AERATOR MIXING STATION
|
|
- Aron Hunter
- 5 years ago
- Views:
Transcription
1 AERATOR MIXING STATION Green Team: Marc Labrie Matt Baltimore Michael Newman Michael Sherrit University of Tennessee at Chattanooga April 13, 211 ENGR 328L
2 OVERVIEW System Overview SSOC Analysis Step Response Analysis FOPDT Modeling FOPDT Analysis Sine and Relay Experiments Root Locus model Proportional-only Controller Experiment Proportional Integral Controller Design Conclusions
3 SCHEMATIC AND BLOCK DIAGRAM OF THE SYSTEM Speed Controller Speed Recording Controller Speed Transmitter
4 EXPERIMENTAL DATA ANALYSIS 75 rpm 6 rpm 75+/- 12 rpm
5 STEADY STATE OPERATING CURVE Operating Ranges -25% lower 25-5% lower mid 5-75% upper mid 75-1% upper
6 CONCLUSION Linear in the operating range of -1% corresponding to an output of -174RPM Small uncertainty
7 STEP RESPONSE EXPERIMENTAL DATA UP
8 STEP RESPONSE DATA UP CONTINUED To=.1sec (Black Lines) Tau=.4s (Green Lines)
9 RESULTS
10 CONTINUED.12 Step Response Dead Time, t (Dead Time).1.8 Time (s) %-25% Up %-25% Down 25%-5% Up 25%-5% Down 5%-75% Up 5%-75%Down 75%-1% Up 75%-1% Down
11 CONTINUED
12 Step Response 5% to 95% Output(RPM) Input Value(%) Output (%) Input (%) Dc = 1549 RPM Dm = 9 K= 17.2 RPM/% t =.1 s τ =.7 s MWN 4/17/ Time (s)
13 Step Response 95% to 5% MWN 4/17/11 Output(RPM) Input Value(%) Output (RPM) Dc = 1545 RPM Dm = 9 K= 17.2 RPM/% t =.1 s τ =.6 s Input (%) Time (s)
14 FOPDT THEORY FOPDT Transfer Function For step functions the Manipulated variable m(t) and the Output c(t) are:
15 Model Output
16 Step Response Model 5%-95% Output(RPM) 9 14 Output (Model) 8 12 Input Value(%) 7 Output (RPM) MWN 4/17/11 Input (Model) K= 17.3 RPM/% t =.1 s τ =.7 s Input (%) Time (s)
17 Step Response Model 5% to 95% MWN 4/17/ Output (%) K= 17.4 RPM/% t =.1 s τ =.6 s Input (%) 6 4 Output(RPM) Output (Model) Input Value(%) 1 Input (Model) Time (s)
18 Gain, K (RPM/%) Up Experimental Up Model Down Experimental Down Model K (RPM/%) % 25-5% 5-75% 75-1% 5%-95% Input
19 Dead Time, to(sec) Up Experimental Up Model Down Experimental Down Model K (RPM/%) % 25-5% 5-75% 75-1% 5%-95% Input
20 Time Constant, τ(sec) Up Experimental Up Model Down Experimental Down Model K (RPM/%) % 25-5% 5-75% 75-1% Input
21 CONCLUSIONS K and t from the model and graphical method closely agreed while there was a larger difference in tau for the two methods.
22 SINE RESPONSE Power Input Speed (RPM)
23 Frequency Response (f=.5 Hz) 13 8 Output (RPM) Ar = ±.3 PA = -38 ± Time (s) Output(RPM) Input Value(%) MWN 3/1/ Input (%)
24 Amplitude Ratio % range AR A Frequency (Hz) Frequency (Hz) PA (degrees) MSS 2/27/211 K = 17.1 RPM/% τ =.15 s t =.17 s fu = 3.4 Hz Kcu =.37 %/RPM Order = 2 Phase Angle MSS 2/26/211
25 Amplitude Ratio.1.1 Frequency (Hz) 1 1 MWN MSS 1 Experimental (5%-74%) Model (5%-74%) Experimental (75%-99%) 1 Amplitude Ratio Model (75%-99%).1.1 Frequency (Hz) 1 1 MWN MSS Phase Angle Experimental (5%-74%) Model (5%-74%) Experimental (75%-99%) Model (75%-99%) 75-1% range K= 17.1 RPM/% t=.8s tau=.17s 5-75% range K= 17.3 RPM/% t=.9s tau=.16s Phase Angle
26 Gain, K (RPM/%) Experimental Model K (RPM/%) % - 74% 75% - 99% Input (%)
27 Dead Time, t (s) Experimental Model t (s) % - 74% 75% - 99% Input (%)
28 Time Constant, τ (s).2 Experimental Model.15 Tau (s).1.5 5% - 74% 75% - 99% Input (%)
29 SINE WAVE.1HZ sine output 5% baseline 45% amplitude 18 1 output rpm Output(RPM) Input Value(%) input% Sine wave of whole axis experimental model K to.1.13 ta u time
30 5-1% Relay Response Trial Input (%) Output (RPM) Time (s)
31 2 K (RPM/%) K (RPM/%) Frequency Response Relay Response
32 .5 Tau, τ (sec) Tau (s) Frequency Response Relay Response
33 .12 Dead Time, to (sec).1.8 t (sec) Frequency Response Relay Response
34 CONCLUSION Overall, the frequency experiment more closely agrees with what was found for K, t, and tau in previous experiments than those from the relay experiment.
35 TRANSFER FUNCTION The transfer function for an FOPDT system is After substituting Pade s approximation and simplifying, the transfer function becomes
36 TRANSFER FUNCTION (CONT D) The transfer function for a proportional feedback controller is For an FOPDT system with proportional control, the OLTF is And the characteristic equation becomes 1 + OLTF =
37 ROOT LOCUS MODEL 5-75% 4 MWN 3/27/11 Kc 1/1 Kc 1/4 3 2 K cu IMAGINARY AXIS Kcd Kc 1/ Kcu=.26 %/RPM Kc 1/4 =.17 %/RPM Kc 1/1 =.13 %/RPM Kc 1/5 =.36 %/RPM Kcd=.17 %/RPM REAL AXIS
38 KCU COMPARISON Kcu (%/RPM) MSS 3/27/11 Root locus Relay Frequency -25% 25-5% 5-75% 75-1%
39 FU COMPARISON Fu (Hz) Root locus Relay Frequency MSS 3/27/ % 25-5% 5-75% 75-1%
40 SYSTEM CONTROLLER RANGE GREEN TEAM ROOT LOCUS PLOT MWN 3/27/11 Kc 1/1 Kc 1/ K cu IMAGINARY AXIS Kc 1/ Under damped Region Kcd -1 Over-damped Region Kcu =.28 %/RPM Kc 1/4 =.18 %/RPM Kc 1/1 =.14 %/RPM Kc 1/5 =.61 %/RPM Kcd =.18 %/RPM REAL AXIS
41 CONTROLLER GAIN EXPERIMENT FOR THE ULTIMATE GAIN Experimental Kcu MSS Output (RPM) Set-P=165RPM M bar=95% Step=-25RPM AR=.52 Offset=34RPM Overshoot=6.% Settling time=n/a Kc=.3%/RPM Output(RPM) SET-P(RPM) Input Value(%) 6 4 Input (%) OFFSET Time (s)
42 CONTROLLER GAIN EXPERIMENT FOR ¼ DECAY Experimental 1/4 Decay Set-P=165RPM M bar=95% Step=-25RPM MSS Output (RPM) AR=.24 Offset=6RPM Overshoot=3.8% Settling time=1.2s Kc=.16%/RPM Output(RPM) SET-P(RPM) Input Value(%) Input (%) 144 OFFSET Time (s)
43 CONTROLLER GAIN EXPERIMENT FOR 1/1 DECAY Exeperimental 1/1 Decay Set-P=165RPM M bar=95% Step=-25RPM MSS Output (RPM) AR=.6 Offset=82RPM Overshoot=1.7% Settling time=1s Kc=.1%/RPM OFFSET Output(RPM) SET-P(RPM) Input Value(%) Input (%) Time (s)
44 CONTROLLER GAIN EXPERIMENT FOR 1/5 DECAY Experimental 1/5 Decay MSS Output (RPM) Set-P=165RPM M bar=95% Step=-25RPM Offset=11RPM Overshoot=.48% Settling time=.5s Kc=.7%/RPM Output(RPM) SET-P(RPM) Input Value(%) OFFSET Input (%) Time (s)
45 CONTROLLER GAIN EXPERIMENT FOR CRITICAL DAMPING Experimental Kcd Set-P=165RPM M bar=95% Step=-25RPM MSS Output (RPM) Offset=165RPM Overshoot=% Settling time=.5s Kc=.2%/RPM OFFSET Output(RPM) SET-P(RPM) Input Value(%) Input (%) Time (s)
46 -25% REGION EXPERIMENT Decay for 12.5% and 1 rpm step up output rom 2 15 Output(RPM) 15 1 input % 1 SET-P(RPM) 5 Input Value(%) ML Team Green team Kc=.5 Step up= 1rpm time
47 KC=.1
48 KC RESULTS AND COMPARISON Kcu =.28 %/RPM Kc 1/4 =.18 %/RPM Kc 1/1 =.14 %/RPM Kc 1/5 =.61 %/RPM Kcd =.18 %/RPM
49 Kcu Across All Regions AR=.5 Offset = 113RPM Overshoot= 8% Settling time=n/a Kc=.29%/RPM Output (RPM) 1 8 MWN 4/17/11 6 Input (%) Input Value(%) Time (s) Kcu=.28 %/RPM Set Pt = 345 RPM Step = 12 RPM Output(RPM) SET-P(RPM) 2
50 PROPORTIONAL INTEGRAL CONTROLLER
51 τ I = 3.33t Tau I =.3 (5%-75%) REAL Kqd =.16 Kcu =.24 3 Kcd =.22 K5 =.55 K1 =.12 fu = 4. Hz IMAGINARY MWN 4/16/11 K = 17.4 RPM/% τ =.16 s t =.9 s -2-3
52 Tau I = 1 (5%-75%) REAL MWN 4/16/11 Kcd.18 K5 =.52 K = 17.4 RPM/% τ =.16 s t =.9 s K1 =.13 Kqd =.17 Kcu =.25 fu = 4.3 Hz IMAGINARY
53 Tau I =.7 (5%-75%) REAL K5 =.12 Kcd =.7 MWN 4/16/11 K1 =.36 Kqd =.57 Kcu =.11 fu = 2.4 Hz IMAGINARY
54 Lower τ I Values %-25% (Tau I =.8) 25%-5% (Tau I =.83) 5%-75% (Tau I =.7) 75%-1% (Tau I =.68).12.1 %/RPM Kcd Kc5 Kc1 Kqd Kcu
55 Middle τ I Values.3.25 %-25% (Tau I =.3) 25%-5% (Tau I =.33) 5%-75% (Tau I =.3) 75%-1% (Tau I =.27).2 %/RPM Kcd Kc5 Kc1 Kqd Kcu
56 Large τ I Values.35.3 %-25% (Tau I = 1.3) 25%-5% (Tau I = 1.3) 5%-75% (Tau I = 1) 75%-1% (Tau I = 1.8).25.2 %/RPM Kcd Kc5 Kc1 Kqd Kcu
57 CONCLUSIONS The SSOC shows a linear correlation between input power and speed. The operating range of the system is -1% corresponding to an output range of -174 RPM. The gain (K) of the system calculated is equal to the slope of the SSOC and experimental vs. model results match closely.
58 CONCLUSIONS CONTINUED From the experimental Bode plot the order is 2. The sine response model shows the best estimate of the FOPDT parameters Best FOPDT Estimate K (RPM/%) 17.3 τ (sec).2 t (sec).1
59 CONCLUSIONS CONTINUED The Kcu of about.3 %/RPM from the Root Locus model agreed with what was found from previous experiments. The ultimate frequency (Fu) from the Root Locus model did not agree with what was found from previous experiments. Experimental results allow for controller gain recommendations to customers. Recommended Controller Gains and corresponding Tau I values found in the table below. Response Tau I =.8 Tau I =.3 Tau I = 1 Value Value Symbol (%/rpm) Response Symbol (%/rpm) Response Symbol Value (%/rpm) Critical Kcd.6 Critical Kcd.28 Critical Kcd.21 1/5 Kc5.13 1/5 Kc5.6 1/5 Kc5.58 1/1 Kc1.41 1/1 Kc1.13 1/1 Kc1.14 1/4 Kqd.63 1/4 Kqd.17 1/4 Kqd.19 Ultimate Kcu.126 Ultimate Kcu.25 Ultimate Kcu.27
60 WHAT WE CAN GIVE THE CUSTOMER WITH A PROPORTIONAL-INTEGRAL CONTROLLER Quarter Decay: Kc=.17 %/RPM, Tau I = Output (RPM) Input (%) MWN 4/18/11 Output(RPM) SET-P(RPM) Input Value(%) Time (s)
61 ASSUMPTION No offset Least reset windup Fastest to reach set point Least oscillation
62 PI Controller Set Pt. = 11 RPM ΔSet Pt. = 25 RPM Tau I =.3 s Kc =.55 %/RPM K5 From P Controller MWN 4/22/ Output (RPM) Input (%) Output(RPM) SET-P(RPM) Input Value(%) Axis Title
63 ALL REGIONS INCLUDED Optimized Proportional Integral Controller Output(RPM) SET-P(RPM) Input Value(%) output rpm ML Team Green Kc=.55 TI=.3 Set point = 1 to innput % Time (s)
64 CONCLUSIONS Proportional Integral controller has best output curve PI has no offset Best values for Proportional TI=.3 or higher Kc=.55 %/rpm Kc is for 1/5 th decay in proportional and acts with little overshoot
AERATOR MIXING STATION
AERATOR MIXING STATION Steady State, Step Response Analysis, Sine and Relay Analysis, Root Locus Green Team: Marc Labrie Matt Baltimore Michael Newman Michael Sherrit University of Tennessee at Chattanooga
More informationUniversity of Tennessee at Chattanooga. Step Response Modeling. Control Systems Laboratory
University of Tennessee at Chattanooga Step Response Modeling Control Systems Laboratory By Stephen Rue Tan Team (Stephanie Raulston, Stefan Hanley) Course: ENGR 3280L Section: 000 Date: 03/06/2013 Instructor:
More informationProportional-Integral Controller Performance
Proportional-Integral Controller Performance Silver Team Jonathan Briere ENGR 329 Dr. Henry 4/1/21 Silver Team Members: Jordan Buecker Jonathan Briere John Colvin 1. Introduction Modeling for the response
More informationUsing Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System
1 University of Tennessee at Chattanooga Engineering 3280L Using Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System By: 2 Introduction: The objectives for these experiments
More informationLab Report 4: Root Locus and Proportional Controller
Lab Report 4: Root Locus and Proportional Controller University of Tennessee at Chattanooga Engineering 32 Blue Team Kevin Schrumpf Justin Anchanattu Justin Rehagen April 1, 212 Introduction The first
More informationFrequency Response for Flow System
Frequency Response for Flow System Report By: Ben Gordon Red Squad: Ben Klinger, Dianah Dugan UTC, Engineering 329 October 7, 2007 Introduction The objective of this experiment is to observe the output
More informationUTC. Engineering 329. Frequency Response for the Flow System. Gold Team. By: Blake Nida. Partners: Roger Lemond and Stuart Rymer
UTC Engineering 329 Frequency Response for the Flow System Gold Team By: Blake Nida Partners: Roger Lemond and Stuart Rymer March 9, 2007 Introduction: The purpose of the frequency response experiments
More informationCourse: ENGR 329 Section: 001 Date: 02/26/2010 Instructor: Dr. Jim M. Henry
1 University of Tennessee at Chattanooga Filter Wash Stations, Both Valves Closed Steady State Operating Curve Engineering 329 By Timmy Collins Lilac Team Tim Garner, Walt Mandrel and You Gao Course: ENGR
More informationUniversity of Tennessee at. Chattanooga
University of Tennessee at Chattanooga Step Response Engineering 329 By Gold Team: Jason Price Jered Swartz Simon Ionashku 2-3- 2 INTRODUCTION: The purpose of the experiments was to investigate and understand
More informationAerator Mixer Speed Control System Step Response Modeling
UTC Engineering 3280L Matthew Addison Green Team (Michael Hansen) 9/4/12 Aerator Mixer Speed Control System Step Response Modeling Introduction In this experiment a program that models the aerator mixing
More informationUniversity of Tennessee at Chattanooga. Steady State and Step Response. By: Alex Bedley. Engineering 3280L. Buff. (Alexander Hudson, Ashley Poe)
University of Tennessee at Chattanooga Steady State and Step Response By: Alex Bedley Engineering 328L Buff (Alexander Hudson, Ashley Poe) February 1, 13 Introduction In the past two experiments, we were
More informationSteady-State and Step Response for the Flow System
Steady-State and Step Response for the Flow System Report By: Dianah Dugan Red Squad: Ben Klinger, Ben Gordon UTC, Engineering 329 September 19, 2007 Introduction: The objectives of this experiment are
More informationSteady-State and Step Response for the Flow System
Steady-State and Step Response for the Flow System Report By: Dianah Dugan Red Squad: Ben Klinger, Ben Gordon UTC, Engineering 329 September 19, 2007 Introduction: The objectives of this experiment are
More informationSteady State Operating Curve
Steady State Operating Curve By Lanze Berry University of Tennessee at Chattanooga Engineering 3280L Blue Team (Khanh Nguyen, Justin Cartwright) Course: ENGR 3280L Section: 001 Date: September 4, 2012
More informationThe Discussion of this exercise covers the following points: Angular position control block diagram and fundamentals. Power amplifier 0.
Exercise 6 Motor Shaft Angular Position Control EXERCISE OBJECTIVE When you have completed this exercise, you will be able to associate the pulses generated by a position sensing incremental encoder with
More information1. Consider the closed loop system shown in the figure below. Select the appropriate option to implement the system shown in dotted lines using
1. Consider the closed loop system shown in the figure below. Select the appropriate option to implement the system shown in dotted lines using op-amps a. b. c. d. Solution: b) Explanation: The dotted
More informationLECTURE FOUR Time Domain Analysis Transient and Steady-State Response Analysis
LECTURE FOUR Time Domain Analysis Transient and Steady-State Response Analysis 4.1 Transient Response and Steady-State Response The time response of a control system consists of two parts: the transient
More informationIntroduction to Signals and Systems Lecture #9 - Frequency Response. Guillaume Drion Academic year
Introduction to Signals and Systems Lecture #9 - Frequency Response Guillaume Drion Academic year 2017-2018 1 Transmission of complex exponentials through LTI systems Continuous case: LTI system where
More informationSteady State Operating Curve
1 Steady State Operating Curve University of Tennessee at Chattanooga Engineering 3280L Instructor: Dr. Jim Henry By: Fuchsia Team: Jonathan Brewster, Jonathan Wooten Date: February 1, 2013 2 Introduction
More informationCDS 101/110: Lecture 8.2 PID Control
CDS 11/11: Lecture 8.2 PID Control November 16, 216 Goals: Nyquist Example Introduce and review PID control. Show how to use loop shaping using PID to achieve a performance specification Discuss the use
More informationCHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING. Professor Dae Ryook Yang
CHBE320 LECTURE XI CONTROLLER DESIGN AND PID CONTOLLER TUNING Professor Dae Ryook Yang Spring 2018 Dept. of Chemical and Biological Engineering 11-1 Road Map of the Lecture XI Controller Design and PID
More informationPERSONALIZED EXPERIMENTATION IN CLASSICAL CONTROLS WITH MATLAB REAL TIME WINDOWS TARGET AND PORTABLE AEROPENDULUM KIT
Eniko T. Enikov, University of Arizona Estelle Eke, California State University Sacramento PERSONALIZED EXPERIMENTATION IN CLASSICAL CONTROLS WITH MATLAB REAL TIME WINDOWS TARGET AND PORTABLE AEROPENDULUM
More informationVarious Controller Design and Tuning Methods for a First Order Plus Dead Time Process
International Journal of Computer Science & Communication Vol. 1, No. 2, July-December 2010, pp. 161-165 Various Controller Design and Tuning Methods for a First Order Plus Dead Time Process Pradeep Kumar
More informationDifferent Controller Terms
Loop Tuning Lab Challenges Not all PID controllers are the same. They don t all use the same units for P-I-and D. There are different types of processes. There are different final element types. There
More informationMTE 360 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering
MTE 36 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering Laboratory #1: Introduction to Control Engineering In this laboratory, you will become familiar
More informationModeling and Analysis of Systems Lecture #9 - Frequency Response. Guillaume Drion Academic year
Modeling and Analysis of Systems Lecture #9 - Frequency Response Guillaume Drion Academic year 2015-2016 1 Outline Frequency response of LTI systems Bode plots Bandwidth and time-constant 1st order and
More informationClass 5. Competency Exam Round 1. The Process Designer s Process. Process Control Preliminaries. On/Off Control The Simplest Controller
Class 5 Competency Exam Round 1 Proportional Control Starts Friday, September 17 Ends Friday, October 1 Process Control Preliminaries The final control element, process and sensor/transmitter all have
More information-binary sensors and actuators (such as an on/off controller) are generally more reliable and less expensive
Process controls are necessary for designing safe and productive plants. A variety of process controls are used to manipulate processes, however the most simple and often most effective is the PID controller.
More informationDr Ian R. Manchester
Week Content Notes 1 Introduction 2 Frequency Domain Modelling 3 Transient Performance and the s-plane 4 Block Diagrams 5 Feedback System Characteristics Assign 1 Due 6 Root Locus 7 Root Locus 2 Assign
More informationSteady State Operating Curve Voltage Control System
UTC Engineering 39 Steady State Operating Curve Voltage Control System Michael Edge Partners: Michael Woolery Nathan Holland September 5, 7 Introduction A steady state operating curve was created to show
More informationCourse Outline. Time vs. Freq. Domain Analysis. Frequency Response. Amme 3500 : System Dynamics & Control. Design via Frequency Response
Course Outline Amme 35 : System Dynamics & Control Design via Frequency Response Week Date Content Assignment Notes Mar Introduction 2 8 Mar Frequency Domain Modelling 3 5 Mar Transient Performance and
More informationCHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION
CHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION Broadly speaking, system identification is the art and science of using measurements obtained from a system to characterize the system. The characterization
More informationEMPIRICAL MODEL IDENTIFICATION AND PID CONTROLLER TUNING FOR A FLOW PROCESS
Volume 118 No. 20 2018, 2015-2021 ISSN: 1311-8080 (printed version); ISSN: 1314-3395 (on-line version) url: http://www.ijpam.eu ijpam.eu EMPIRICAL MODEL IDENTIFICATION AND PID CONTROLLER TUNING FOR A FLOW
More informationComparative Analysis of Controller Tuning Techniques for Dead Time Processes
Comparative Analysis of Controller Tuning Techniques for Dead Time Processes Parvesh Saini *, Charu Sharma Department of Electrical Engineering Graphic Era Deemed to be University, Dehradun, Uttarakhand,
More informationLab 11. Speed Control of a D.C. motor. Motor Characterization
Lab 11. Speed Control of a D.C. motor Motor Characterization Motor Speed Control Project 1. Generate PWM waveform 2. Amplify the waveform to drive the motor 3. Measure motor speed 4. Estimate motor parameters
More informationPID Tuner (ver. 1.0)
PID Tuner (ver. 1.0) Product Help Czech Technical University in Prague Faculty of Mechanical Engineering Department of Instrumentation and Control Engineering This product was developed within the subject
More informationInternational Journal of Research in Advent Technology Available Online at:
OVERVIEW OF DIFFERENT APPROACHES OF PID CONTROLLER TUNING Manju Kurien 1, Alka Prayagkar 2, Vaishali Rajeshirke 3 1 IS Department 2 IE Department 3 EV DEpartment VES Polytechnic, Chembur,Mumbai 1 manjulibu@gmail.com
More informationDesign of Model Based PID Controller Tuning for Pressure Process
ISSN (Print) : 3 3765 Design of Model Based PID Controller Tuning for Pressure Process A.Kanchana 1, G.Lavanya, R.Nivethidha 3, S.Subasree 4, P.Aravind 5 UG student, Dept. of ICE, Saranathan College Engineering,
More informationRoot Locus Design. by Martin Hagan revised by Trevor Eckert 1 OBJECTIVE
TAKE HOME LABS OKLAHOMA STATE UNIVERSITY Root Locus Design by Martin Hagan revised by Trevor Eckert 1 OBJECTIVE The objective of this experiment is to design a feedback control system for a motor positioning
More information5 Lab 5: Position Control Systems - Week 2
5 Lab 5: Position Control Systems - Week 2 5.7 Introduction In this lab, you will convert the DC motor to an electromechanical positioning actuator by properly designing and implementing a proportional
More informationHands-on Lab. PID Closed-Loop Control
Hands-on Lab PID Closed-Loop Control Adding feedback improves performance. Unity feedback was examined to serve as a motivating example. Lectures derived the power of adding proportional, integral and
More informationME 375 System Modeling and Analysis
ME 375 System Modeling and Analysis G(s) H(s) Section 9 Block Diagrams and Feedback Control Spring 2009 School of Mechanical Engineering Douglas E. Adams Associate Professor 9.1 Key Points to Remember
More informationController Algorithms and Tuning
The previous sections of this module described the purpose of control, defined individual elements within control loops, and demonstrated the symbology used to represent those elements in an engineering
More informationComparative Study of PID Controller tuning methods using ASPEN HYSYS
Comparative Study of PID Controller tuning methods using ASPEN HYSYS Bhavatharini S #1, Abirami S #2, Arun Prem Anand N #3 # Department of Chemical Engineering, Sri Venkateswara College of Engineering
More informationExperiment 2: Transients and Oscillations in RLC Circuits
Experiment 2: Transients and Oscillations in RLC Circuits Will Chemelewski Partner: Brian Enders TA: Nielsen See laboratory book #1 pages 5-7, data taken September 1, 2009 September 7, 2009 Abstract Transient
More informationMAE106 Laboratory Exercises Lab # 5 - PD Control of DC motor position
MAE106 Laboratory Exercises Lab # 5 - PD Control of DC motor position University of California, Irvine Department of Mechanical and Aerospace Engineering Goals Understand how to implement and tune a PD
More informationResearch Article 12 Control of the Fractionator Top Pressure for a Delayed Coking Unit in Khartoum Refinery
Research Article 12 Control of the Fractionator Top Pressure for a Delayed Coking Unit in Khartoum Refinery Salah Eldeen F..Hegazi 1, Gurashi Abdallah Gasmelseed 2, Mohammed M.Bukhari 3 1 Department of
More informationLECTURE 2: PD, PID, and Feedback Compensation. ( ) = + We consider various settings for Zc when compensating the system with the following RL:
LECTURE 2: PD, PID, and Feedback Compensation. 2.1 Ideal Derivative Compensation (PD) Generally, we want to speed up the transient response (decrease Ts and Tp). If we are lucky then a system s desired
More informationA Feedback Control System for Engineering Technology Laboratory Courses
Session 359 A Feedback Control System for Engineering Technology Laboratory Courses J. W. Somerville, N. F. Macia Department of Electronics and Computer Technology, Arizona State University East Abstract
More informationUniversity of Tennessee at Chattanooga. Stead State Operating Curve Report. Engr 3280L/Week 3. William Disterdick. Brown Team
1 University of Tennessee at Chattanooga Stead State Operating Curve Report Engr 3280L/Week 3 By Brown Team (Trent, William, William) 09/05/2012 2 Introduction: In this laboratory, a percentage of power
More informationLock in time calculation Wenlan Wu (
Lock in time calculation Wenlan Wu (http://cmosedu.com/jbaker/students/wenlan/wenlan.htm) Figure 1 Charge pump PLL block diagram First, for the above feedback system, we can get the loop gain and transfer
More informationMM7 Practical Issues Using PID Controllers
MM7 Practical Issues Using PID Controllers Readings: FC textbook: Section 4.2.7 Integrator Antiwindup p.196-200 Extra reading: Hou Ming s lecture notes p.60-69 Extra reading: M.J. Willis notes on PID controler
More informationFrequency Response Analysis and Design Tutorial
1 of 13 1/11/2011 5:43 PM Frequency Response Analysis and Design Tutorial I. Bode plots [ Gain and phase margin Bandwidth frequency Closed loop response ] II. The Nyquist diagram [ Closed loop stability
More informationElectronics and Instrumentation Name ENGR-4220 Fall 1999 Section Modeling the Cantilever Beam Supplemental Info for Project 1.
Name ENGR-40 Fall 1999 Section Modeling the Cantilever Beam Supplemental Info for Project 1 The cantilever beam has a simple equation of motion. If we assume that the mass is located at the end of the
More informationLecture 7:Examples using compensators
Lecture :Examples using compensators Venkata Sonti Department of Mechanical Engineering Indian Institute of Science Bangalore, India, This draft: March, 8 Example :Spring Mass Damper with step input Consider
More informationPROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SCIENCE AND ENGINEERING
POCEEDINGS OF THE SECOND INTENATIONAL CONFEENCE ON SCIENCE AND ENGINEEING Organized by Ministry of Science and Technology DECEMBE -, SEDONA HOTEL, YANGON, MYANMA Design and Analysis of PID Controller for
More informationTeaching Mechanical Students to Build and Analyze Motor Controllers
Teaching Mechanical Students to Build and Analyze Motor Controllers Hugh Jack, Associate Professor Padnos School of Engineering Grand Valley State University Grand Rapids, MI email: jackh@gvsu.edu Session
More informationGLOSSARY OF TERMS FOR PROCESS CONTROL
Y1900SS-1a 1 GLOSSARY OF TERMS FOR PROCESS CONTROL Accuracy Conformity of an indicated value to an accepted standard value, or true value. Accuracy, Reference A number or quantity which defines the limit
More informationFigure 1: Unity Feedback System. The transfer function of the PID controller looks like the following:
Islamic University of Gaza Faculty of Engineering Electrical Engineering department Control Systems Design Lab Eng. Mohammed S. Jouda Eng. Ola M. Skeik Experiment 3 PID Controller Overview This experiment
More informationExperiment 9. PID Controller
Experiment 9 PID Controller Objective: - To be familiar with PID controller. - Noting how changing PID controller parameter effect on system response. Theory: The basic function of a controller is to execute
More informationMotor Modeling and Position Control Lab 3 MAE 334
Motor ing and Position Control Lab 3 MAE 334 Evan Coleman April, 23 Spring 23 Section L9 Executive Summary The purpose of this experiment was to observe and analyze the open loop response of a DC servo
More informationLaboratory PID Tuning Based On Frequency Response Analysis. 2. be able to evaluate system performance for empirical tuning method;
Laboratory PID Tuning Based On Frequency Response Analysis Objectives: At the end, student should 1. appreciate a systematic way of tuning PID loop by the use of process frequency response analysis; 2.
More informationPOLYTECHNIC UNIVERSITY Electrical Engineering Department. EE SOPHOMORE LABORATORY Experiment 3 The Oscilloscope
POLYTECHNIC UNIVERSITY Electrical Engineering Department EE SOPHOMORE LABORATORY Experiment 3 The Oscilloscope Modified for Physics 18, Brooklyn College I. Overview of the Experiment The main objective
More informationLab #2: Electrical Measurements II AC Circuits and Capacitors, Inductors, Oscillators and Filters
Lab #2: Electrical Measurements II AC Circuits and Capacitors, Inductors, Oscillators and Filters Goal: In circuits with a time-varying voltage, the relationship between current and voltage is more complicated
More informationCHAPTER 4 AN EFFICIENT ANFIS BASED SELF TUNING OF PI CONTROLLER FOR CURRENT HARMONIC MITIGATION
92 CHAPTER 4 AN EFFICIENT ANFIS BASED SELF TUNING OF PI CONTROLLER FOR CURRENT HARMONIC MITIGATION 4.1 OVERVIEW OF PI CONTROLLER Proportional Integral (PI) controllers have been developed due to the unique
More informationPHY203: General Physics III Lab page 1 of 5 PCC-Cascade. Lab: AC Circuits
PHY203: General Physics III Lab page 1 of 5 Lab: AC Circuits OBJECTIVES: EQUIPMENT: Universal Breadboard (Archer 276-169) 2 Simpson Digital Multimeters (464) Function Generator (Global Specialties 2001)*
More informationClosed-loop System, PID Controller
Closed-loop System, PID Controller M. Fikar Department of Information Engineering and Process Control Institute of Information Engineering, Automation and Mathematics FCFT STU in Bratislava TAR MF (IRP)
More informationAndrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Spring Semester, Linear control systems design
Andrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL Andrea M. Zanchettin, PhD Spring Semester, 2018 Linear control systems design Andrea Zanchettin Automatic Control 2 The control problem Let s introduce
More informationDesign of a Simulink-Based Control Workstation for Mobile Wheeled Vehicles with Variable-Velocity Differential Motor Drives
Design of a Simulink-Based Control Workstation for Mobile Wheeled Vehicles with Variable-Velocity Differential Motor Drives Kevin Block, Timothy De Pasion, Benjamin Roos, Alexander Schmidt Gary Dempsey
More informationThe diodes keep the output waveform from getting too large.
Wien Bridge Oscillat CIRCUIT: The Wien bridge oscillat, see Fig., consists of two voltage dividers. It oscillates (approximately) sinusoidally at the frequency that produces the same voltage out of both
More informationJNTUWORLD. 6 The unity feedback system whose open loop transfer function is given by G(s)=K/s(s 2 +6s+10) Determine: (i) Angles of asymptotes *****
Code: 9A050 III B. Tech I Semester (R09) Regular Eaminations, November 0 Time: hours Ma Marks: 70 (a) What is a mathematical model of a physical system? Eplain briefly. (b) Write the differential equations
More informationENGR-4300 Electronic Instrumentation Quiz 2 Fall 2011 Name Section
ENGR-43 Quiz 2 Fall 211 ENGR-43 Electronic Instrumentation Quiz 2 Fall 211 Name Section Question I (2 points) Question II (2 points) Question III (2 points) Question I (2 points) Question (2 points) Total
More informationANNA UNIVERSITY :: CHENNAI MODEL QUESTION PAPER(V-SEMESTER) B.E. ELECTRONICS AND COMMUNICATION ENGINEERING EC334 - CONTROL SYSTEMS
ANNA UNIVERSITY :: CHENNAI - 600 025 MODEL QUESTION PAPER(V-SEMESTER) B.E. ELECTRONICS AND COMMUNICATION ENGINEERING EC334 - CONTROL SYSTEMS Time: 3hrs Max Marks: 100 Answer all Questions PART - A (10
More informationCOMPARISON OF TUNING METHODS OF PID CONTROLLER USING VARIOUS TUNING TECHNIQUES WITH GENETIC ALGORITHM
JOURNAL OF ELECTRICAL ENGINEERING & TECHNOLOGY Journal of Electrical Engineering & Technology (JEET) (JEET) ISSN 2347-422X (Print), ISSN JEET I A E M E ISSN 2347-422X (Print) ISSN 2347-4238 (Online) Volume
More informationEEL2216 Control Theory CT2: Frequency Response Analysis
EEL2216 Control Theory CT2: Frequency Response Analysis 1. Objectives (i) To analyse the frequency response of a system using Bode plot. (ii) To design a suitable controller to meet frequency domain and
More informationQuickBuilder PID Reference
QuickBuilder PID Reference Doc. No. 951-530031-006 2010 Control Technology Corp. 25 South Street Hopkinton, MA 01748 Phone: 508.435.9595 Fax: 508.435.2373 Thursday, March 18, 2010 2 QuickBuilder PID Reference
More informationNeural Network Predictive Controller for Pressure Control
Neural Network Predictive Controller for Pressure Control ZAZILAH MAY 1, MUHAMMAD HANIF AMARAN 2 Department of Electrical and Electronics Engineering Universiti Teknologi PETRONAS Bandar Seri Iskandar,
More informationEE 308 Spring Preparation for Final Lab Project Simple Motor Control. Motor Control
Preparation for Final Lab Project Simple Motor Control Motor Control A proportional integral derivative controller (PID controller) is a generic control loop feedback mechanism (controller) widely used
More informationAndrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL. Andrea M. Zanchettin, PhD Winter Semester, Linear control systems design Part 1
Andrea Zanchettin Automatic Control 1 AUTOMATIC CONTROL Andrea M. Zanchettin, PhD Winter Semester, 2018 Linear control systems design Part 1 Andrea Zanchettin Automatic Control 2 Step responses Assume
More informationMechatronics. Analog and Digital Electronics: Studio Exercises 1 & 2
Mechatronics Analog and Digital Electronics: Studio Exercises 1 & 2 There is an electronics revolution taking place in the industrialized world. Electronics pervades all activities. Perhaps the most important
More informationEE 560 Electric Machines and Drives. Autumn 2014 Final Project. Contents
EE 560 Electric Machines and Drives. Autumn 2014 Final Project Page 1 of 53 Prof. N. Nagel December 8, 2014 Brian Howard Contents Introduction 2 Induction Motor Simulation 3 Current Regulated Induction
More informationCONTROL IMPROVEMENT OF UNDER-DAMPED SYSTEMS AND STRUCTURES BY INPUT SHAPING
CONTROL IMPROVEMENT OF UNDER-DAMPED SYSTEMS AND STRUCTURES BY INPUT SHAPING Igor Arolovich a, Grigory Agranovich b Ariel University of Samaria a igor.arolovich@outlook.com, b agr@ariel.ac.il Abstract -
More informationTEMPERATURE PROCESS CONTROL MANUAL. Penn State Chemical Engineering
TEMPERATURE PROCESS CONTROL MANUAL Penn State Chemical Engineering Revised Summer 2015 Contents LEARNING OBJECTIVES... 3 EXPERIMENTAL OBJECTIVES AND OVERVIEW... 3 Pre-lab study:... 3 Experiments in the
More informationLAMBDA TUNING TECHNIQUE BASED CONTROLLER DESIGN FOR AN INDUSTRIAL BLENDING PROCESS
ISSN : 0973-7391 Vol. 3, No. 1, January-June 2012, pp. 143-146 LAMBDA TUNING TECHNIQUE BASED CONTROLLER DESIGN FOR AN INDUSTRIAL BLENDING PROCESS Manik 1, P. K. Juneja 2, A K Ray 3 and Sandeep Sunori 4
More informationExam Signal Detection and Noise
Exam Signal Detection and Noise Tuesday 27 January 2015 from 14:00 until 17:00 Lecturer: Sense Jan van der Molen Important: It is not allowed to use a calculator. Complete each question on a separate piece
More informationHomework Assignment 07
Homework Assignment 07 Question 1 (Short Takes). 2 points each unless otherwise noted. 1. A single-pole op-amp has an open-loop low-frequency gain of A = 10 5 and an open loop, 3-dB frequency of 4 Hz.
More information4 Experiment 4: DC Motor Voltage to Speed Transfer Function Estimation by Step Response and Frequency Response (Part 2)
4 Experiment 4: DC Motor Voltage to Speed Transfer Function Estimation by Step Response and Frequency Response (Part 2) 4.1 Introduction This lab introduces new methods for estimating the transfer function
More informationGE420 Laboratory Assignment 8 Positioning Control of a Motor Using PD, PID, and Hybrid Control
GE420 Laboratory Assignment 8 Positioning Control of a Motor Using PD, PID, and Hybrid Control Goals for this Lab Assignment: 1. Design a PD discrete control algorithm to allow the closed-loop combination
More informationCOMPUTATION OF STABILIZING PI/PID CONTROLLER FOR LOAD FREQUENCY CONTROL
COMPUTATION OF STABILIZING PI/PID CONTROLLER FOR LOAD FREQUENCY CONTROL 1 B. AMARENDRA REDDY, 2 CH. V. V. S. BHASKARA REDDY, 3 G. THEJESWARI 1 Asst. Professor, 2 Asso. Professor, 3 M.E. Student, Dept.
More informationAddendum Handout for the ECE3510 Project. The magnetic levitation system that is provided for this lab is a non-linear system.
Addendum Handout for the ECE3510 Project The magnetic levitation system that is provided for this lab is a non-linear system. Because of this fact, it should be noted that the associated ideal linear responses
More informationMEM01: DC-Motor Servomechanism
MEM01: DC-Motor Servomechanism Interdisciplinary Automatic Controls Laboratory - ME/ECE/CHE 389 February 5, 2016 Contents 1 Introduction and Goals 1 2 Description 2 3 Modeling 2 4 Lab Objective 5 5 Model
More informationDiodes. Sections
iodes Sections 3.3.1 3.3.8 1 Modeling iode Characteristics Exponential model nonlinearity makes circuit analysis difficult. Two common approaches are graphical analysis and iterative analysis For simple
More informationA Discrete Time Model of Boiler Drum and Heat Exchanger QAD Model BDT 921
International onference on Instrumentation, ontrol & Automation IA009 October 0-, 009, Bandung, Indonesia A Discrete Time Model of Boiler Drum and Heat Exchanger QAD Model BDT 91 Tatang Mulyana *, Mohd
More informationEC CONTROL SYSTEMS ENGINEERING
1 YEAR / SEM: II / IV EC 1256. CONTROL SYSTEMS ENGINEERING UNIT I CONTROL SYSTEM MODELING PART-A 1. Define open loop and closed loop systems. 2. Define signal flow graph. 3. List the force-voltage analogous
More informationNew PID Tuning Rule Using ITAE Criteria
New PID Tuning Rule Using ITAE Criteria Ala Eldin Abdallah Awouda Department of Mechatronics and Robotics, Faculty of Electrical Engineering, Universiti Teknologi Malaysia, Johor, 83100, Malaysia rosbi@fke.utm.my
More informationDr Ian R. Manchester Dr Ian R. Manchester Amme 3500 : Root Locus Design
Week Content Notes 1 Introduction 2 Frequency Domain Modelling 3 Transient Performance and the s-plane 4 Block Diagrams 5 Feedback System Characteristics Assign 1 Due 6 Root Locus 7 Root Locus 2 Assign
More informationPosition Control of DC Motor by Compensating Strategies
Position Control of DC Motor by Compensating Strategies S Prem Kumar 1 J V Pavan Chand 1 B Pangedaiah 1 1. Assistant professor of Laki Reddy Balireddy College Of Engineering, Mylavaram Abstract - As the
More informationBrushed DC Motor Microcontroller PWM Speed Control with Optical Encoder and H-Bridge
Brushed DC Motor Microcontroller PWM Speed Control with Optical Encoder and H-Bridge L298 Full H-Bridge HEF4071B OR Gate Brushed DC Motor with Optical Encoder & Load Inertia Flyback Diodes Arduino Microcontroller
More informationModule 08 Controller Designs: Compensators and PIDs
Module 08 Controller Designs: Compensators and PIDs Ahmad F. Taha EE 3413: Analysis and Desgin of Control Systems Email: ahmad.taha@utsa.edu Webpage: http://engineering.utsa.edu/ taha March 31, 2016 Ahmad
More informationDynamic Vibration Absorber
Part 1B Experimental Engineering Integrated Coursework Location: DPO Experiment A1 (Short) Dynamic Vibration Absorber Please bring your mechanics data book and your results from first year experiment 7
More information