AERATOR MIXING STATION

Size: px
Start display at page:

Download "AERATOR MIXING STATION"

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 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 information

University of Tennessee at Chattanooga. Step Response Modeling. Control Systems Laboratory

University 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 information

Proportional-Integral Controller Performance

Proportional-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 information

Using Root Locus Modeling for Proportional Controller Design for Spray Booth Pressure System

Using 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 information

Lab Report 4: Root Locus and Proportional Controller

Lab 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 information

Frequency Response for Flow System

Frequency 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 information

UTC. 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 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 information

Course: ENGR 329 Section: 001 Date: 02/26/2010 Instructor: Dr. Jim M. Henry

Course: 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 information

University of Tennessee at. Chattanooga

University 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 information

Aerator Mixer Speed Control System Step Response Modeling

Aerator 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 information

University 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 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 information

Steady-State and Step Response for the Flow System

Steady-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 information

Steady-State and Step Response for the Flow System

Steady-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 information

Steady State Operating Curve

Steady 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 information

The Discussion of this exercise covers the following points: Angular position control block diagram and fundamentals. Power amplifier 0.

The 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 information

1. 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 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 information

LECTURE FOUR Time Domain Analysis Transient and Steady-State Response Analysis

LECTURE 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 information

Introduction 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 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 information

Steady State Operating Curve

Steady 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 information

CDS 101/110: Lecture 8.2 PID Control

CDS 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 information

CHBE320 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 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 information

PERSONALIZED EXPERIMENTATION IN CLASSICAL CONTROLS WITH MATLAB REAL TIME WINDOWS TARGET AND PORTABLE AEROPENDULUM KIT

PERSONALIZED 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 information

Various Controller Design and Tuning Methods for a First Order Plus Dead Time Process

Various 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 information

Different Controller Terms

Different 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 information

MTE 360 Automatic Control Systems University of Waterloo, Department of Mechanical & Mechatronics Engineering

MTE 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 information

Modeling 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 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 information

Class 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. 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

-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 information

Dr Ian R. Manchester

Dr 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 information

Steady State Operating Curve Voltage Control System

Steady 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 information

Course Outline. Time vs. Freq. Domain Analysis. Frequency Response. Amme 3500 : System Dynamics & Control. Design via Frequency Response

Course 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 information

CHAPTER 6 INTRODUCTION TO SYSTEM IDENTIFICATION

CHAPTER 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 information

EMPIRICAL MODEL IDENTIFICATION AND PID CONTROLLER TUNING FOR A FLOW PROCESS

EMPIRICAL 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 information

Comparative Analysis of Controller Tuning Techniques for Dead Time Processes

Comparative 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 information

Lab 11. Speed Control of a D.C. motor. Motor Characterization

Lab 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 information

PID Tuner (ver. 1.0)

PID 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 information

International Journal of Research in Advent Technology Available Online at:

International 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 information

Design of Model Based PID Controller Tuning for Pressure Process

Design 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 information

Root Locus Design. by Martin Hagan revised by Trevor Eckert 1 OBJECTIVE

Root 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 information

5 Lab 5: Position Control Systems - Week 2

5 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 information

Hands-on Lab. PID Closed-Loop Control

Hands-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 information

ME 375 System Modeling and Analysis

ME 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 information

Controller Algorithms and Tuning

Controller 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 information

Comparative Study of PID Controller tuning methods using ASPEN HYSYS

Comparative 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 information

Experiment 2: Transients and Oscillations in RLC Circuits

Experiment 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 information

MAE106 Laboratory Exercises Lab # 5 - PD Control of DC motor position

MAE106 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 information

Research 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 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 information

LECTURE 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. ( ) = + 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 information

A Feedback Control System for Engineering Technology Laboratory Courses

A 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 information

University of Tennessee at Chattanooga. Stead State Operating Curve Report. Engr 3280L/Week 3. William Disterdick. Brown Team

University 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 information

Lock in time calculation Wenlan Wu (

Lock 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 information

MM7 Practical Issues Using PID Controllers

MM7 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 information

Frequency Response Analysis and Design Tutorial

Frequency 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 information

Electronics and Instrumentation Name ENGR-4220 Fall 1999 Section Modeling the Cantilever Beam Supplemental Info for Project 1.

Electronics 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 information

Lecture 7:Examples using compensators

Lecture 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 information

PROCEEDINGS OF THE SECOND INTERNATIONAL CONFERENCE ON SCIENCE AND ENGINEERING

PROCEEDINGS 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 information

Teaching Mechanical Students to Build and Analyze Motor Controllers

Teaching 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 information

GLOSSARY OF TERMS FOR PROCESS CONTROL

GLOSSARY 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 information

Figure 1: Unity Feedback System. The transfer function of the PID controller looks like the following:

Figure 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 information

Experiment 9. PID Controller

Experiment 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 information

Motor Modeling and Position Control Lab 3 MAE 334

Motor 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 information

Laboratory 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. 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 information

POLYTECHNIC UNIVERSITY Electrical Engineering Department. EE SOPHOMORE LABORATORY Experiment 3 The Oscilloscope

POLYTECHNIC 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 information

Lab #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 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 information

CHAPTER 4 AN EFFICIENT ANFIS BASED SELF TUNING OF PI CONTROLLER FOR CURRENT HARMONIC MITIGATION

CHAPTER 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 information

PHY203: General Physics III Lab page 1 of 5 PCC-Cascade. Lab: AC Circuits

PHY203: 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 information

Closed-loop System, PID Controller

Closed-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 information

Andrea 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, 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 information

Design 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 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 information

The diodes keep the output waveform from getting too large.

The 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 information

JNTUWORLD. 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 *****

JNTUWORLD. 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 information

ENGR-4300 Electronic Instrumentation Quiz 2 Fall 2011 Name Section

ENGR-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 information

ANNA UNIVERSITY :: CHENNAI MODEL QUESTION PAPER(V-SEMESTER) B.E. ELECTRONICS AND COMMUNICATION ENGINEERING EC334 - CONTROL SYSTEMS

ANNA 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 information

COMPARISON OF TUNING METHODS OF PID CONTROLLER USING VARIOUS TUNING TECHNIQUES WITH GENETIC ALGORITHM

COMPARISON 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 information

EEL2216 Control Theory CT2: Frequency Response Analysis

EEL2216 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 information

QuickBuilder PID Reference

QuickBuilder 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 information

Neural Network Predictive Controller for Pressure Control

Neural 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 information

EE 308 Spring Preparation for Final Lab Project Simple Motor Control. Motor Control

EE 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 information

Andrea 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, 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 information

Mechatronics. Analog and Digital Electronics: Studio Exercises 1 & 2

Mechatronics. 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 information

EE 560 Electric Machines and Drives. Autumn 2014 Final Project. Contents

EE 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 information

CONTROL IMPROVEMENT OF UNDER-DAMPED SYSTEMS AND STRUCTURES BY INPUT SHAPING

CONTROL 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 information

TEMPERATURE PROCESS CONTROL MANUAL. Penn State Chemical Engineering

TEMPERATURE 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 information

LAMBDA TUNING TECHNIQUE BASED CONTROLLER DESIGN FOR AN INDUSTRIAL BLENDING PROCESS

LAMBDA 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 information

Exam Signal Detection and Noise

Exam 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 information

Homework Assignment 07

Homework 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 information

4 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 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 information

GE420 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 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 information

COMPUTATION OF STABILIZING PI/PID CONTROLLER FOR LOAD FREQUENCY CONTROL

COMPUTATION 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 information

Addendum 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. 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 information

MEM01: DC-Motor Servomechanism

MEM01: 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 information

Diodes. Sections

Diodes. 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 information

A Discrete Time Model of Boiler Drum and Heat Exchanger QAD Model BDT 921

A 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 information

EC CONTROL SYSTEMS ENGINEERING

EC 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 information

New PID Tuning Rule Using ITAE Criteria

New 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 information

Dr Ian R. Manchester Dr Ian R. Manchester Amme 3500 : Root Locus Design

Dr 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 information

Position Control of DC Motor by Compensating Strategies

Position 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 information

Brushed 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 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 information

Module 08 Controller Designs: Compensators and PIDs

Module 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 information

Dynamic Vibration Absorber

Dynamic 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