set exp dies ist bla /1*10/
        quantities /dZ1,dZ2,Z1,Z2/;

variables dZ1_mod, dZ2_mod, dZ3_mod, P1, P2, w;

table meas(exp,quantities)
         dZ1                 dZ2                Z1                 Z2
1        -2.506088031        2.768413222        0.647560427        0.313014796
2        -2.145320241        1.468534287        0.328812995        0.687826034
3        -1.357028662        0.273771617        0.189320045        0.584957475
4        -0.519582153        -0.41648671        0.064100791        0.6809773
5        -0.067716786        -0.579062316        0.094564484        0.480766681
6        -0.193121093        -0.518080416        0.068456053        0.600942227
7        -0.190009468        -0.279670967        0.033224993        0.39340625
8        -0.126175228        0.43602324        0.023368798        0.463068729
9        -0.096536877        0.670504626        0.011248626        0.569401235
10        -0.064294708        0.523244184        0.005087132        0.605767687
;

equations E1, E2, obj;

E1(exp)..  dZ1_mod(exp) =E=  -P1*meas(exp, 'Z1') ;
E2(exp)..  dZ2_mod(exp) =E=  P1*meas(exp, 'Z1') -  P2*meas(exp, 'Z2');

Obj..  w =E= sum( exp, (dZ1_mod(exp) - meas(exp, 'dZ1'))*(dZ1_mod(exp) - meas(exp, 'dZ1')) + (dZ2_mod(exp) - meas(exp, 'dZ2'))*(dZ2_mod(exp) - meas(exp, 'dZ2')) );

P1.lo = 0;
P1.up = 10;
P2.lo = 0;
P2.up = 10;

 MODEL TEST / E1, E2, obj / ;

 OPTION LIMROW = 0.0;
 OPTION LIMCOL = 0.0;
*OPTION MINLP=SBB;

 SOLVE TEST USING NLP minimiZING w;