lecture 1 feedback control system sept 2012

Upload: mohd-ikram-solehuddin

Post on 03-Jun-2018

226 views

Category:

Documents


0 download

TRANSCRIPT

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    1/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 14/11/2014

    Lecture 1. Feedback Control System

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    2/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 24/11/2014

    Feedback Control System

    Figure 1. Schematic diagram of a heat exchanger

    Schematic Diagram : A Heat Exchanger ( without controlsystem)

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    3/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 34/11/2014

    Feedback Control System

    Model Equations : Assuming W(s)=0

    )(1

    )(1

    1)( 1 sW

    s

    KsT

    ssT s

    p

    )()()()( 1 sWsGTsGsT spd

    In general

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    4/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 44/11/2014

    Schematic Diagram : A Heat Exchanger ( with Feedback

    control system)

    Feedback Control System

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    5/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 54/11/2014

    Feedback Control System

    Block Diagram Diagram

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    6/21

    MultivariablePro

    cessControl

    CAB4523 Multivariable Process Control 64/11/2014

    Block Diagram General

    Feedback Control System

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    7/21

    MultivariablePro

    cessControl

    Closed-loop Equation

    CAB4523 Multivariable Process Control 74/11/2014

    )(1

    )(1

    sDGGGG

    GsY

    GGGG

    GGGY

    mpvc

    dsp

    mpvc

    pvc

    Feedback Control System

    )(1

    sDGGGG

    GY

    mpvc

    d

    )(1

    sYGGGG

    GGGY sp

    mpvc

    pvc

    Servo-problem

    Regulator-problem

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    8/21

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    9/21

    MultivariablePro

    cessControl

    Stability Analysis

    The characteristic equation

    CAB4523 Multivariable Process Control 94/11/2014

    01 mpvc GGGG

    A feedback control system is stable if and only if all

    roots of the characteristic equation are negative or

    have negative real parts. Otherwise, the system is

    unstable.

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    10/21

    MultivariablePro

    cessControl

    ECB4034 - Chemical Process Instrumentation and Control 10

    Routh Stability Criterion

    Uses an analytical technique for determining whetherany roots of a polynomial have positive real parts.

    Characteristic equation

    00111 asasasa n

    nn

    n

    where an>0. According to the Routh criterion, if any of

    the coefficients a0, a1, aK, an-1 are negative or zero, then at

    least one root of the characteristic equation lies in the RHP,and thus, the system is unstable.

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    11/21

    MultivariablePro

    cessControl

    ECB4034 - Chemical Process Instrumentation and Control 11

    The first two rows of the Routh Array are comprised of

    the coefficients in the characteristics equation. The

    elements in the remaining rows are calculated from

    coefficients from the using the formulas:

    1

    3211

    n

    nnnn

    aaaaab

    1n

    5nn4n1n2

    aaaaab

    1

    21311

    b

    baabc nn

    1

    31n5n12

    b

    baabc

    (n+1 rows must be constructed

    n = order of the characteristic eqn.)

    Routh Stability Criterion

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    12/21

    MultivariableProcessControl

    ECB4034 - Chemical Process Instrumentation and Control 12

    Routh Stability Criterion:

    A necessary and sufficient condition for all roots of thecharacteristic equation to have negative real parts is

    that all of the elements in the left column of the Routh

    array are positive.

    Example 1:Determine the stability of a system that

    has the characteristic equation

    0135 234 sss

    Solution: Because thesterm is missing, its coefficient is

    zero. Thus the system is unstable.

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    13/21

    MultivariableProcessControl

    Example 2The transfer functions comprising a feedback

    control system are given below. Check whether the

    closed-loop response is stable.

    CAB4523 Multivariable Process Control 134/11/2014

    ss

    c3

    11)(G

    )18(

    3.2)(G

    s

    sp

    15

    5.2)(G

    ssv

    12

    1)(G

    s

    sm

    Routh Stability Criterion:

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    14/21

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    15/21

    MultivariableProcessControl

    ECB4034 - Chemical Process Instrumentation and Control 15

    The Routh array is:

    Routh Stability Criterion:

    Row

    1 240 45 5.75

    2 198 2.25

    3 42.27 5.75

    4 -24.68

    5 1

    2727.42198

    )25.2240()45198(

    68.2427.42

    )75.5198()25.227.42(

    Since element in row 4 is negative the feedback control

    system is unstable

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    16/21

    MultivariableProcessControl

    Tuning of Feedback Controllers

    Tuning Methods: There are numerous tuningmethods one of the most popular methodZeigler Nichols

    CAB4523 Multivariable Process Control 164/11/2014

    Controller Parameters

    Controller Kc I D

    P

    PI

    PID

    2

    cuK

    2.2

    cuK

    2.1

    uT

    7.1

    cuK

    2

    uT

    8

    uT

    Zeigler-Nichols controller setting

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    17/21

    MultivariableProcessControl

    CAB4523 Multivariable Process Control 174/11/2014

    Ziegler-Nichols Closed-loop

    MethodKnown as cont inuou s cyc l ing method. It is based on thefollowing trial-and-error procedure:

    Step 1.After the process has reached steady state, the integraland derivative actions are eliminated by setting Tdto zeroand Tito the largest possible value.

    Step 2.Set Kcequal to a small value and place the controller inthe automatic mode.

    Step 3.Introduce a small momentary set point change. Graduallyincrease Kcin small increments until continuous cyclingoccurs. The numerical value of Kcthat produces the effectis called the ultimate gain, Kcuand the period of thecorresponding sustained oscillation is referred to as the

    ultimate period, Pu.Step 4.Calculate the PID controller settings using the Ziegler-

    Nichols tuning relations as given in the Table.

    Step 5.Evaluate the Ziegler-Nichols controller settings byintroducing small set point change and observing theclosed-loop response. Fine-tune the settings, if necessary.

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    18/21

    MultivariableProcessControl

    CAB4523 Multivariable Process Control 184/11/2014

    This method is an open- loop method. An open-loop transient is induced by a step change in thesignal to the valve. The Cohen-Coon method issummarized in the following steps:

    Step 1. With the controller in manual, introduce asmall step change in the controller outputthat goes to the valve and record thetransient, which is the process reactioncurve.

    Step 2. Draw a straight line tangent to the curve atthe point of inflection. The intersection ofthe tangent line with the time axis is theapparent transport lag, Td.

    Cohen-Coon Tuning

    Method

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    19/21

    MultivariableProcessControl

    CAB4523 Multivariable Process Control 194/11/2014

    Typical process reaction curve showing graphical

    construction to determine first-order with transport lag

    model.

    Tangent line, slope =Bu/T= S

    Bu

    0

    0 t

    M

    0

    0 t

    Input

    Cohen-Coon Tuning

    Method

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    20/21

    MultivariableProcessControl

    CAB4523 Multivariable Process Control 204/11/2014

    Step 3.

    The apparent first-order time constant, is obtained

    from

    where Buis theultimate value of Bat large tand Sis

    the slope of the tangent line. The steady state gain is

    given by

    where Mis the magnitude of the input signal. The time

    delay is given by

    Cohen-Coon Tuning

    Method

    S

    BT u

    MB

    K up

    Td

  • 8/12/2019 Lecture 1 Feedback Control System Sept 2012

    21/21

    MultivariableProcessControl

    CAB4523 M lti ariable Process Control 214/11/2014

    Step 4. Using the values Kp, Tand Tdfrom step 3, the

    controller settings are found from the relations given in

    the Table.

    Controller KcI

    D

    P

    T

    T

    T

    T

    K

    d

    dp 31

    1

    - -

    PI

    T

    T

    T

    T

    K

    d

    dp 1210

    91

    TT

    TTT

    d

    dd

    /209

    /3030

    -

    PID

    T

    T

    T

    T

    K

    d

    dp 43

    41

    TT

    TTT

    d

    dd

    /813

    /632

    TTT

    d

    d/211

    4

    Cohen-Coon Tuning

    Method