ECE 100: Intro to Engineering Design, Presentation No. 11 Daniel E. Rivera Department of Chemical and Materials Engineering Arizona State University ECE.

Slides:



Advertisements
Similar presentations
ERT 210 Process Control & dynamics
Advertisements

Signals and Systems March 25, Summary thus far: software engineering Focused on abstraction and modularity in software engineering. Topics: procedures,
Chapter 4: Basic Properties of Feedback
CHAPTER I INTRODUCTION
Ratio Control Chapter 15.
LECTURE#08 PROCESS CONTROL STRATEGIES
The Distribution Game Modified from the MIT game.
Causal Loop Diagrams Esmaeil Khedmati Morasae Center for Community-Based Participatory Research in Health Tehran University of Medical Sciences January.
THE INTRODUCTION OF AUTOMATIC PROCESS CONTROL
CHE 185 – PROCESS CONTROL AND DYNAMICS
Practical Process Control Using Control Station
Enhanced Single-Loop Control Strategies
Controller Tuning: A Motivational Example
Chapter 11 Simulating Wireless Control. Simulate Parameter – Analog Input Block  The current or digital outputs of these transmitters and switches are.
Production Systems Chapter 9.
Chemical Engineering 3P04 Process Control Tutorial # 2 Learning goals 1.The feedback cause-effect principle 2. Key element in the loop: The control valve.
Open loop vs closed loop By Norbert Benei ZI5A58.
The Water Benders Final Presentations. Outline Introduction Project Description Motivation Problem Statement Objectives Customer Requirements Design Concepts.
Unit 3a Industrial Control Systems
Introduction to Industrial Control Systems
LOGISTICS OPERATION Industrial Logistics (BPT 3123)
Cascade, Ratio, and Feedforward Control
Process Control: Designing Process and Control Systems for Dynamic Performance Chapter 1. Introduction to Process Control Copyright © Thomas Marlin 2013.
Daniel E. Rivera Control Systems Engineering Laboratory Department of Chemical and Materials Engineering Ira A. Fulton School of Engineering Arizona State.
Process Operability Class Materials Copyright © Thomas Marlin 2013
INDUSTRIAL ELECTRONICS CONTROL EET425/4 Lecturers Indra Nisja School of Electrical System Engineering Northern Malaysia University College of Engineering.
Sensor-Based Fast Thermal Evaluation Model For Energy Efficient High-Performance Datacenters Q. Tang, T. Mukherjee, Sandeep K. S. Gupta Department of Computer.
INTRODUCTION TO CONTROL SYSTEMS
Book Adaptive control -astrom and witten mark
Cascade and Ratio Control
PSE and PROCESS CONTROL
Process Control: Designing Process and Control Systems for Dynamic Performance Chapter 7. The Feedback Loop Copyright © Thomas Marlin 2013 The copyright.
Brief Review of Control Theory
Illustrations Course Synopsis Provides a background of control principles in various engineering applications. Basic mathematical tools such as Laplace.
DYNAMIC BEHAVIOR AND STABILITY OF CLOSED-LOOP CONTROL SYSTEMS
BY IRFAN AZHAR Control systems. What Do Mechatronics Engineers Do?
ECE 100: Intro to Engineering Design, Presentation No. 14 Daniel E. Rivera Department of Chemical and Materials Engineering Arizona State University ECE.
What is Control System? To answer this question, we first have to understand what a system is Simon Hui Engineer Control and Informatics, Industrial Centre.
CONTROL ENGINEERING IN DRYING TECHNOLOGY FROM 1979 TO 2005: REVIEW AND TRENDS by: Pascal DUFOUR IDS’06, Budapest, 21-23/08/2006.
Fault Tree Analysis Part 4: Digraph-Based Fault Tree Synthesis Procedure (NFFL and Lapp-Powers Algorithm)
Submitted by Pawan kumar sharma Pgdm 2 nd sem.. Objective of presentation Introduction Definition History Production Types of production Operation Objective.
Industrial Electronic Department Copyright of German Malaysian Institute. All rights reserved.
ERT 210/4 Process Control Hairul Nazirah bt Abdul Halim Office: CHAPTER 8 Feedback.
Lecture 25: Implementation Complicating factors Control design without a model Implementation of control algorithms ME 431, Lecture 25.
Thermal Energy Storage Thermal energy storage (TES) systems heat or cool a storage medium and then use that hot or cold medium for heat transfer at a later.
Demand Management and Customer Service
President UniversityErwin SitompulSMI 1/1 Dr.-Ing. Erwin Sitompul President University Lecture 1 System Modeling and Identification
The first question is really "Why do you need a control system at all?” Consider the following: What good is an airplane if you are a pilot and you.
Lecture 2: Mathematical Modeling Copyright © Thomas Marlin 2013 The copyright holder provides a royalty-free license for use of this material at non-profit.
Name of Student : PATEL ARPITKUMAR RAJNIKANT Enrollment No
Systems Dynamics Dr. Mohammad Kilani Class 1 Introduction.
MISS. RAHIMAH BINTI OTHMAN
Dead Time Compensation (Smith Predictor)
Cascade Control Systems (串级控制系统)
Control Engineering 05/09/2006Control SystemsLecture # 1.
بسم الله الرحمن الرحيم وبه نستعين
ET 438a Automatic Control Systems Technology Lesson 1: Introduction to Control Systems Technology 1 lesson1et438a.pptx.
Author: Nurul Azyyati Sabri
Chapter 1: Overview of Control
Chapter 12. Controlling the Process
Introduction to Control Systems Objectives
Introduction to process control
Course PEF3006 Process Control Fall 2018 Feedforward Control
Sem I 2013/2014 BDU Electromechanical & Control Systems
G1 and G2 are transfer functions and independent of the
Introduction to process control
Process Operability Class Materials Copyright © Thomas Marlin 2013
Course PEF3006 Process Control Fall 2017 Feedforward Control
G1 and G2 are transfer functions and independent of the
Presentation transcript:

ECE 100: Intro to Engineering Design, Presentation No. 11 Daniel E. Rivera Department of Chemical and Materials Engineering Arizona State University ECE 100: Introduction to Engineering Design Understanding Engineering Control Strategies

ECE 100: Intro to Engineering Design, Presentation No. 11 Motivating Philosophy “…it is a redeeming feature of life that we are able to use many things without understanding every detail of them.” L. Ljung, 1987

ECE 100: Intro to Engineering Design, Presentation No. 11 Control Engineering You have been applying engineering control principles throughout your life, even if you have not been fully aware of it. Control engineering is a broadly-applicable field that spans all areas of engineering: –Chemical –Electrical –Mechanical and Aerospace –Civil / Construction –Industrial –Biomedical –Computer Science and Engineering

ECE 100: Intro to Engineering Design, Presentation No. 11 Control Engineering (Cont.) Considers how to manipulate system variables in order to transform dynamic behavior to desirable from undesirable Open-loop: refers to system behavior without a control policy Closed-loop: refers to system behavior once a controller/decision policy is implemented.

ECE 100: Intro to Engineering Design, Presentation No. 11 Control Engineering (Cont.) Many examples of control applications in society: –Cruise control and climate control in automobiles –The “sensor reheat” feature in your microwave oven –Home heating and cooling –The insulin pump for Type-I diabetics –“Fly-by-wire” systems for high-performance jet aircraft –Many, many, more… The development of improved sensors and actuators, coupled with increasing embedded computing capabilities, will continue to facilitate the application of control engineering in many diverse application settings.

ECE 100: Intro to Engineering Design, Presentation No. 11 An Industrial Control Problem QuickTime™ and a BMP decompressor are needed to see this picture. Objective: Use fuel gas flow to keep outlet temperature under control, in spite of occasional yet significant changes in the feed flowrate.

ECE 100: Intro to Engineering Design, Presentation No. 11 The “Shower” Control Problem The presence of delay or “transportation lag” makes this a difficult control problem

ECE 100: Intro to Engineering Design, Presentation No. 11 Definitions Controlled Variable (y): system variable that we wish to keep at a reference value or setpoint (r). Control Error (e=r-y): the difference between the controlled variable and the setpoint; we wish to take this to zero. Manipulated Variable (u): system variable whose adjustment influences the response of the controlled variable; its value is determined by the controller/decision policy. Disturbance Variable (d): system variable that influences the controlled variable response, but cannot be manipulated by the controller; disturbance changes occur external to the system (hence sometimes referred to as exogeneous variables)

ECE 100: Intro to Engineering Design, Presentation No. 11 The “Shower” Control Problem Think about what may constitute controlled, manipulated and disturbance variables in this system Controlled: Temperature, Total Water Flow Manipulated: Hot and Cold Water Handle Positions Disturbances: Inlet Water Flows, Temperatures

ECE 100: Intro to Engineering Design, Presentation No. 11 Feedback and Feedforward Control Strategies In feedback control strategies, a controlled variable (y) is examined and compared to a reference value or setpoint (r). The controller issues actions (decisions on the values of a manipulated variable (u)) on the basis of the discrepancy between y and r. In feedforward control, changes in a disturbance variable (d) are monitored and the manipulated variable (u) is chosen to counteract anticipated changes in y as a result of d.

ECE 100: Intro to Engineering Design, Presentation No. 11 Closed-Loop Feedback Control “Block Diagram” C = Controller P = Process “Transfer Function” Pd = Disturbance “Transfer Function” Controlled: Measured Temperature, Total Water Flow Manipulated: Hot and Cold Water Handle Positions Disturbances: Inlet Water Flows, Temperatures Reference: Desired Temperature, Total Water Flow

ECE 100: Intro to Engineering Design, Presentation No. 11 Shell Westhollow Research Center’s Pumper (a.k.a. Fire Truck)

ECE 100: Intro to Engineering Design, Presentation No. 11 The Front Line Crew

ECE 100: Intro to Engineering Design, Presentation No. 11 “Catching The Plug”

ECE 100: Intro to Engineering Design, Presentation No. 11 For Discussion As a team, review the problem description presented by Dr. Rivera and determine the following: –What are the controlled, manipulated, and disturbance variables in the problem? –What control strategy is best suited to this problem (feedback or feedforward)?

ECE 100: Intro to Engineering Design, Presentation No. 11 Supply Chain “Level” Control Problem LT ORDER DECISIONS Demand Meet demand (with forecast possibly given  f days beforehand) for a node with  day production (or order fulfillment) time and  d delivery time. Do so with the lowest possible cost. CTL

ECE 100: Intro to Engineering Design, Presentation No. 11 Inventory Management Problem Controlled Variable: Candidates include –On-Hand Inventory –Net Stock –Inventory Position –Costs Manipulated Variable: Orders Disturbance Variable: Demand

ECE 100: Intro to Engineering Design, Presentation No. 11 Feedback-Only Control Problem LT CTL Demand In the feedback-only control problem, ordering decisions are calculated based only on perceived changes to “level” (e.g., inventory position or equivalent variable).

ECE 100: Intro to Engineering Design, Presentation No. 11 Closed-Loop Feedback Control “Block Diagram” C = Feedback Controller P = Process “Transfer Function” Pd = Disturbance “Transfer Function” (Demand) (Measured Net Stock Or Inventory Position) (Desired Net Stock Or Inventory Position) (Orders)

ECE 100: Intro to Engineering Design, Presentation No. 11 Combined Feedback/Feedforward Control LT CTL Demand Meet demand (with forecast given  f days beforehand) for a node with  day production (or order fulfillment) time and  d delivery time. Demand Forecast (known  f days beforehand)  order fulfillment time)  d delivery time)

ECE 100: Intro to Engineering Design, Presentation No. 11 Combined Feedback/Feedforward Block Diagram (Orders) (Desired Net Stock Or Inventory Position) (Measured Net Stock Or Inventory Position) (Forecasted Demand) (Unforecasted Demand)

ECE 100: Intro to Engineering Design, Presentation No. 11 In-Class Read and discuss with your team the “Retailer Inventory Dynamics Simulation” handout. Break up into sub-teams and work with a partner to attempt Scenarios 1 – 4. Keep track of the results of your runs and record your observations, as described in the handout. If you have time (or if you do not find Scenarios 1 – 4 challenging enough) give Scenarios 5 – 8 a try. Stay until we have completed an in-class discussion of the results of the exercise (and be willing to perform the “challenge” in front of the rest of the class). Responses to the questions posed in the exercise will be part of Modeling Assignment 3 and Project 1.

ECE 100: Intro to Engineering Design, Presentation No. 11 Modeling Assignment No. 3 Add an engineering-based Proportional-Integral- Derivative (PID) decision policy to your previousl Excel-based simulation that compares the four EOQ strategies. Use your simulation to determine which choice of controlled variable (net stock or inventory position) is “best” suited for this application. Evaluate each policy for a 60-day time period. More details will be provided on Tuesday.

ECE 100: Intro to Engineering Design, Presentation No. 11 Coming Up Tuesday, March 4: Modeling Assignment No. 2 is due; we will begin working on Modeling Assignment No. 3. Thursday, March 6: Continued work on Modeling Assignment No. 3. Class may meet again in ECG 224 – this will be confirmed via .