How to design a controller/ controllers for a MIMO thermo-hydraulic system modeled in Modelica/Dymola

Question

I am currently developing a large and complex thermo-hydraulic systems in Modelica/Dymola environment using ThermoPower library by Prof. Francesco Casella. At present, I have completed building our system model (which contains several closed-loop hydraulic circuits) and concentrating on designing controllers for the developed model. Given complexity of the system, I have about 25 PI controllers controlling various valve opening, pump, condenser and boilers. At this stage, I am tuning the controller gains using some judicious trial-and-error method. I tried to look into literature to see if there are any formal design methodology or any rule-of-thumbs for designing controllers for such a multi-input-multi-output (MIMO) thermo-hydraulic system. Consequently, I would like to ask if anyone can provide some pointers or literature/papers which deals with controller designs for such systems. Because my knowledge in controller design (sliding mode, linear control, root locus, etc) are not helping me here as most of these methodology are based on available model equations.

Furthermore, for such a large thermo-hydraulic systems, how one sets initial conditions of the system? Does one need to just provide some reasonable guess value and expect Dymola to take care of rest of it?

Answer 1

Well, I have to qualify my response by pointing out that I am NOT a controls engineer so take everything I say with a grain of salt.

To some extent, it really depends on what tool you are using since different tools specialize in different analysis features and offer different capabilities. For example, if you are using Dymola, you can use the "linearize" function to linearize your system. This will give you an entry into the formal controller design methods you are familiar with. The problem is, of course, that your system is probably highly non-linear so you will have to formulate a strategy to determine over what range of state space you need to control and then potentially develop strategies to adjust your gains accordingly.

One the other hand, if you are using tools like SystemModeler (from Wolfram) or MapleSim (from Maplesoft), I'm pretty sure you have the option to elaborate the Modelica model into a symbolic system of equations. As a result, you can again revisit the classical techniques that require the model equations to be available. Since these are not linearized, you will have full visibility on the non-linearities in symbolic form and you can take whatever measures are possible to address them.

Does that help?

Answer 2

I would try Model Predictive Control in your case (as long as your system will only be active in an approximately linear region or it can be made approximately linear).

Here is some info: http://www.stanford.edu/class/archive/ee/ee392m/ee392m.1056/Lecture14_MPC.pdf

But I would recommend getting a good control engineer book that describes this in more detail.

It has been quite a few years back that I have done an example of this so maybe this suggestion is outdated now.

Note that when you implement this in Modelica/Dymola that you will have to simulate the model using a fixed time step solver.