set exper /1*14/
    quantities /Z1, dZ1/;

variables dZ1_mod, P1, P2, w;

table meas(exper,quantities)
         Z1         dZ1
1        1.4        3.309433965
2        6.3        3.84391593
3        10.4       3.968719982
4        14.2       3.775720852
5        17.6       3.391081904
6        21.4       2.896681355
7        23         2.427629166
8        27         1.823704749
9        30.5       1.484138245
10       34.4       1.107290032
11       38.8       0.63696542
12       41.6       0.428840615
13       43.5       0.353338548
14       45.3       -0.048810324

;



equations E1, obj;

E1(exper)..  dZ1_mod(exper) =E=  P1*(126.2 - meas(exper, 'Z1'))*(91.9 - meas(exper, 'Z1'))*(91.9 - meas(exper, 'Z1')) - P2*meas(exper, 'Z1')*meas(exper, 'Z1') ;

Obj..  w =E= sum( exper, (dZ1_mod(exper) - meas(exper, 'dZ1'))*(dZ1_mod(exper) - meas(exper, 'dZ1')) );

P1.lo = 0;
P1.up = 0.1;
P2.lo = 0;
P2.up = 0.1;

 MODEL TEST / E1, obj / ;

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

 SOLVE TEST USING NLP minimiZING w;