfFQ Are you using a textbook? Check out our website for screencasts organized by popular textbooks: http://www.learncheme.com/screencasts/process-controls Check out our website for interactive Process Control simulations: http://www.learncheme.com/simulations/process-control
Views: 15557 LearnChemE
Turning a Model Into a Block Diagram
 
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Shows how to turn a model into a block diagram for a process control problem. Made by faculty at Lafayette College and produced by the University of Colorado Boulder, Department of Chemical & Biological Engineering. Check out our Process Control playlist: https://www.youtube.com/playlist?list=PL4xAk5aclnUhfXrHhv_ZQfbQ6w6ahwfFQ Are you using a textbook? Check out our website for screencasts organized by popular textbooks: http://www.learncheme.com/screencasts/process-controls Check out our website for interactive Process Control simulations: http://www.learncheme.com/simulations/process-control
Views: 11872 LearnChemE
SPSS - Moderated Mediation with PROCESS (Model 7)
 
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Lecturer: Dr. Erin M. Buchanan Missouri State University Summer 2016 Lecture materials and assignment available at statstools.com. http://statstools.com/learn/advanced-statistics/ This video covers moderated mediation (model 7) using Hayes' Process plug in for SPSS - includes g power, data screening, analysis, and interpretation.
Views: 39593 Statistics of DOOM
State Space Models and Simulation in Python
 
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Linear Time Invariant (LTI) state space models are a linear representation of a dynamic system in either discrete or continuous time. Putting a model into state space form is the basis for many methods in process dynamics and control analysis. See http://apmonitor.com/pdc/index.php/Main/StateSpaceModel for source code and further information on state space models.
Views: 9589 APMonitor.com
Advanced Pharmaceutical Manufacturing
 
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There are a number of challenges that the industry faces in order to transition towards more competitive, systematic and efficient manufacturing. Regulatory authorities have recognized the deficiencies of pharmaceutical product manufacturing and aim to enhance process understanding through Quality by Design (QbD) and Process Analytical Technology (PAT) tools. As a result of this current effort to change the mindset in order to mimic the rest of the chemical industry, an additional transition is becoming more and more appealing: transition from batch to continuous production mode. However, continuous manufacturing requires detailed process understanding in terms of the evolution of all critical material properties as a function of its operating parameters and environmental conditions. Once process knowledge is translated into models, computer aided dynamic simulation tools will allow the design, analysis and optimization of continuous integrated processes. In this talk I will discuss the work that has been done in my lab towards the development of an integrated platform that will enable the efficient flowsheet simulation and analysis, the assessment of design alternatives, the feasibility analysis of the production line, and the control and optimization of process design and operations. The developed flowsheet model includes modules for all the necessary unit operations, namely powder feeding, mixing, roller compaction, tablet press and milling integrated to represent a tablet manufacturing line. Models used to represent each unit operation vary from empirical, first-principle or hybrid. Population balance models are developed in order to track the composition and particle size changes throughout complex powder processes dynamically. The developed flowsheet simulation is used to predict the propagation of upstream disturbances to final product quality, the assessment of recycle stream benefits, the identification of process integration bottlenecks and evaluation of different control strategies in order to retain the process within its design space. In addition, global dynamic sensitivity analysis is performed to identify critical process parameters not only within each unit operation, but also between different processes. Finally, simulation based optimization techniques enable the identification of the optimal operating conditions, as well as the optimal design sequence which leads to pharmaceutical tablets with desired characteristics. This work aims to merge knowledge, experience, experimental results and modeling tools for developing a dynamic simulation platform that will enable the safe implementation of the transition towards continuous pharmaceutical manufacturing. Biography: Marianthi Ierapetritou is a Professor and Chair in the Department of Chemical and Biochemical Engineering at Rutgers University in Piscataway, New Jersey. Dr. Ierapetritou’s research focuses on the following areas: 1) process operations; (2) design and synthesis of flexible production systems focusing on pharmaceutical manufacturing; 3) modeling of reactive flow processes; and 4) metabolic engineering with focus on biopharmaceutical production. Her research is supported by several federal (NIH, NSF, ONR, NASA) and industrial (BMS, J&J, ExxonMobil, Honeywell, Cardinal Health) grants. Among her accomplishments are the Outstanding Faculty Award, the Rutgers Board of Trustees Research Fellowship for Scholarly Excellence, and the prestigious NSF CAREER award. She has more than 180 publications, and has been an invited speaker to numerous national and international conferences. Dr. Ierapetritou obtained her BS from The National Technical University in Athens, Greece, her PhD from Imperial College (London, UK) in 1995 and subsequently completed her post-doctoral research at Princeton University (Princeton, NJ) before joining Rutgers University in 1998.
Views: 44243 APMonitor.com
1st order modelling 6 - thermal systems
 
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Lectures aimed at engineering undergraduates. Presentation focuses on understanding key prinicples, processes and problem solving rather than mathematical rigour. Derives models for simple thermal systems containing capacitance and insulation. Summarises analogies with other systems.
Views: 12170 John Rossiter
Statistical Process Control and Trending Analysis
 
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There are several methods to trend data to highlight both the preventative and corrective nature of the system. Plotting data over time is a good visual method to identify trends. Statistical Process Control (SPC) techniques such as control charts give an objective method to identify trends. A discussion of out of trend versus out of specification will be covered. For More Information Contact - Organization: NetZealous BDA GlobalCompliancePanel Website: http://www.globalcompliancepanel.com/ Email: [email protected] Help us caption & translate this video! http://amara.org/v/OXHK/
Integrating Process: Model & Math
 
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Describes an integrating process and uses an example of a cylindrical storage tank to develop a transfer function. Made by faculty at Lafayette College and produced by the University of Colorado Boulder, Department of Chemical & Biological Engineering. Check out our Process Control playlist: https://www.youtube.com/playlist?list=PL4xAk5aclnUhfXrHhv_ZQfbQ6w6ahwfFQ Are you using a textbook? Check out our website for screencasts organized by popular textbooks: http://www.learncheme.com/screencasts/process-controls Check out our website for interactive Process Control simulations: http://www.learncheme.com/simulations/process-control
Views: 6063 LearnChemE
Introduction to System Dynamics: Overview
 
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MIT 15.871 Introduction to System Dynamics, Fall 2013 View the complete course: http://ocw.mit.edu/15-871F13 Instructor: John Sterman Professor John Sterman introduces system dynamics and talks about the course. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 131627 MIT OpenCourseWare
Model Predictive Control (MPC)
 
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Advanced Process Control by Prof.Sachin C.Patwardhan,Department of Chemical Engineering,IIT Bombay.For more details on NPTEL visit http://nptel.ac.in
Views: 11227 nptelhrd
Laplace Transforms for Process Control
 
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Laplace domain allows algebraic manipulation of differential equations. Analysis in the Laplace domain can determine whether a signal will converge or diverge and whether it will oscillate or be smooth.
Views: 5292 APMonitor.com
State Space Analysis for Electrical System in Control Engineering by Engineering Funda
 
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In this video, i have explained State Space Analysis for Electrical System. For free materials of different engineering subjects use my android application named Engineering Funda with following link: https://play.google.com/store/apps/details?id=com.viaviapp.ENG_Funda Above Android application of Engineering Funda provides following services: 1. Free Materials (GATE exam, Class Notes, Interview questions) 2. Technical Forum 3. Technical discussion 4. Inquiry For more details and inquiry on above topic visit website of Engineering Funda with given link: http://www.engineeringfunda.co.in Engineering Funda channel is all about Engineering and Technology. Here this video is a part of Control Engineering . . . . . . . . . . . . . . . . #Control Engineering, #Control System, #Control System Engineering
Views: 13745 Engineering Funda
Second Order Systems in Process Control
 
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Second order systems may be underdamped (oscillate with a step input), critically damped, or overdamped. This lecture reviews theory and application of second order systems for process control. Second order systems are particularly useful to describe the closed loop response or underdamped mechanical systems.
Views: 11784 APMonitor.com
Thermolib - Modeling Thermodynamics in Simulink Part 1 of 3
 
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Website: http://www.thermolib.de Email: [email protected] Thermolib Free Trial Request: http://www.thermolib.de/free-trial.html Thermolib expands the MATLAB® /Simulink® Suite with tools to design, model and simulate complex thermodynamic systems. You can use this extensive library of thermodynamic components to build a model of your highly dynamic and nonlinear system in Simulink®. Use your Thermolib model to address issues of optimal design and control strategy. Simulate real gas behavior, liquid mixtures and chemical reactions all the while knowing that correct thermodynamic equations and calculations drive your model. This presentation provides you with a first inisght into Thermolib's capabilities and functionalities by showing examples like: - Absorption Heat Pump - Combined Cycle Power Plant - Solar Thermal Plant - Fuel Cell Vehicle - Air Conditioning - Reforming Process In addition, special featues like thermodynamic balancing and command-line functions are further explained. Wrapping up the presentation, the summary repeats the key features of thermodynamic modeling with Thermolib.
Views: 19899 EUtech1999
System Identification Methods
 
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I'm writing a book on the fundamentals of control theory! Get the book-in-progress with any contribution for my work on Patreon - https://www.patreon.com/briandouglas System Identification is the process of determining the model or the equations of motion for your system. This is incredibly important because basing a control system design off of a bad model results in a bad control system design. This video goes through the system identification process for a very simple system (a spring-mass system). Errata: 10:52 - 11:34 I said the two poles exist on the real line. I meant to say on the imaginary line. The vertical axis is the imaginary line. Don't forget to subscribe! I'm on Twitter @BrianBDouglas! If you have any questions on it leave them in the comment section below or on Twitter and I'll try my best to answer them. I will be loading a new video each week and welcome suggestions for new topics. Please leave a comment or question below and I will do my best to address it. Thanks for watching!
Views: 64615 Brian Douglas
12 Steps to Create a Dynamic Model
 
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Dynamic models are essential for understanding the system dynamics in open-loop (manual mode) or for closed-loop (automatic) control. These models are either derived from data (empirical) or from more fundamental relationships (first principles, physics-based) that rely on knowledge of the process. A combination of the two approaches is often used in practice where the form of the equations are developed from fundamental balance equations and unknown or uncertain parameters are adjusted to fit process data. In engineering, there are 4 common balance equations from conservation principles including mass, momentum, energy, and species. An alternative to physics-based models is to use input-output data to develop empirical dynamic models such as first-order or second-order systems. See http://apmonitor.com/pdc/index.php/Main/DynamicModeling
Views: 3737 APMonitor.com
Control Systems Lectures - Transfer Functions
 
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I'm writing a book on the fundamentals of control theory! Get the book-in-progress with any contribution for my work on Patreon - https://www.patreon.com/briandouglas This lecture describes transfer functions and how they are used to simplify modeling of dynamic systems. I will be loading a new video each week and welcome suggestions for new topics. Please leave a comment or question below and I will do my best to address it. Thanks for watching! Don't forget to subscribe! Follow me on Twitter @BrianBDouglas!
Views: 379794 Brian Douglas
State Space Analysis for MIMO in Control Engineering by Engineering Funda
 
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In this video, i have explained State Space Analysis MIMO. For free materials of different engineering subjects use my android application named Engineering Funda with following link: https://play.google.com/store/apps/details?id=com.viaviapp.ENG_Funda Above Android application of Engineering Funda provides following services: 1. Free Materials (GATE exam, Class Notes, Interview questions) 2. Technical Forum 3. Technical discussion 4. Inquiry For more details and inquiry on above topic visit website of Engineering Funda with given link: http://www.engineeringfunda.co.in Engineering Funda channel is all about Engineering and Technology. Here this video is a part of Control Engineering . . . . . . . . . . . . . . . . #Control Engineering, #Control System, #Control System Engineering
Views: 3674 Engineering Funda
Introduction to State Space Systems
 
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Lecture Series on Control Engineering by Prof. Ramkrishna Pasumarthy, Department of Electrical Engineering, IIT Madras and Dr. Viswanath Talasila, Telecommunication Engineering Department, Ramaiah Institute of Technology. For more details on NPTEL visit https://onlinecourses.nptel.ac.in/noc17_ee12/preview This lecture covers the basics of state space representation of control systems.
Views: 14134 Control engineering
Moderated Mediation and Controls
 
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This is another video lecture for the doctorate of management program at Case Western Reserve University. It covers the advanced topic of moderated mediation, as well as control variables.
Views: 43005 James Gaskin
SPSS - Mediation Analysis with PROCESS
 
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Lecturer: Dr. Erin M. Buchanan Missouri State University Spring 2015 Mediation analysis video covering model 4 in the process plug in (Hayes, 2013). Lecture materials and assignment available at statstools.com. http://statstools.com/learn/advanced-statistics/
Views: 103940 Statistics of DOOM
Laplace Transforms for Engineers
 
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This introduction on Laplace transforms covers basic strategies to solve and analyze differential equations for control systems analysis.
Views: 10220 APMonitor.com
Process Control and Dynamics in Python
 
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This course focuses on a complete start to finish process of physics-based modeling, data driven methods, and controller design. Although some knowledge of computer programming is required, students are led through several introductory topics that develop an understanding of numerical methods in process control. This course focuses on methods that are used in practice for simple or complex systems. It is divided into three main parts including (1) data driven modeling and controller development, (2) physics-based modeling and controller development, and (3) advanced controls with optimization. Example problems are provided throughout in the Python programming language.
Views: 8522 APMonitor.com
Stochastic modeling
 
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MIT 8.591J Systems Biology, Fall 2014 View the complete course: http://ocw.mit.edu/8-591JF14 Instructor: Jeff Gore Prof. Jeff Gore discusses modeling stochastic systems. The discussion of the master equation continues. Then he talks about the Gillespie algorithm, an exact way to simulate stochastic systems. He then moves on to the Fokker-Planck equation. License: Creative Commons BY-NC-SA More information at http://ocw.mit.edu/terms More courses at http://ocw.mit.edu
Views: 23405 MIT OpenCourseWare
State Space Representation of Transfer Function - Problem 1 - State Space Analysis - Control Systems
 
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Problem 1 on State Space Representation of Transfer Function Video Lecture of Chapter State Space Analysis in Control Systems for EXTC, Instrumentation, Electronics & Electrical Engineering Students. Watch Next Videos of Chapter State Space Analysis:- 1) State Model Representation for Linear System - State Space Analysis - Control Systems - https://www.youtube.com/watch?v=3IC_AaFkVFQ 2) Different Types of Representation of a State Model - State Space Analysis - Control Systems - https://www.youtube.com/watch?v=9MocegdUnZU Watch Next Videos of Chapter State Space Analysis:- 1) State Space Representation of Transfer Function - Problem 2 - State Space Analysis - Control Systems - https://www.youtube.com/watch?v=ZXORobxgegc 2) State Space Representation of Transfer Function - Problem 3 - State Space Analysis - Control Systems - https://www.youtube.com/watch?v=SGWHpym7cO0 Access the complete Playlist of Control Systems:- https://goo.gl/GQrMXf Access the complete Playlist of Chapter State Space Analysis:- http://gg.gg/State-Space-Analysis Subscribe to Ekeeda Channel to access more videos http://gg.gg/Subscribe-Now #ControlSystems #OnlineEngineeringVideoLectures #EngineeringLectures #DegreeEngineeringLectures #ElectricalNetworks #EkeedaOnlineLectures #EkeedaVideoLectures #EkeedaVideoTutorial Thanks For Watching. You can follow and Like us on following social media. Website - http://ekeeda.com Parent Channel - https://www.youtube.com/c/ekeeda Facebook - https://www.facebook.com/ekeeda Twitter - https://twitter.com/Ekeeda_Video LinkedIn- https://www.linkedin.com/company-beta/13222723/ Instgram - https://www.instagram.com/ekeeda_/ Pinterest - https://in.pinterest.com/ekeedavideo You can reach us on [email protected] Happy Learning : )
Views: 1427 Ekeeda
Finding Gain and Time Constant from a Transfer Function Model
 
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Determines the gain and the time constant for a stirred tank bioreactor that is represented by a first-order transfer function. Made by faculty at Lafayette College and produced by the University of Colorado Boulder, Department of Chemical & Biological Engineering. Check out our Process Control playlist: https://www.youtube.com/playlist?list=PL4xAk5aclnUhfXrHhv_ZQfbQ6w6ahwfFQ Are you using a textbook? Check out our website for screencasts organized by popular textbooks: http://www.learncheme.com/screencasts/process-controls Check out our website for interactive Process Control simulations: http://www.learncheme.com/simulations/process-control
Views: 27712 LearnChemE
Process Dynamics and Control Exam Review
 
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This exam covers material on balance equations and modeling, Laplace transforms, transfer functions, 1st order systems, 2nd order systems, and higher order systems. See exam review questions at http://apmonitor.com/che436/index.php/Main/LectureNotes23
Views: 2043 APMonitor.com
Blending Process: State Space
 
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The linear approximate model of the blending process is rewritten in state space form. The dynamic states are the deviations in volume and in mass fraction. The inputs are the flow rates of the inlet and outlet streams. Made by Prof. Martha Grover from the Georgia Institute of Technology and produced by the University of Colorado Boulder, Department of Chemical & Biological Engineering. Check out our Process Control playlist: https://www.youtube.com/playlist?list=PL4xAk5aclnUhfXrHhv_ZQfbQ6w6ahwfFQ Check out our website for screencasts organized by popular textbooks: http://www.learncheme.com/screencasts/process-controls Check out our website for interactive process control simulations: http://www.learncheme.com/simulations/process-control
Views: 1173 LearnChemE
Model based process control design of phosphorus removal - S.C.F. Meijer
 
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Model based process control design of combined biological-chemical phosphorus removal at WWTP Amsterdam West. S.C.F. Meijer, p. piekema, the Netherlands Mr. Sebastiaan (Bas) Meijer is founder and managing director of ASM design. He is a specialist in the field of wastewater treatment and WWTP process design. His particular expertise is model based optimization, design and control of activated sludge processes. During his career as Ph.D. researcher, consultant, trainer, water board engineer and managing director of ASM design, he gained experience of the theoretical, technical, operational and management aspects of wastewater treatment. Since 2002 he is a professional coach and consultant for the Dutch water boards and thereby also trains wastewater engineers. During the past 13 years he has trained hundreds of students and waste water engineers in the field of wastewater engineering and modeling. Since 1998, he teaches as a guest lecturer at the TU Delft and IHE-UNESCO In this conference we will discuss the new developments in IT & Water. These developments are very important for the further evolution of the water sector. IT applications in the water sector cover a broad field of interest. On one hand, IT applications have the ability to integrate the water sector from a high strategic level with connections to security and energy services. on the other hand IT applications have the ability to improve the performance of a single process, or part of a process, by improving the design or control with detailed models. IT applications should lead to better water quality, lower environmental impact and more efficient management, control, monitoring and maintenance of water systems, infrastructure and water treatment processes. Due to fast communication and new ways of personal interaction with stakeholders and customers, IT applications will not only support the water sector in carrying out its primary tasks but also in its communication with customers and stakeholders.
Views: 772 Waternetwerk
Dynamic Models: FOPDT and Fundamental
 
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Dynamic modeling covers fundamental relationships (first principles, physics-based) and data-driven (empirical) approaches. In engineering, there are 4 common balance equations from conservation principles including mass, momentum, energy, and species (see Balance Equations). An alternative to physics-based models is to use input-output data to develop empirical dynamic models such as first-order plus dead time (FOPDT) approximations from a step response. See http://apmonitor.com/pdc/index.php/Main/ExamModeling for a review of mathematical modeling concepts for process dynamics and control.
Views: 870 APMonitor.com
1 - State Space Analysis for Signal Flow Graph Example in Control Engineering by Engineering Funda
 
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In this video, i have explained State Space Analysis Signal Flow Graph Example. For free materials of different engineering subjects use my android application named Engineering Funda with following link: https://play.google.com/store/apps/details?id=com.viaviapp.ENG_Funda Above Android application of Engineering Funda provides following services: 1. Free Materials (GATE exam, Class Notes, Interview questions) 2. Technical Forum 3. Technical discussion 4. Inquiry For more details and inquiry on above topic visit website of Engineering Funda with given link: http://www.engineeringfunda.co.in Engineering Funda channel is all about Engineering and Technology. Here this video is a part of Control Engineering . . . . . . . . . . . . . . . . #Control Engineering, #Control System, #Control System Engineering
Views: 5142 Engineering Funda
Frequency Domain Analysis | Part-1 | Control System |
 
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-~-~~-~~~-~~-~- Please watch: "Phase Margin and Gain Margin | Control System | Gate | IES | BARC| ISRO" https://www.youtube.com/watch?v=QPMwbgB4fro -~-~~-~~~-~~-~-
Views: 19199 Flyhigh Tutorials