I'm trying to model the respective processes of an internal combustion engine. My current modelling approach is to have different sub functions which model the different processes.
Within each sub function is a Level 2 S-Function which solves the ODEs to give the in cylinder state (pressure, temperature, etc).
The problem that I'm having is that each sub function is enabled depending on the current crank angle which is computed from the current timestep in Simulink. The first process works fine as I manually set the initial values, but then I can't pass the latest in-cylinder state (the output from the first sub function) to the second sub function to use as the initial conditions (it insists on using the initial values I set at the beginning of the simulation).
Is there any way round this? Currently I'm going along a path of global data stores, but haven't had any joy so far.
There are a lot of different ways to solve this problem.
I'll show some of them as examples.
You can create additive output with Unit dalay block like this:
So you can get value of your crank angle from previous timestep and USE IT in formula for solving you equations.
Also you can use some code like this:
if (t == 0)
% equations with your initial values
sred = 0;
else
% equations with other values
y = uOld + myCoeef;
end
Another idea: sometimes I use persistent variables in Matlab function to save values of some variable from previous step. But I think it makes calculation slower.
One more idea - if you have Stateflow you can create chart with two states: first for initial moment with your coefficient and second to solve new equations.
If I understood you in wrong way you can show your code and we'll offer some new ideas!
P.S. Example of my using of S-Function:
My S-Function needs 2 values: Q is calculated in simulink at every step, ro is initial I took from big matrix I loaded from workspace in table and took necessary value depending of time.
So there is no any initial values in S-Function - all needed values I transmit into it from simulink!
Related
For reading time-based data of variables from the Matlab workspace in Simulink (for time-based inter- and extrapolation), a typical solution is the use of the From Workspace block, by e.g. providing variable input data var in the following structure format:
var.time=[nx1]
var.signals.dimensions=m
var.signals.values=[nxm]
for providing the data of m variables with n time-based samples. Since variables' data is stored in a single matrix, it is implied that all variables are required to have the same (number of) time stamps.
If this is not the case, a solution could be the use of multiple From Workspace blocks, and corresponding variable input data structs (e.g. varA, varB, varC, etc.), like so:
However, this solution requires the number of variables to be fixed for all simulations. In my case, variables are numbered (rather than named) and the number of variables might not be the same from one simulation to the next. As such, for generalization purposes, I would like to find a solution without having to change the simulation file. A first step in this direction is the use of a struct array (i.e. var(1), var(2), var(3), etc.), which works:
A candidate next step is then to use a For Iterator to loop over N variables (and then to assign and concatenate the output in some output array, which I know can be done and is not the focus here):
The problem here is that the index id can't be fed to the From Workspace block! I ran into an identical issue when trying to solve the problem with a lookup table block. How to solve this problem of reading multiple but varying number of data variables from the workspace with different (number of) time stamps? Solutions that don't use a From Workspace or lookup table block are welcome too.
Here is equivalent code for running the whole thing in Matlab instead of Simulink:
% DEFINED IN MATLAB:
% Examplary input of variable data with different time stamps, according to
% Simulink structure conventions (.time, .signals etc)
N=3; % number of variables
for id=N:-1:1
var(id).time = linspace(0,2,id*2+2)';
var(id).signals.dimensions = 1;
var(id).signals.values = sin((var(id).time-id)*pi/2)';
end
% TO BE EXECUTED IN SIMULINK:
% the simulink clock time:
t = 1.234; % random time
for id=N:-1:1
var_t(id) = interp1(var(id).time,var(id).signals.values,t);
end
And here a figure to illustrate the results:
% Figure code:
figure(1),clf
colors=lines(N);
for id=1:N
plot(var(id).time,var(id).signals.values,'*-','color',colors(id,:)),hold on
plot(t,var_t(id),'o','color',colors(id,:))
end
xlabel('time'),ylabel('variable data')
Assuming I have a very complicated thermal-fluid model built with Dymola. During the initialization process, how would dymola choose the iteration variables for the nonlinear solver? Is there a standard for this issue in dymola? I wanna make this clear, cause sometimes if the start values of the iteration variables are too far away from the right solution, there would be a divergence issue during the initialization process. I think if I could know the choice of iteration variables, I could make sure their values are appropriate instead of checking all the start values.
I think this information is not available to the public. At least I could not find anything in the user manuals. Therefore, you have only limited options.
What you can do is:
List your current iteration variables
Try to influence the selection
Get information on performed iterations
List iteration variables
You can list your current iteration variables by activating the flag
Advanced.LogNonLinearIterationVariables = true;
The iteration variables will be listed in the Translation tab as info message Variables appearing in the nonlinear systems of equations:
Influence selected variables
You can influence (but not control) the variables selected for iteration by setting start values. Take this code for example:
model MyNonLinear
Real x;
Real y;
Real z(start=-1);
equation
0 = y - z;
x = (y + z)^2;
x = (y + z) + time;
end MyNonLinear;
If you translate it with the above flag active, Dymola will give this information in the translation tab of the message window:
Iteration variables:
y
When you additionally set a start value for x, (e.g. start=1) x becomes the iteration variable in this case.
Information on performed iterations
To get more information on the performed iterations, activate the Nonlinear solver diagnostics flags in the Debug tab of the Simulation Setup:
Dymola will then display additional information in the simulation log. Note that some of these flags can generate a log of output.
This is possible via a very lightly documented feature. See the 2019 FD01 release highlights for some limited info: https://www.3ds.com/fileadmin/PRODUCTS/CATIA/DYMOLA/PDF/Dymola-2019FD01-highlights.pdf
Specifically:
I'm a super beginner in Simulink models and control systems.
I have .slx Simulink model for drone dynamics system.
It takes in two inputs (roll cmd, pitch cmd) and outputs velocity x, velocity y, position x, and position y.
From here, it seems like I can open the system by calling
open_system('myModel.slx', 'loadable');
But how do I put inputs and get output values?
Is there a way I can do this in a gui?
EDIT:
Here is the full layout of my model:
When I did
roll_CMD=10;
pitch_CMD=20;
I got a warning saying:
Input port 1 of 'SimpleDroneDynamics/...' is not connected.
How do I feed inputs using port numbers?
How do I get outputs with port numbers? I tried
[vx, vy, px, py] = sim('SimpleDroneDynamics.slx');
and got an error saying
Number of left-hand side argument doesn't match block diagram...
Is there a way to continuously feed inputs at every time step? This being controller module, I think I'm supposed to feed in different values based on output position and velocity.
EDIT2:
I'm using Matlab2017a
About the first two points of your question:
In simulink:
For the inputs you can use a constant block and when you double click the input block you can assign a value, which can be a workspace variable.
To get the outputs to your workspace you can use the simout block (make sure to put Save format to array).
Connect inputs to your simulink model
Connect outputs of your simulink model to the simout blocks.
MATLAB script
clc;
clear all;
roll = 10;
pitch = 20;
sim('/path_to_simulinkmodel.slx')
time = simout(:,1);
velocity_X = simout(:,2);
velocity_Y = simout(:,3);
position_X = simout(:,4);
position_Y = simout(:,5);
About the third point of your question
You can define the duration of your simulation in the block diagram editor. You can put a variable which is defined in the calling script. There are multiple ways of achieving time dependent input variables:
One option I personally don't recommend is using a for-loop and calling the simulink model with a different value of roll and pitch
for i = 1:numberOfTimesteps
roll = ...
...
sim('simulinkModel.slx')
end
A second and more efficient approach is changing the constant blocks to other source blocks like ramp signals or sinusoid signals
First of all Simulink model use main Matlab workspace. So you can change your variables values at command window (or just at your script) and run Simulink model.
There are several ways to initialize this constants for Simulink. One more useful way is to create script containing all your variables and load it at Simulink model starts. You can do it by adding script name in Simulink/Model Explorer/Callbacks. (There are different callbacks - on Loading, on Starting and etc.). Read more about this: here.
Now you can run your simulation using sim function:
sim('name_of_model')
name_of_model must contain path if model is not in the active MATLAB folder (active folder you can see in your matlab window just under the main menu).
There are different properties of sim function, read about them in help this can be useful for you. By the way: you can change some parameters of your model using sim. You even can find any block in your model and change it's properties. Read more about sim and about finding current blocks. Interesting that the last solution give you ability to change parameters during the simulation!
About getting output. After you run simulation you get tout variable in main workspace. It is an array of timesteps. But if you add outport block (like at my image) you also get another variable in workspace yout. yout is an Datasets. It contain all your outports values. For 2 outports for example:
yout
yout =
Simulink.SimulationData.Dataset
Package: Simulink.SimulationData
Characteristics:
Name: 'yout'
Total Elements: 2
Elements:
1 : ''
2 : ''
Get the values of any of outports:
yout.get(1).Values
it is a timeseries data type, so:
yout.get(1).Values.Time - give you times
yout.get(2).Values.Data - give you values of this outport at each time
We have one more method to take output values:
[t,x,y] = sim('model_name')
it returns double arrays. t- time array, y - matrix of all outports values (it already double and contain only values without times, but for each simulation time!)
So now you can create common Matlab GUI and work at this variables! There is no any difficulties. You can read more about GUI for Simulink here.
I have a differential equation that's a function of around 30 constants. The differential equation is a system of (N^2+1) equations (where N is typically 4). Solving this system produces N^2+1 functions.
Often I want to see how the solution of the differential equation functionally depends on constants. For example, I might want to plot the maximum value of one of the output functions and see how that maximum changes for each solution of the differential equation as I linearly increase one of the input constants.
Is there a particularly clean method of doing this?
Right now I turn my differential-equation-solving script into a large function that returns an array of output functions. (Some of the inputs are vectors & matrices). For example:
for i = 1:N
[OutputArray1(i, :), OutputArray2(i, :), OutputArray3(i, :), OutputArray4(i, :), OutputArray5(i, :)] = DE_Simulation(Parameter1Array(i));
end
Here I loop through the function. The function solves a differential equation, and then returns the set of solution functions for that input parameter, and then each is appended as a row to a matrix.
There are a few issues I have with my method:
If I want to see the solution to the differential equation for a different parameter, I have to redefine the function so that it is an input of one of the thirty other parameters. For the sake of code readability, I cannot see myself explicitly writing all of the input parameters as individual inputs. (Although I've read that structures might be helpful here, but I'm not sure how that would be implemented.)
I typically get lost in parameter space and often have to update the same parameter across multiple scripts. I have a script that runs the differential-equation-solving function, and I have a second script that plots the set of simulated data. (And I will save the local variables to a file so that I can load them explicitly for plotting, but I often get lost figuring out which file is associated with what set of parameters). The remaining parameters that are not in the input of the function are inside the function itself. I've tried making the parameters global, but doing so drastically slows down the speed of my code. Additionally, some of the inputs are arrays I would like to plot and see before running the solver. (Some of the inputs are time-dependent boundary conditions, and I often want to see what they look like first.)
I'm trying to figure out a good method for me to keep track of everything. I'm trying to come up with a smart method of saving generated figures with a file tag that displays all the parameters associated with that figure. I can save such a file as a notepad file with a generic tagging-number that's listed in the title of the figure, but I feel like this is an awkward system. It's particularly awkward because it's not easy to see what's different about a long list of 30+ parameters.
Overall, I feel as though what I'm doing is fairly simple, yet I feel as though I don't have a good coding methodology and consequently end up wasting a lot of time saving almost-identical functions and scripts to solve fairly simple tasks.
It seems like what you really want here is something that deals with N-D arrays instead of splitting up the outputs.
If all of the OutputArray_ variables have the same number of rows, then the line
for i = 1:N
[OutputArray1(i, :), OutputArray2(i, :), OutputArray3(i, :), OutputArray4(i, :), OutputArray5(i, :)] = DE_Simulation(Parameter1Array(i));
end
seems to suggest that what you really want your function to return is an M x K array (where in this case, K = 5), and you want to pack that output into an M x K x N array. That is, it seems like you'd want to refactor your DE_Simulation to give you something like
for i = 1:N
OutputArray(:,:,i) = DE_Simulation(Parameter1Array(i));
end
If they aren't the same size, then a struct or a table is probably the best way to go, as you could assign to one element of the struct array per loop iteration or one row of the table per loop iteration (the table approach would assume that the size of the variables doesn't change from iteration to iteration).
If, for some reason, you really need to have these as separate outputs (and perhaps later as separate inputs), then what you probably want is a cell array. In that case you'd be able to deal with the variable number of inputs doing something like
for i = 1:N
[OutputArray{i, 1:K}] = DE_Simulation(Parameter1Array(i));
end
I hesitate to even write that, though, because this almost certainly seems like the wrong data structure for what you're trying to do.
I wanted to vectorize this piece of code. Is it possible to do this? I tried finding a solution, but I was not able to find any good result on google.
for pos=length1+1:length
X1(pos) = sim(net1, [demandPred(pos), demand(pos-1), X1(pos-1), X1(pos-2)]')';
X2(pos) = sim(net1, [demandPred(pos), demand(pos-1), X2(pos-1), X2(pos-2)]')';
end
Thanks in advance. :)
Edit 1:
The model which I am going to simulate is a simple GRNN.
net1 = newgrnn([demand(169:trainElem), demand(169-1:trainElem-1), X1(169 - 1:trainElem - 1), X1(169 - 2:trainElem - 2)]', 0.09);
Can Simulink models be vectorized? Sometimes.
Can your Simulink model be vectorised? It's impossible to tell without seeing the model -- and how it is being called from m-code (as you've shown in your question) is no indication.
An example of vectorization would be: consider a model with signal s1 that gets added to constant K, and assume that you need to run the models for different values if K. You could use a loop (like the m-code you show) and run the model for each individual required value for K. Alternatively, you can make K a vector, in which case all values would get added to s1 and the result would be a vector of signals s1+K(1), s1+K(2),..., s1+K(n), and the model only needs to be executed once for all of these summations to occur.
But, whether that sort of thing can be done in your model cannot be determined without seeing the model.