Feedback Control of Linear SISO systems. Process Dynamics and Control

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Feedback Control of Linear SISO systems. Process Dynamics and Control"

Transcription

1 Feedback Control of Linear SISO systems Process Dynamics and Control 1

2 Open-Loop Process The study of dynamics was limited to open-loop systems Observe process behavior as a result of specific input signals 2

3 Closed-Loop System In study and design of control systems, we are concerned with the dynamic behavior of a controlled or Closed-loop Systems Feedback Control System 3

4 Feedback Control Control is meant to provide regulation of process outputs about a reference,, despite inherent disturbances Controller System Feedback Control System The deviation of the plant output,,from its intended reference is used to make appropriate adjustments in the plant input, 4

5 Feedback Control Process is a combination of sensors and actuators Controller is a computer (or operator) that performs the required manipulations Computer Actuator Process Sensor e.g. Classical one degree-of-freedom feedback control loop 5

6 Block Diagram of Closed-Loop Process Closed-Loop Transfer Function Computer Actuator Process Sensor - Open-Loop Process Transfer Function - Controller Transfer Function - Sensor Transfer Function - Actuator Transfer Function 6

7 Closed-Loop Transfer Function For analysis, we assume that the impact of actuator and sensor dynamics are negligible Closed-loop process reduces to the block diagram: Feedback Control System 7

8 Closed-loop Transfer Functions The closed-loop process has Two inputs The reference signal The disturbance signal Two outputs The manipulated (control) variable signal The output (controlled) variable signal We want to see how the inputs affect the outputs Transfer functions relating, and, 8

9 Closed-loop Transfer function There are four basic transfer functions They arise from three so-called sensitivity functions Highlights the dilemma of control system design Only one degree of freedom to shape the three sensitivity functions 9

10 Closed-loop Transfer Functions Sensitivity functions: The sensitivity function: The complementary sensitivity function: The control sensitivity function: 10

11 Closed-loop Transfer Functions Overall transfer function for the output: SERVO RESPONSE REGULATORY RESPONSE Servo response is the response of the output to setpoint change Regulatory response is the response of the output to disturbance changes 11

12 Closed-loop Transfer Functions Servo mechanism requires that: Regulatory response requires that: Since The two objectives are complementary 12

13 Closed-loop Transfer Functions Note that or requires that the controller is large This leads to large control sensitivity 13

14 PID Controller Most widespread choice for the controller is the PID controller The acronym PID stands for: P - Proportional I - Integral D - Derivative PID Controllers: greater than 90% of all control implementations dates back to the 1930s very well studied and understood optimal structure for first and second order processes (given some assumptions) always first choice when designing a control system 14

15 PID Control PID Control Equation Proportional Action Derivative Action Integral Action Controller Bias PID Controller Parameters K c Proportional gain Integral Time Constant Derivative Time Constant Controller Bias 15

16 PID Control PID Controller Transfer Function or: Note: numerator of PID transfer function cancels second order dynamics denominator provides integration to remove possibility of steady-state errors 16

17 PID Control Controller Transfer Function: or, Note: Many variations of this controller exist Easily implemented in MATLAB/SIMULINK each mode (or action) of controller is better studied individually 17

18 Proportional Feedback Form: Transfer function: or, Closed-loop form: 18

19 Proportional Feedback Example: Given first order process: for P-only feedback closed-loop dynamics: Closed-Loop Time Constant 19

20 Proportional Feedback Final response: Note: for zero offset response we require Tracking Error Disturbance rejection Possible to eliminate offset with P-only feedback (requires infinite controller gain) Need different control action to eliminate offset (integral) 20

21 Proportional Feedback Servo dynamics of a first order process under proportional feedback increasing controller gain eliminates off-set 21

22 High-order process e.g. second order underdamped process Proportional Feedback increasing controller gain reduces offset, speeds response and increases oscillation 22

23 Proportional Feedback Important points: proportional feedback does not change the order of the system started with a first order process closed-loop process also first order order of characteristic polynomial is invariant under proportional feedback speed of response of closed-loop process is directly affected by controller gain increasing controller gain reduces the closed-loop time constant in general, proportional feedback reduces (does not eliminate) offset speeds up response for oscillatory processes, makes closed-loop process more oscillatory 23

24 Integral Control Integrator is included to eliminate offset provides reset action usually added to a proportional controller to produce a PI controller PID controller with derivative action turned off PI is the most widely used controller in industry optimal structure for first order processes PI controller form Transfer function model 24

25 PI Feedback Closed-loop response more complex expression degree of denominator is increased by one Assuming the closed-loop system is stable, we get 25

26 PI Feedback Example PI control of a first order process Closed-loop transfer function Note: offset is removed closed-loop is second order 26

27 PI Feedback Example (contd) effect of integral time constant and controller gain on closed-loop dynamics (time constant) natural period of oscillation damping coefficient integral time constant and controller gain can induce oscillation and change the period of oscillation 27

28 Effect of integral time constant on servo dynamics PI Feedback Small integral time constant induces oscillatory (underdamped) closed-loop response 28

29 PI Feedback Effect of controller gain on servo dynamics affects speed of response increasing gain eliminates offset quicker 29

30 Effect of integral action of regulatory response PI Feedback reducing integral time constant removes effect of disturbances makes behavior more oscillatory 30

31 PI Feedback Important points: integral action increases order of the system in closed-loop PI controller has two tuning parameters that can independently affect speed of response final response (offset) integral action eliminates offset integral action should be small compared to proportional action tuned to slowly eliminate offset can increase or cause oscillation can be de-stabilizing 31

32 Derivative of error signal Used to compensate for trends in output measure of speed of error signal change provides predictive or anticipatory action Derivative Action P and I modes only response to past and current errors Derivative mode has the form if error is increasing, decrease control action if error is decreasing, decrease control action Usually implemented in PID form 32

33 PID Feedback Transfer Function Closed-loop Transfer Function Slightly more complicated than PI form 33

34 PID Feedback Example: PID Control of a first order process Closed-loop transfer function 34

35 PID Feedback Effect of derivative action on servo dynamics Increasing derivative action leads to a more sluggish servo response 35

36 PID Feedback Effect of derivative action on regulatory response increasing derivative action reduces impact of disturbances on controlled variable slows down servo response and affects oscillation of process 36

37 PD Feedback PD Controller Proportional Derivative Control is common in mechanical systems Arise in application for systems with an integrating behaviour Example : System in series with an integrator 37

38 PD Feedback Transfer Function Closed-loop Transfer Function Slightly more complicated than PI form 38

39 PD Feedback DC Motor example: In terms of angular velocity (velocity control) In terms of the angle (position control) 39

40 PD Feedback Closed-loop transfer function Simplifying Notice that Same effect as a PID controller. 40

41 Derivative Action Important Points: Characteristic polynomial is similar to PI derivative action does not increase the order of the system adding derivative action affects the period of oscillation of the process good for disturbance rejection poor for tracking the PID controller has three tuning parameters and can independently affect, speed of response final response (offset) servo and regulatory response derivative action should be small compared to integral action has a stabilizing influence difficult to use for noisy signals usually modified in practical implementation 41

42 Closed-loop Stability Every control problem involves a consideration of closed-loop stability General concepts: Bounded Input Bounded Output (BIBO) Stability: An (unconstrained) linear system is said to be stable if the output response is bounded for all bounded inputs. Otherwise it is unstable. Comments: Stability is much easier to prove than instability This is just one type of stability 42

43 Closed-loop Stability Closed-loop dynamics Let then, The closed-loop transfer functions have a common denominator called the characteristic polynomial 43

44 Closed-loop stability General Stability criterion: A closed-loop feedback control system is stable if and only if all roots of the characteristic polynomial are negative or have negative real parts. Otherwise, the system is unstable. Unstable region is the right half plane of the complex plane. Valid for any linear systems. 44

45 Closed-loop Stability Problem reduces to finding roots of a polynomial (for polynomial systems, without delay) Easy (1990s) way : MATLAB function ROOTS (or POLE) Traditional: 1. Routh array: Test for positivity of roots of a polynomial 2. Direct substitution Complex axis separates stable and unstable regions Find controller gain that yields purely complex roots 3. Root locus diagram Vary location of poles as controller gain is varied Of limited use 45

46 Closed-loop stability Routh array for a polynomial equation is where Elements of left column must be positive to have roots with negative real parts 46

47 Example: Routh Array Characteristic polynomial Polynomial Coefficients Routh Array 2. 36s s 4! 0. 58s s s = 0 a5 = 2. 36, a4 = 149., a3 =! 0. 58, a2 = 121., a1 = 0. 42, a0 = a5( 2. 36) a3(! 0. 58) a1( 0. 42) a4( 149. ) a2( 121. ) a0( 0. 78) b1 (! 2. 50) b2 (! 0. 82) b3( 0) c1( 0. 72) c2 ( 0. 78) d1( 189. ) d2( 0) e1( 0. 78) Closed-loop system is unstable 47

48 Direct Substitution Technique to find gain value that de-stabilizes the system. Observation: Process becomes unstable when poles appear on right half plane Find value of that yields purely complex poles Strategy: Start with characteristic polynomial Write characteristic equation: Substitute for complex pole Solve for and 48

49 Example: Direct Substitution Characteristic equation Substitution for Real Part Complex Part System is unstable if 49

50 Root Locus Diagram Old method that consists in plotting poles of characteristic polynomial as controller gain is changed e.g. Characteristic polynomial 50

51 Stability and Performance Given plant model, we assume a stable closed-loop system can be designed Once stability is achieved - need to consider performance of closedloop process - stability is not enough All poles of closed-loop transfer function have negative real parts - can we place these poles to get a good performance S C Space of all Controllers P S: Stabilizing Controllers for a given plant P: Controllers that meet performance 51

52 Controller Tuning Can be achieved by Direct synthesis : Specify servo transfer function required and calculate required controller - assume plant = model Internal Model Control: Morari et al. (86) Similar to direct synthesis except that plant and plant model are concerned Pole placement Tuning relations: Cohen-Coon - 1/4 decay ratio designs based on ISE, IAE and ITAE Frequency response techniques Bode criterion Nyquist criterion Field tuning and re-tuning 52

53 Direct Synthesis From closed-loop transfer function Isolate For a desired trajectory and plant model, controller is given by not necessarily PID form inverse of process model to yield pole-zero cancellation (often inexact because of process approximation) used with care with unstable process or processes with RHP zeroes 53

54 Direct Synthesis 1. Perfect Control cannot be achieved, requires infinite gain 2. Closed-loop process with finite settling time For 1st order open-loop process, For 2nd order open-loop process,, it leads to PI control, get PID control 3. Processes with delay requires again, 1st order leads to PI control 2nd order leads to PID control 54

55 IMC Controller Tuning Closed-loop transfer function In terms of implemented controller, G c 55

56 1. Process model factored into two parts IMC Controller Tuning where to 1. contains dead-time and RHP zeros, steady-state gain scaled 2. Controller where is the IMC filter The constant is chosen such the IMC controller is proper based on pole-zero cancellation 56

57 Example PID Design using IMC and Direct synthesis for the process Process parameters: 1. Direct Synthesis: (Taylor Series) (Padé) Servo Transfer function 57

58 Example 1. IMC Tuning: a) Taylor Series: Filter Controller (PI) b) Padé approximation: Filter Controller (Commercial PID) 58

59 Example Servo Response 59

60 Example Regulatory response 60

61 IMC Tuning For unstable processes, Must modify IMC filter such that the value of at is 1 Usual modification Strategy is to specify and solve for such that 61

62 Example Consider the process Consider the filter Let then solve for Yields a PI controller 62

63 Example Servo response 63

64 Pole placement Given a process model a controller of the form, and an arbitrary polynomial Under what condition does there exist a unique controller pair and such that 64

65 We say that and any common factors Pole placement are prime if they do not have Result: Assume that and are (co) prime. Let be an arbitraty polynomial of degree. Then there exist polynomials and of degree such that 65

66 Pole Placement Example This is a second order system The polynomials and are prime The required degree of the characteristic polynomial is The degree of the controller polynomial and are Controller is given by 66

67 Pole Placement Performance objective: 3rd order polynomial Characteristic polynomial is given by Solving for and coefficients on both sides by equating polynomial Obtain a system of 4 equations in 4 unknowns 67

68 Pole Placement System of equations Solution is Corresponding controller is a PI controller 68

69 Tuning Relations Process reaction curve method: based on approximation of process using first order plus delay model 1. Step in U is introduced 2. Observe behavior 3. Fit a first order plus dead time model Manual Control 69

70 Tuning Relations Process response Obtain tuning from tuning correlations Ziegler-Nichols Cohen-Coon ISE, IAE or ITAE optimal tuning relations 70

71 Ziegler-Nichols Tunings Controller P-only PI PID - Note presence of inverse of process gain in controller gain - Introduction of integral action requires reduction in controller gain - Increase gain when derivation action is introduced Example: PI: PID: 71

72 Example Ziegler-Nichols Tunings: Servo response 72

73 Example Regulatory Response Z-N tuning Oscillatory with considerable overshoot Tends to be conservative 73

74 Cohen-Coon Tuning Relations Designed to achieve 1/4 decay ratio fast decrease in amplitude of oscillation Controller K c T i T d P-only ( 1/ )(! /" )[1 + " / 3! ] PI K p ( 1/ )(! /" )[0.9 + " /12! ] K p "[30 + 3( " /!)] ( " /! ) PID (1/ K p 3" + 16! )(! /" )[ ] 12! "[32 + 6( " /! )] ( " /! ) 4" 11+ 2( " /! ) Example: PI: K c =10.27 τ I =18.54 PID: K c =15.64 τ I =19.75 τ d =

75 Tuning relations Cohen-Coon: Servo More aggressive/ Higher controller gains Undesirable response for most cases 75

76 Tuning Relations Cohen-Coon: Regulatory Highly oscillatory Very aggressive 76

77 Integral Error Relations 1. Integral of absolute error (IAE) IAE " =! e ( t ) dt 0 2. Integral of squared error (ISE) penalizes large errors 3. Integral of time-weighted absolute error (ITAE) penalizes errors that persist ITAE is most conservative ITAE is preferred " ISE =! e ( t ) 2 dt 0 ITAE " =! t e ( t ) dt 0 77

78 ITAE Relations Choose K c, τ I and τ d that minimize the ITAE: For a first order plus dead time model, solve for:! ITAE! ITAE! ITAE = 0, = 0, = 0! Kc!" I!" d Design for Load and Setpoint changes yield different ITAE optimum Type of Type of Mode A B Input Controller Load PI P I Load PID P I D Set point PI P I Set point PID P I D

79 ITAE Relations From table, we get Load Settings: ( ) B Y = A! = KK d c = " " " " = I " Setpoint Settings: B " d ( ) c ", ( ) Y = A! = KK = " " = A + B! " I " Example 79

80 ITAE Relations Example (contd) Setpoint Settings Kc Load Settings: Kc ( )! KKc = = = K = = ( )! KKc = = = = = K 0. 3 ( ) ( )!! = " I 30 = !! I = = = ! d! = 0 308( ) = ! d = ! = ! "! = I 30 = !! I = = = ! d! = 0 381( ) = ! d = ! =

81 ITAE Relations Servo Response design for load changes yields large overshoots for set-point changes 81

82 ITAE Relations Regulatory response 82

83 Tuning Relations In all correlations, controller gain should be inversely proportional to process gain Controller gain is reduced when derivative action is introduced Controller gain is reduced as increases! " Integral time constant and derivative constant should increase as increases In general, Ziegler-Nichols and Cohen-Coon tuning relations yield aggressive control with oscillatory response (requires detuning)! d! I = ITAE provides conservative performance (not aggressive)! " 83

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

Ch 14: Feedback Control systems

Ch 14: Feedback Control systems Ch 4: Feedback Control systems Part IV A is concerned with sinle loop control The followin topics are covered in chapter 4: The concept of feedback control Block diaram development Classical feedback controllers

More information

Open Loop Tuning Rules

Open Loop Tuning Rules Open Loop Tuning Rules Based on approximate process models Process Reaction Curve: The process reaction curve is an approximate model of the process, assuming the process behaves as a first order plus

More information

CHAPTER 3 TUNING METHODS OF CONTROLLER

CHAPTER 3 TUNING METHODS OF CONTROLLER 57 CHAPTER 3 TUNING METHODS OF CONTROLLER 3.1 INTRODUCTION This chapter deals with a simple method of designing PI and PID controllers for first order plus time delay with integrator systems (FOPTDI).

More information

CM 3310 Process Control, Spring Lecture 21

CM 3310 Process Control, Spring Lecture 21 CM 331 Process Control, Spring 217 Instructor: Dr. om Co Lecture 21 (Back to Process Control opics ) General Control Configurations and Schemes. a) Basic Single-Input/Single-Output (SISO) Feedback Figure

More information

STABILITY OF CLOSED-LOOP CONTOL SYSTEMS

STABILITY OF CLOSED-LOOP CONTOL SYSTEMS CHBE320 LECTURE X STABILITY OF CLOSED-LOOP CONTOL SYSTEMS Professor Dae Ryook Yang Spring 2018 Dept. of Chemical and Biological Engineering 10-1 Road Map of the Lecture X Stability of closed-loop control

More information

Video 5.1 Vijay Kumar and Ani Hsieh

Video 5.1 Vijay Kumar and Ani Hsieh Video 5.1 Vijay Kumar and Ani Hsieh Robo3x-1.1 1 The Purpose of Control Input/Stimulus/ Disturbance System or Plant Output/ Response Understand the Black Box Evaluate the Performance Change the Behavior

More information

Index. INDEX_p /15/02 3:08 PM Page 765

Index. INDEX_p /15/02 3:08 PM Page 765 INDEX_p.765-770 11/15/02 3:08 PM Page 765 Index N A Adaptive control, 144 Adiabatic reactors, 465 Algorithm, control, 5 All-pass factorization, 257 All-pass, frequency response, 225 Amplitude, 216 Amplitude

More information

Lecture 5 Classical Control Overview III. Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore

Lecture 5 Classical Control Overview III. Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore Lecture 5 Classical Control Overview III Dr. Radhakant Padhi Asst. Professor Dept. of Aerospace Engineering Indian Institute of Science - Bangalore A Fundamental Problem in Control Systems Poles of open

More information

1 An Overview and Brief History of Feedback Control 1. 2 Dynamic Models 23. Contents. Preface. xiii

1 An Overview and Brief History of Feedback Control 1. 2 Dynamic Models 23. Contents. Preface. xiii Contents 1 An Overview and Brief History of Feedback Control 1 A Perspective on Feedback Control 1 Chapter Overview 2 1.1 A Simple Feedback System 3 1.2 A First Analysis of Feedback 6 1.3 Feedback System

More information

(b) A unity feedback system is characterized by the transfer function. Design a suitable compensator to meet the following specifications:

(b) A unity feedback system is characterized by the transfer function. Design a suitable compensator to meet the following specifications: 1. (a) The open loop transfer function of a unity feedback control system is given by G(S) = K/S(1+0.1S)(1+S) (i) Determine the value of K so that the resonance peak M r of the system is equal to 1.4.

More information

A Tuning of the Nonlinear PI Controller and Its Experimental Application

A Tuning of the Nonlinear PI Controller and Its Experimental Application Korean J. Chem. Eng., 18(4), 451-455 (2001) A Tuning of the Nonlinear PI Controller and Its Experimental Application Doe Gyoon Koo*, Jietae Lee*, Dong Kwon Lee**, Chonghun Han**, Lyu Sung Gyu, Jae Hak

More information

Analysis and Design of Control Systems in the Time Domain

Analysis and Design of Control Systems in the Time Domain Chapter 6 Analysis and Design of Control Systems in the Time Domain 6. Concepts of feedback control Given a system, we can classify it as an open loop or a closed loop depends on the usage of the feedback.

More information

Additional Closed-Loop Frequency Response Material (Second edition, Chapter 14)

Additional Closed-Loop Frequency Response Material (Second edition, Chapter 14) Appendix J Additional Closed-Loop Frequency Response Material (Second edition, Chapter 4) APPENDIX CONTENTS J. Closed-Loop Behavior J.2 Bode Stability Criterion J.3 Nyquist Stability Criterion J.4 Gain

More information

Laboratory Exercise 1 DC servo

Laboratory Exercise 1 DC servo Laboratory Exercise DC servo Per-Olof Källén ø 0,8 POWER SAT. OVL.RESET POS.RESET Moment Reference ø 0,5 ø 0,5 ø 0,5 ø 0,65 ø 0,65 Int ø 0,8 ø 0,8 Σ k Js + d ø 0,8 s ø 0 8 Off Off ø 0,8 Ext. Int. + x0,

More information

Chapter 5 The SIMC Method for Smooth PID Controller Tuning

Chapter 5 The SIMC Method for Smooth PID Controller Tuning Chapter 5 The SIMC Method for Smooth PID Controller Tuning Sigurd Skogestad and Chriss Grimholt 5.1 Introduction Although the proportional-integral-derivative (PID) controller has only three parameters,

More information

Linear State Feedback Controller Design

Linear State Feedback Controller Design Assignment For EE5101 - Linear Systems Sem I AY2010/2011 Linear State Feedback Controller Design Phang Swee King A0033585A Email: king@nus.edu.sg NGS/ECE Dept. Faculty of Engineering National University

More information

Contents. PART I METHODS AND CONCEPTS 2. Transfer Function Approach Frequency Domain Representations... 42

Contents. PART I METHODS AND CONCEPTS 2. Transfer Function Approach Frequency Domain Representations... 42 Contents Preface.............................................. xiii 1. Introduction......................................... 1 1.1 Continuous and Discrete Control Systems................. 4 1.2 Open-Loop

More information

CHAPTER 10: STABILITY &TUNING

CHAPTER 10: STABILITY &TUNING When I complete this chapter, I want to be able to do the following. Determine the stability of a process without control Determine the stability of a closed-loop feedback control system Use these approaches

More information

Ian G. Horn, Jeffery R. Arulandu, Christopher J. Gombas, Jeremy G. VanAntwerp, and Richard D. Braatz*

Ian G. Horn, Jeffery R. Arulandu, Christopher J. Gombas, Jeremy G. VanAntwerp, and Richard D. Braatz* Ind. Eng. Chem. Res. 996, 35, 3437-344 3437 PROCESS DESIGN AND CONTROL Improved Filter Design in Internal Model Control Ian G. Horn, Jeffery R. Arulandu, Christopher J. Gombas, Jeremy G. VanAntwerp, and

More information

CHAPTER 6 CLOSED LOOP STUDIES

CHAPTER 6 CLOSED LOOP STUDIES 180 CHAPTER 6 CLOSED LOOP STUDIES Improvement of closed-loop performance needs proper tuning of controller parameters that requires process model structure and the estimation of respective parameters which

More information

Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control

Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control Plan of the Lecture Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control Goal: understand the difference between open-loop and closed-loop (feedback)

More information

Lecture 12. Upcoming labs: Final Exam on 12/21/2015 (Monday)10:30-12:30

Lecture 12. Upcoming labs: Final Exam on 12/21/2015 (Monday)10:30-12:30 289 Upcoming labs: Lecture 12 Lab 20: Internal model control (finish up) Lab 22: Force or Torque control experiments [Integrative] (2-3 sessions) Final Exam on 12/21/2015 (Monday)10:30-12:30 Today: Recap

More information

Plan of the Lecture. Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control

Plan of the Lecture. Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control Plan of the Lecture Review: stability; Routh Hurwitz criterion Today s topic: basic properties and benefits of feedback control Plan of the Lecture Review: stability; Routh Hurwitz criterion Today s topic:

More information

Tuning of Internal Model Control Proportional Integral Derivative Controller for Optimized Control

Tuning of Internal Model Control Proportional Integral Derivative Controller for Optimized Control Tuning of Internal Model Control Proportional Integral Derivative Controller for Optimized Control Thesis submitted in partial fulfilment of the requirement for the award of Degree of MASTER OF ENGINEERING

More information

IC6501 CONTROL SYSTEMS

IC6501 CONTROL SYSTEMS DHANALAKSHMI COLLEGE OF ENGINEERING CHENNAI DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING YEAR/SEMESTER: II/IV IC6501 CONTROL SYSTEMS UNIT I SYSTEMS AND THEIR REPRESENTATION 1. What is the mathematical

More information

Cascade Control of a Continuous Stirred Tank Reactor (CSTR)

Cascade Control of a Continuous Stirred Tank Reactor (CSTR) Journal of Applied and Industrial Sciences, 213, 1 (4): 16-23, ISSN: 2328-4595 (PRINT), ISSN: 2328-469 (ONLINE) Research Article Cascade Control of a Continuous Stirred Tank Reactor (CSTR) 16 A. O. Ahmed

More information

EE 422G - Signals and Systems Laboratory

EE 422G - Signals and Systems Laboratory EE 4G - Signals and Systems Laboratory Lab 9 PID Control Kevin D. Donohue Department of Electrical and Computer Engineering University of Kentucky Lexington, KY 40506 April, 04 Objectives: Identify the

More information

Index Accumulation, 53 Accuracy: numerical integration, sensor, 383, Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709,

Index Accumulation, 53 Accuracy: numerical integration, sensor, 383, Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709, Accumulation, 53 Accuracy: numerical integration, 83-84 sensor, 383, 772-773 Adaptive tuning: expert system, 528 gain scheduling, 518, 529, 709, 715 input conversion, 519 reasons for, 512-517 relay auto-tuning,

More information

6.1 Sketch the z-domain root locus and find the critical gain for the following systems K., the closed-loop characteristic equation is K + z 0.

6.1 Sketch the z-domain root locus and find the critical gain for the following systems K., the closed-loop characteristic equation is K + z 0. 6. Sketch the z-domain root locus and find the critical gain for the following systems K (i) Gz () z 4. (ii) Gz K () ( z+ 9. )( z 9. ) (iii) Gz () Kz ( z. )( z ) (iv) Gz () Kz ( + 9. ) ( z. )( z 8. ) (i)

More information

Chapter 2. Classical Control System Design. Dutch Institute of Systems and Control

Chapter 2. Classical Control System Design. Dutch Institute of Systems and Control Chapter 2 Classical Control System Design Overview Ch. 2. 2. Classical control system design Introduction Introduction Steady-state Steady-state errors errors Type Type k k systems systems Integral Integral

More information

ECSE 4962 Control Systems Design. A Brief Tutorial on Control Design

ECSE 4962 Control Systems Design. A Brief Tutorial on Control Design ECSE 4962 Control Systems Design A Brief Tutorial on Control Design Instructor: Professor John T. Wen TA: Ben Potsaid http://www.cat.rpi.edu/~wen/ecse4962s04/ Don t Wait Until The Last Minute! You got

More information

10/8/2015. Control Design. Pole-placement by state-space methods. Process to be controlled. State controller

10/8/2015. Control Design. Pole-placement by state-space methods. Process to be controlled. State controller Pole-placement by state-space methods Control Design To be considered in controller design * Compensate the effect of load disturbances * Reduce the effect of measurement noise * Setpoint following (target

More information

Research Article. World Journal of Engineering Research and Technology WJERT.

Research Article. World Journal of Engineering Research and Technology WJERT. wjert, 2015, Vol. 1, Issue 1, 27-36 Research Article ISSN 2454-695X WJERT www.wjert.org COMPENSATOR TUNING FOR DISTURBANCE REJECTION ASSOCIATED WITH DELAYED DOUBLE INTEGRATING PROCESSES, PART I: FEEDBACK

More information

Chapter 7 Control. Part Classical Control. Mobile Robotics - Prof Alonzo Kelly, CMU RI

Chapter 7 Control. Part Classical Control. Mobile Robotics - Prof Alonzo Kelly, CMU RI Chapter 7 Control 7.1 Classical Control Part 1 1 7.1 Classical Control Outline 7.1.1 Introduction 7.1.2 Virtual Spring Damper 7.1.3 Feedback Control 7.1.4 Model Referenced and Feedforward Control Summary

More information

Answers to multiple choice questions

Answers to multiple choice questions Answers to multiple choice questions Chapter 2 M2.1 (b) M2.2 (a) M2.3 (d) M2.4 (b) M2.5 (a) M2.6 (b) M2.7 (b) M2.8 (c) M2.9 (a) M2.10 (b) Chapter 3 M3.1 (b) M3.2 (d) M3.3 (d) M3.4 (d) M3.5 (c) M3.6 (c)

More information

Table of Laplacetransform

Table of Laplacetransform Appendix Table of Laplacetransform pairs 1(t) f(s) oct), unit impulse at t = 0 a, a constant or step of magnitude a at t = 0 a s t, a ramp function e- at, an exponential function s + a sin wt, a sine fun

More information

PID Control. Objectives

PID Control. Objectives PID Control Objectives The objective of this lab is to study basic design issues for proportional-integral-derivative control laws. Emphasis is placed on transient responses and steady-state errors. The

More information

Professional Portfolio Selection Techniques: From Markowitz to Innovative Engineering

Professional Portfolio Selection Techniques: From Markowitz to Innovative Engineering Massachusetts Institute of Technology Sponsor: Electrical Engineering and Computer Science Cosponsor: Science Engineering and Business Club Professional Portfolio Selection Techniques: From Markowitz to

More information

CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER

CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER 114 CHAPTER 5 ROBUSTNESS ANALYSIS OF THE CONTROLLER 5.1 INTRODUCTION Robust control is a branch of control theory that explicitly deals with uncertainty in its approach to controller design. It also refers

More information

Solutions for Tutorial 10 Stability Analysis

Solutions for Tutorial 10 Stability Analysis Solutions for Tutorial 1 Stability Analysis 1.1 In this question, you will analyze the series of three isothermal CSTR s show in Figure 1.1. The model for each reactor is the same at presented in Textbook

More information

Improved Identification and Control of 2-by-2 MIMO System using Relay Feedback

Improved Identification and Control of 2-by-2 MIMO System using Relay Feedback CEAI, Vol.17, No.4 pp. 23-32, 2015 Printed in Romania Improved Identification and Control of 2-by-2 MIMO System using Relay Feedback D.Kalpana, T.Thyagarajan, R.Thenral Department of Instrumentation Engineering,

More information

Index. Index. More information. in this web service Cambridge University Press

Index. Index. More information.  in this web service Cambridge University Press A-type elements, 4 7, 18, 31, 168, 198, 202, 219, 220, 222, 225 A-type variables. See Across variable ac current, 172, 251 ac induction motor, 251 Acceleration rotational, 30 translational, 16 Accumulator,

More information

ECE317 : Feedback and Control

ECE317 : Feedback and Control ECE317 : Feedback and Control Lecture : Routh-Hurwitz stability criterion Examples Dr. Richard Tymerski Dept. of Electrical and Computer Engineering Portland State University 1 Course roadmap Modeling

More information

CompensatorTuning for Didturbance Rejection Associated with Delayed Double Integrating Processes, Part II: Feedback Lag-lead First-order Compensator

CompensatorTuning for Didturbance Rejection Associated with Delayed Double Integrating Processes, Part II: Feedback Lag-lead First-order Compensator CompensatorTuning for Didturbance Rejection Associated with Delayed Double Integrating Processes, Part II: Feedback Lag-lead First-order Compensator Galal Ali Hassaan Department of Mechanical Design &

More information

Chapter 8. Feedback Controllers. Figure 8.1 Schematic diagram for a stirred-tank blending system.

Chapter 8. Feedback Controllers. Figure 8.1 Schematic diagram for a stirred-tank blending system. Feedback Controllers Figure 8.1 Schematic diagram for a stirred-tank blending system. 1 Basic Control Modes Next we consider the three basic control modes starting with the simplest mode, proportional

More information

SRI VENKATESWARA COLLEGE OF ENGINEERING

SRI VENKATESWARA COLLEGE OF ENGINEERING COURSE DELIVERY PLAN - THEORY Page 1 of 7 Department of Chemical Engineering B.E/B.Tech/M.E/M.Tech : Chemical Engineering Regulation:2013 PG Specialisation : NA Sub. Code / Sub. Name : CH 6605 - Process

More information

EC CONTROL SYSTEM UNIT I- CONTROL SYSTEM MODELING

EC CONTROL SYSTEM UNIT I- CONTROL SYSTEM MODELING EC 2255 - CONTROL SYSTEM UNIT I- CONTROL SYSTEM MODELING 1. What is meant by a system? It is an arrangement of physical components related in such a manner as to form an entire unit. 2. List the two types

More information

Introduction to. Process Control. Ahmet Palazoglu. Second Edition. Jose A. Romagnoli. CRC Press. Taylor & Francis Group. Taylor & Francis Group,

Introduction to. Process Control. Ahmet Palazoglu. Second Edition. Jose A. Romagnoli. CRC Press. Taylor & Francis Group. Taylor & Francis Group, Introduction to Process Control Second Edition Jose A. Romagnoli Ahmet Palazoglu CRC Press Taylor & Francis Group Boca Raton London NewYork CRC Press is an imprint of the Taylor & Francis Group, an informa

More information

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING QUESTION BANK SUB.NAME : CONTROL SYSTEMS BRANCH : ECE YEAR : II SEMESTER: IV 1. What is control system? 2. Define open

More information

CHAPTER 7 FRACTIONAL ORDER SYSTEMS WITH FRACTIONAL ORDER CONTROLLERS

CHAPTER 7 FRACTIONAL ORDER SYSTEMS WITH FRACTIONAL ORDER CONTROLLERS 9 CHAPTER 7 FRACTIONAL ORDER SYSTEMS WITH FRACTIONAL ORDER CONTROLLERS 7. FRACTIONAL ORDER SYSTEMS Fractional derivatives provide an excellent instrument for the description of memory and hereditary properties

More information

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review

Dr Ian R. Manchester Dr Ian R. Manchester AMME 3500 : Review Week Date Content Notes 1 6 Mar Introduction 2 13 Mar Frequency Domain Modelling 3 20 Mar Transient Performance and the s-plane 4 27 Mar Block Diagrams Assign 1 Due 5 3 Apr Feedback System Characteristics

More information

VALLIAMMAI ENGINEERING COLLEGE

VALLIAMMAI ENGINEERING COLLEGE VALLIAMMAI ENGINEERING COLLEGE SRM Nagar, Kattankulathur 603 203 DEPARTMENT OF ELECTRICAL AND ELECTRONICS ENGINEERING QUESTION BANK V SEMESTER IC650 CONTROL SYSTEMS Regulation 203 Academic Year 207 8 Prepared

More information

3.1 Overview 3.2 Process and control-loop interactions

3.1 Overview 3.2 Process and control-loop interactions 3. Multivariable 3.1 Overview 3.2 and control-loop interactions 3.2.1 Interaction analysis 3.2.2 Closed-loop stability 3.3 Decoupling control 3.3.1 Basic design principle 3.3.2 Complete decoupling 3.3.3

More information

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING

KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING KINGS COLLEGE OF ENGINEERING DEPARTMENT OF ELECTRONICS AND COMMUNICATION ENGINEERING QUESTION BANK SUB.NAME : CONTROL SYSTEMS STAFF NAME: Mr. P.NARASIMMAN BRANCH : ECE Mr.K.R.VENKATESAN YEAR : II SEMESTER

More information

The output voltage is given by,

The output voltage is given by, 71 The output voltage is given by, = (3.1) The inductor and capacitor values of the Boost converter are derived by having the same assumption as that of the Buck converter. Now the critical value of the

More information

IMC based automatic tuning method for PID controllers in a Smith predictor configuration

IMC based automatic tuning method for PID controllers in a Smith predictor configuration Computers and Chemical Engineering 28 (2004) 281 290 IMC based automatic tuning method for PID controllers in a Smith predictor configuration Ibrahim Kaya Department of Electrical and Electronics Engineering,

More information

Autonomous Mobile Robot Design

Autonomous Mobile Robot Design Autonomous Mobile Robot Design Topic: Guidance and Control Introduction and PID Loops Dr. Kostas Alexis (CSE) Autonomous Robot Challenges How do I control where to go? Autonomous Mobile Robot Design Topic:

More information

Course Summary. The course cannot be summarized in one lecture.

Course Summary. The course cannot be summarized in one lecture. Course Summary Unit 1: Introduction Unit 2: Modeling in the Frequency Domain Unit 3: Time Response Unit 4: Block Diagram Reduction Unit 5: Stability Unit 6: Steady-State Error Unit 7: Root Locus Techniques

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

Chapter 7 - Solved Problems

Chapter 7 - Solved Problems Chapter 7 - Solved Problems Solved Problem 7.1. A continuous time system has transfer function G o (s) given by G o (s) = B o(s) A o (s) = 2 (s 1)(s + 2) = 2 s 2 + s 2 (1) Find a controller of minimal

More information

Principles and Practice of Automatic Process Control

Principles and Practice of Automatic Process Control Principles and Practice of Automatic Process Control Third Edition Carlos A. Smith, Ph.D., P.E. Department of Chemical Engineering University of South Florida Armando B. Corripio, Ph.D., P.E. Gordon A.

More information

arxiv: v1 [cs.sy] 30 Nov 2017

arxiv: v1 [cs.sy] 30 Nov 2017 Disturbance Observer based Control of Integrating Processes with Dead-Time using PD controller Sujay D. Kadam SysIDEA Lab, IIT Gandhinagar, India. arxiv:1711.11250v1 [cs.sy] 30 Nov 2017 Abstract The work

More information

LABORATORY INSTRUCTION MANUAL CONTROL SYSTEM I LAB EE 593

LABORATORY INSTRUCTION MANUAL CONTROL SYSTEM I LAB EE 593 LABORATORY INSTRUCTION MANUAL CONTROL SYSTEM I LAB EE 593 ELECTRICAL ENGINEERING DEPARTMENT JIS COLLEGE OF ENGINEERING (AN AUTONOMOUS INSTITUTE) KALYANI, NADIA CONTROL SYSTEM I LAB. MANUAL EE 593 EXPERIMENT

More information

A unified approach for proportional-integral-derivative controller design for time delay processes

A unified approach for proportional-integral-derivative controller design for time delay processes Korean J. Chem. Eng., 32(4), 583-596 (2015) DOI: 10.1007/s11814-014-0237-6 INVITED REVIEW PAPER INVITED REVIEW PAPER pissn: 0256-1115 eissn: 1975-7220 A unified approach for proportional-integral-derivative

More information

Tuning Method of PI Controller with Desired Damping Coefficient for a First-order Lag Plus Deadtime System

Tuning Method of PI Controller with Desired Damping Coefficient for a First-order Lag Plus Deadtime System PID' Brescia (Italy), March 8-0, 0 FrA. Tuning Method of PI Controller with Desired Damping Coefficient for a First-order Lag Plus Deadtime System Yuji Yamakawa*. Yohei Okada** Takanori Yamazaki***. Shigeru

More information

Controls Problems for Qualifying Exam - Spring 2014

Controls Problems for Qualifying Exam - Spring 2014 Controls Problems for Qualifying Exam - Spring 2014 Problem 1 Consider the system block diagram given in Figure 1. Find the overall transfer function T(s) = C(s)/R(s). Note that this transfer function

More information

Simple analytic rules for model reduction and PID controller tuning

Simple analytic rules for model reduction and PID controller tuning Journal of Process Control 3 (2003) 29 309 www.elsevier.com/locate/jprocont Simple analytic rules for model reduction and PID controller tuning Sigurd Sogestad* Department of Chemical Engineering, Norwegian

More information

1 Loop Control. 1.1 Open-loop. ISS0065 Control Instrumentation

1 Loop Control. 1.1 Open-loop. ISS0065 Control Instrumentation Lecture 4 ISS0065 Control Instrumentation 1 Loop Control System has a continuous signal (analog) basic notions: open-loop control, close-loop control. 1.1 Open-loop Open-loop / avatud süsteem / открытая

More information

Process Control J.P. CORRIOU. Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 2016

Process Control J.P. CORRIOU. Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 2016 Process Control J.P. CORRIOU Reaction and Process Engineering Laboratory University of Lorraine-CNRS, Nancy (France) Zhejiang University 206 J.P. Corriou (LRGP) Process Control Zhejiang University 206

More information

NonlinearControlofpHSystemforChangeOverTitrationCurve

NonlinearControlofpHSystemforChangeOverTitrationCurve D. SWATI et al., Nonlinear Control of ph System for Change Over Titration Curve, Chem. Biochem. Eng. Q. 19 (4) 341 349 (2005) 341 NonlinearControlofpHSystemforChangeOverTitrationCurve D. Swati, V. S. R.

More information

Stability of Feedback Control Systems: Absolute and Relative

Stability of Feedback Control Systems: Absolute and Relative Stability of Feedback Control Systems: Absolute and Relative Dr. Kevin Craig Greenheck Chair in Engineering Design & Professor of Mechanical Engineering Marquette University Stability: Absolute and Relative

More information

Internal Model Control of A Class of Continuous Linear Underactuated Systems

Internal Model Control of A Class of Continuous Linear Underactuated Systems Internal Model Control of A Class of Continuous Linear Underactuated Systems Asma Mezzi Tunis El Manar University, Automatic Control Research Laboratory, LA.R.A, National Engineering School of Tunis (ENIT),

More information

University of Science and Technology, Sudan Department of Chemical Engineering.

University of Science and Technology, Sudan Department of Chemical Engineering. ISO 91:28 Certified Volume 3, Issue 6, November 214 Design and Decoupling of Control System for a Continuous Stirred Tank Reactor (CSTR) Georgeous, N.B *1 and Gasmalseed, G.A, Abdalla, B.K (1-2) University

More information

Course roadmap. Step response for 2nd-order system. Step response for 2nd-order system

Course roadmap. Step response for 2nd-order system. Step response for 2nd-order system ME45: Control Systems Lecture Time response of nd-order systems Prof. Clar Radcliffe and Prof. Jongeun Choi Department of Mechanical Engineering Michigan State University Modeling Laplace transform Transfer

More information

IMPROVED TECHNIQUE OF MULTI-STAGE COMPENSATION. K. M. Yanev A. Obok Opok

IMPROVED TECHNIQUE OF MULTI-STAGE COMPENSATION. K. M. Yanev A. Obok Opok IMPROVED TECHNIQUE OF MULTI-STAGE COMPENSATION K. M. Yanev A. Obok Opok Considering marginal control systems, a useful technique, contributing to the method of multi-stage compensation is suggested. A

More information

Control of Electromechanical Systems

Control of Electromechanical Systems Control of Electromechanical Systems November 3, 27 Exercise Consider the feedback control scheme of the motor speed ω in Fig., where the torque actuation includes a time constant τ A =. s and a disturbance

More information

CDS 101/110a: Lecture 8-1 Frequency Domain Design

CDS 101/110a: Lecture 8-1 Frequency Domain Design CDS 11/11a: Lecture 8-1 Frequency Domain Design Richard M. Murray 17 November 28 Goals: Describe canonical control design problem and standard performance measures Show how to use loop shaping to achieve

More information

Chemical Process Dynamics and Control. Aisha Osman Mohamed Ahmed Department of Chemical Engineering Faculty of Engineering, Red Sea University

Chemical Process Dynamics and Control. Aisha Osman Mohamed Ahmed Department of Chemical Engineering Faculty of Engineering, Red Sea University Chemical Process Dynamics and Control Aisha Osman Mohamed Ahmed Department of Chemical Engineering Faculty of Engineering, Red Sea University 1 Chapter 4 System Stability 2 Chapter Objectives End of this

More information

Design Methods for Control Systems

Design Methods for Control Systems Design Methods for Control Systems Maarten Steinbuch TU/e Gjerrit Meinsma UT Dutch Institute of Systems and Control Winter term 2002-2003 Schedule November 25 MSt December 2 MSt Homework # 1 December 9

More information

Outline. Classical Control. Lecture 1

Outline. Classical Control. Lecture 1 Outline Outline Outline 1 Introduction 2 Prerequisites Block diagram for system modeling Modeling Mechanical Electrical Outline Introduction Background Basic Systems Models/Transfers functions 1 Introduction

More information

Process Modelling, Identification, and Control

Process Modelling, Identification, and Control Jan Mikles Miroslav Fikar 2008 AGI-Information Management Consultants May be used for personal purporses only or by libraries associated to dandelon.com network. Process Modelling, Identification, and

More information

Step input, ramp input, parabolic input and impulse input signals. 2. What is the initial slope of a step response of a first order system?

Step input, ramp input, parabolic input and impulse input signals. 2. What is the initial slope of a step response of a first order system? IC6501 CONTROL SYSTEM UNIT-II TIME RESPONSE PART-A 1. What are the standard test signals employed for time domain studies?(or) List the standard test signals used in analysis of control systems? (April

More information

CYBER EXPLORATION LABORATORY EXPERIMENTS

CYBER EXPLORATION LABORATORY EXPERIMENTS CYBER EXPLORATION LABORATORY EXPERIMENTS 1 2 Cyber Exploration oratory Experiments Chapter 2 Experiment 1 Objectives To learn to use MATLAB to: (1) generate polynomial, (2) manipulate polynomials, (3)

More information

Chapter 9: Controller design

Chapter 9: Controller design Chapter 9. Controller Design 9.1. Introduction 9.2. Effect of negative feedback on the network transfer functions 9.2.1. Feedback reduces the transfer function from disturbances to the output 9.2.2. Feedback

More information

SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015

SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015 FACULTY OF ENGINEERING AND SCIENCE SAMPLE SOLUTION TO EXAM in MAS501 Control Systems 2 Autumn 2015 Lecturer: Michael Ruderman Problem 1: Frequency-domain analysis and control design (15 pt) Given is a

More information

Control 2. Proportional and Integral control

Control 2. Proportional and Integral control Control 2 Proportional and Integral control 1 Disturbance rejection in Proportional Control Θ i =5 + _ Controller K P =20 Motor K=2.45 Θ o Consider first the case where the motor steadystate gain = 2.45

More information

Automatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year

Automatic Control 2. Loop shaping. Prof. Alberto Bemporad. University of Trento. Academic year Automatic Control 2 Loop shaping Prof. Alberto Bemporad University of Trento Academic year 21-211 Prof. Alberto Bemporad (University of Trento) Automatic Control 2 Academic year 21-211 1 / 39 Feedback

More information

Control Introduction. Gustaf Olsson IEA Lund University.

Control Introduction. Gustaf Olsson IEA Lund University. Control Introduction Gustaf Olsson IEA Lund University Gustaf.Olsson@iea.lth.se Lecture 3 Dec Nonlinear and linear systems Aeration, Growth rate, DO saturation Feedback control Cascade control Manipulated

More information

BASIC PROPERTIES OF FEEDBACK

BASIC PROPERTIES OF FEEDBACK ECE450/550: Feedback Control Systems. 4 BASIC PROPERTIES OF FEEDBACK 4.: Setting up an example to benchmark controllers There are two basic types/categories of control systems: OPEN LOOP: Disturbance r(t)

More information

R a) Compare open loop and closed loop control systems. b) Clearly bring out, from basics, Force-current and Force-Voltage analogies.

R a) Compare open loop and closed loop control systems. b) Clearly bring out, from basics, Force-current and Force-Voltage analogies. SET - 1 II B. Tech II Semester Supplementary Examinations Dec 01 1. a) Compare open loop and closed loop control systems. b) Clearly bring out, from basics, Force-current and Force-Voltage analogies..

More information

Control for. Maarten Steinbuch Dept. Mechanical Engineering Control Systems Technology Group TU/e

Control for. Maarten Steinbuch Dept. Mechanical Engineering Control Systems Technology Group TU/e Control for Maarten Steinbuch Dept. Mechanical Engineering Control Systems Technology Group TU/e Motion Systems m F Introduction Timedomain tuning Frequency domain & stability Filters Feedforward Servo-oriented

More information

CHAPTER 13: FEEDBACK PERFORMANCE

CHAPTER 13: FEEDBACK PERFORMANCE When I complete this chapter, I want to be able to do the following. Apply two methods for evaluating control performance: simulation and frequency response Apply general guidelines for the effect of -

More information

PID Tuning of Plants With Time Delay Using Root Locus

PID Tuning of Plants With Time Delay Using Root Locus San Jose State University SJSU ScholarWorks Master's Theses Master's Theses and Graduate Research Summer 2011 PID Tuning of Plants With Time Delay Using Root Locus Greg Baker San Jose State University

More information

Intermediate Process Control CHE576 Lecture Notes # 2

Intermediate Process Control CHE576 Lecture Notes # 2 Intermediate Process Control CHE576 Lecture Notes # 2 B. Huang Department of Chemical & Materials Engineering University of Alberta, Edmonton, Alberta, Canada February 4, 2008 2 Chapter 2 Introduction

More information

Lecture 25: Tue Nov 27, 2018

Lecture 25: Tue Nov 27, 2018 Lecture 25: Tue Nov 27, 2018 Reminder: Lab 3 moved to Tuesday Dec 4 Lecture: review time-domain characteristics of 2nd-order systems intro to control: feedback open-loop vs closed-loop control intro to

More information

K c < K u K c = K u K c > K u step 4 Calculate and implement PID parameters using the the Ziegler-Nichols tuning tables: 30

K c < K u K c = K u K c > K u step 4 Calculate and implement PID parameters using the the Ziegler-Nichols tuning tables: 30 1.5 QUANTITIVE PID TUNING METHODS Tuning PID parameters is not a trivial task in general. Various tuning methods have been proposed for dierent model descriptions and performance criteria. 1.5.1 CONTINUOUS

More information

Model-based PID tuning for high-order processes: when to approximate

Model-based PID tuning for high-order processes: when to approximate Proceedings of the 44th IEEE Conference on Decision and Control, and the European Control Conference 25 Seville, Spain, December 2-5, 25 ThB5. Model-based PID tuning for high-order processes: when to approximate

More information

MEM 355 Performance Enhancement of Dynamical Systems

MEM 355 Performance Enhancement of Dynamical Systems MEM 355 Performance Enhancement of Dynamical Systems Frequency Domain Design Intro Harry G. Kwatny Department of Mechanical Engineering & Mechanics Drexel University /5/27 Outline Closed Loop Transfer

More information

Iterative Feedback Tuning

Iterative Feedback Tuning Iterative Feedback Tuning Michel Gevers CESAME - UCL Louvain-la-Neuve Belgium Collaboration : H. Hjalmarsson, S. Gunnarsson, O. Lequin, E. Bosmans, L. Triest, M. Mossberg Outline Problem formulation Iterative

More information