LabVIEW
How to specify equality constraints in constrained nonlinear optimization
Solved!
You have two ways to specify parameters of an objective function.
1. Specify in the objective function: This means that in the objective function you specify constants or default values that can only be changed by editing the objective function. It looks like this is what you are trying to do, but you are using a block-diagram constant as the "type" input to the "variant to data" primitive. Any data contained within the type input is ignored as it is used as a type specifier only. So instead of your current code:
You might have this:
2. Specify objective function parameters elsewhere in the optimization algorithm:
Method one can be inconvenient because every time the objective function parameters change you must edit the objective function. For example, suppose temperature (T) is a measured quantity in an experiment and is a parameter of your objective function. Suppose you measure temperature 10 times and each time you will perform an optimization with your objective function. Using method 1 you will have to edit your objective function 10 times, making automation of the optimization problem problematic. An alternative is to have a method to pass the objective function parameter into the cost function from a higher level in the VI hierarchy. This data could be anything, so we used a variant as a carrier for this data. This means that at the point in your diagram where you call the global optimization.vi you would pass your model parameters into the "function data" input of "global optimization.vi". The global optimization vi uses call by reference internally to evaluate your specified objective function, and passes the function data variant to your objective function. Inside the objective function you just convert from the variant type back to the actual parameter type.
-Jim
