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        -2.844758727        1.772390077        0.618334961        0.327384632
2        -1.789541283        1.397405553        0.446838172        0.419746818
3        -1.934754843        0.880111238        0.255602191        0.593253045
4        -1.006031154        0.379060033        0.069045196        0.577132976
5        -0.047658029        -0.08179372        0.052672613        0.689930183
6        -0.124053768        -0.457878464        0.041489199        0.594926384
7        -0.142116339        -0.380754393        0.02492878        0.409770313
8        -0.078115606        -0.362090946        0.012459928        0.601286138
9        -0.021748041        -0.551822214        0.009609389        0.458334121
10        -0.069665146        -0.491267614        0.005490968        0.397242521
;

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;