Apps

Piecewise Linear

Apps.PiecewiseLinear History

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February 13, 2013, at 10:09 AM by 69.169.188.188 -
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   minimize slk_u[1:4]
    minimize slk_l[2:5]

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File *.m.csv
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File m.csv
August 27, 2010, at 10:16 PM by 206.180.155.75 -
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  End Equations
End Model
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! Piece-wise function with the LOOKUP object

! create the csv file
File *.m.csv
  input,  y[1],  y[2]
      1,    2,    4
      3,    4,    6
      5,    -5,  -7
    -1,    1,  0.5
End File

! define lookup object m
Objects
  m = lookup
End Objects

! connect m properties with model parameters
Connections
  x = m.input
  y[1] = m.y[1]
  y[2] = m.y[2]
End Connections

! simple model
Model n
  Parameters
    x = 1
    y[1]
    y[2]
  End Parameters

  Variables
    y
  End Variables

  Equations
    y = y[1]+y[2]
March 06, 2010, at 02:45 AM by 206.180.155.75 -
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April 23, 2009, at 10:46 AM by 158.35.225.231 -
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Model pwl
  Parameters
    ! independent variable
    x = 6.0

    ! data points
    xp[1] = 1
    yp[1] = 1

    xp[2] = 2
    yp[2] = 0

    xp[3] = 3
    yp[3] = 2

    xp[4] = 3.5
    yp[4] = 2.5

    xp[5] = 4
    yp[5] = 2.8

    xp[6] = 5
    yp[6] = 3
  End Parameters

  Variables
    ! piece-wise linear segments
    x[1]            <=xp[2]
    x[2:4] >xp[2:4], <=xp[3:5]
    x[5]  >xp[5]

    ! dependent variable
    y

    ! slack variables
    slk_u[1:4]
    slk_l[2:5]
  End Variables

  Intermediates
    slope[1:5] = (yp[2:6]-yp[1:5]) / (xp[2:6]-xp[1:5])
    y[1:5] = (x[1:5]-xp[1:5])*slope[1:5]
  End Intermediates

  Equations
    x = x[1]  + slk_u[1]
    x = x[2:4] + slk_u[2:4] - slk_l[2:4]
    x = x[5]                - slk_l[5]

    y = yp[1] + y[1] + y[2] + y[3] + y[4] + y[5]
  End Equations
End Model
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February 23, 2009, at 07:45 AM by 158.35.225.228 -
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!! Piece-wise Linear Approximation

* %list list-page% [[Attach:pwl.apm | Piece-wise Linear Approximation Example]]

Attach:pwl.gif

A piece-wise linear function is an approximation of a nonlinear relationship.  For more nonlinear relationships, additional linear segments are added to refine the approximation.

As an example, the piecewise linear form is often used to approximate valve characterization (valve position (% open) to flow).  This is a single input-single output function approximation.

''In Situ'' Adaptive Tabulation (ISAT) is an example of a multi-dimensional piecewise linear approximation.  The piecewise linear segments are built dynamically as new data becomes available.  This way, only regions that are accessed in practice contribute to the function approximation.

Attach:mpwl.png