Difference between revisions of "Lotka Volterra fishing problem (JModelica)"
From mintOC
(Created page with "This page contains the model formulation of the MIOCP Lotka Volterra fishing problem in JModelica format. == JModelica == The model for compilation with JModelica. <source...") |
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x1(0)=0.7; | x1(0)=0.7; | ||
end lotka; | end lotka; | ||
| − | |||
| + | </source> | ||
| + | The run file. | ||
| + | |||
| + | <source lang="python"> | ||
| + | #Import the function for transfering a model to CasADiInterface | ||
| + | from pyjmi import transfer_optimization_problem | ||
| + | |||
| + | op=transfer_optimization_problem("lotka", "lotka.mop") | ||
| + | |||
| + | res=op.optimize() | ||
</source> | </source> | ||
[[Category:JModelica]] | [[Category:JModelica]] | ||
Revision as of 11:17, 18 January 2016
This page contains the model formulation of the MIOCP Lotka Volterra fishing problem in JModelica format.
JModelica
The model for compilation with JModelica.
//-------------------------------------------------------------------- //Lotka Volterra Fishing Problem // (c) Madeleine Schroeter //-------------------------------------------------------------------- optimization lotka(objective = cost(finalTime), startTime = 0, finalTime = 12) "Steady State Solution with u=0" Real cost(start=0, min=0, max=25) "Integrated Deviation"; // Differential state variables Real x0(min=0, max=20.0) "Biomass of Prey"; Real x1(min=0, max=20.0) "Biomass of Predator"; // Control functions input Real u(free=true, min=0,max=1); constant Real ref0 = 1.0 "Steady State Prey"; constant Real ref1 = 1.0 "Steady State Predator"; equation der(x0) = x0 - x0*x1 - 0.4*x0*u; der(x1) = -x1 + x0*x1 - 0.2*x1*u; der(cost) = (x0 - ref0)*(x0 - ref0) + (x1 - ref1)*(x1 - ref1); // Quadratic deviation constraint x0(0)=0.5; x1(0)=0.7; end lotka;
The run file.
#Import the function for transfering a model to CasADiInterface from pyjmi import transfer_optimization_problem op=transfer_optimization_problem("lotka", "lotka.mop") res=op.optimize()
