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.

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 minimize slk_u[1:4] minimize slk_l[2:5] 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

! 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] End Equations End Model

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Page last modified on July 31, 2017, at 07:56 PM