ChE 433 DPCL - PowerPoint PPT Presentation

1 / 18
About This Presentation
Title:

ChE 433 DPCL

Description:

ChE 433 DPCL Model Based Control Smith Predictors – PowerPoint PPT presentation

Number of Views:75
Avg rating:3.0/5.0
Slides: 19
Provided by: wus52
Category:
Tags: che | dpcl | adaptive | array

less

Transcript and Presenter's Notes

Title: ChE 433 DPCL


1
ChE 433 DPCL
  • Model Based Control
  • Smith Predictors

2
Model Based Control
  • What can we do with a process model? Improve
    performance.
  • 3 Methods
  • Internal Model Control
  • Model Free Adaptive Control
  • Model based PID controllers

3
Internal Model Control
  • Dynamic Matrix Control, DMC, forward projection
    of a process change is placed in an array and
    output changes are based on a least error squared
    value of the projected process variable.
    Multivariable handout
  • Minimal Prototype Controller, where the
    controller output change is based on a projected
    change in process variable. This algorithm does
    not even use any elements from a conventional PID
    algorithm.

4
Model Free Adaptive Control
  • Uses neural network to control the process. The
    output will move the process variable to the set
    point based on an internal network, not
    determined by the user.
  • Some reasonable understanding of the process
    dynamics required. The process dynamics can
    change and the algorithm will learn the new
    conditions without being told to retrain itself.

5
MBC, Model Based Control
  • Introduced to improve control response with
    dominant dead time processes
  • Smith Predictor
  • Concept If we know the process transfer
    function, we can place the transfer function in
    the feedback path and cancel the dead time effect.

6
Smith Predictor
  • Smith Predictor describe how a model of the
    process is placed in the feed back path. The user
    believes that an exact calculation and
    representation is required to implement the
    technique.
  • Consider the elements in the feedback path as
    compensation elements.

7
MBC Implementation
  • The process model is divided into two sections,
    one that models the process first order time
    constants and a second that models the process
    dead time.
  • The value of these terms are not precisely equal
    to the process model.

8
MBC Implementation
  • The controllers compensated dead time should be
    smaller that the process dead time and the time
    constants should be slightly longer than the
    largest time constant.
  • The compensated dead time approx. 25 percent
    shorter than the process dead time and the
    compensated lag 25 percent longer than the
    process time constants.

9
MBC Implementation
  • It is not necessary for these compensating
    elements be precisely defined. The estimated
    values are usually sufficient. 85
  • It is not necessary to know the exact process
    gain
  • It is not necessary to have linear behavior the
    algorithm is configured to compensate for the
    model error.

10
MBC Implementation
  • A standard PID algorithm with a remote set
    point, CAS_IN, can be used if the model
    compensating terms can be implemented in a
    separating computing function block external to
    the controller.
  • Without an offset between set point and the
    algorithm output, and to correct for modeling
    error, a model correction term, MC is the ratio
    of the actual process variable to the output of
    the total process model, W.
  • Model correction method should be implemented in
    any advanced model based control system

11
(No Transcript)
12
(No Transcript)
13
(No Transcript)
14
Feed Forward to MBC
  • The disturbance test was done without
    implementing any feed forward.
  • Feed forward be implemented external to the
    predicted algorithm.
  • Difficult to suppress the compensating action
    based on the feed forward signal, move the valve
    some amount and not allow the compensating
    algorithm to adjust for the change. The algorithm
    will correct for model errors as designed.

15
Potential Problems
  • If dead time and time constants change
    significantly, the control loop will operate with
    choppy behaviour and not stabilize
  • Nonlinearity can be compensated

16
Integral Delay Dead Time Compensation
  • Add a delay before the integral function. Change
    in the error results in immediate change in the
    proportional action, reset or integral behavior
    will be delayed.
  • Integral delay time should be equal to the
    process dead time. This prevents excessive
    integral action.

17
(No Transcript)
18
Problems Implementing Integral Delay
  • Most commercially available controllers don't
    allow the user to configure the controllers
    internal elements. DeltaV does not. LabView does.
  • Many do not offer delay or dead time function
    blocks. A requires the controller manufacture to
    use more dynamic memory, which increases the cost
  • Use multiple first orders to simulate a dead time
Write a Comment
User Comments (0)
About PowerShow.com