I have a PID controller working in simulink, but I want to pass it to C++ code. I found how to make a PID with code, something like this:
error = input - refeed;
iError += error * sampleTime;
dError = (error - lastError)/ sampleTime;
//PID Function
output = Kp * error + Ki * iError + Kd * dError;
refeed = output;
lastError = error;
But, that's the only clear thing I got in my research.
I need to know what's the next step, I have the transfer function discretized but I'm not sure about what should I do with the "z" parameters, the times, ...
Is it possible to pass manually a PID controller to C++? How?
The Temperature Control Lab passes a PID output from Python to an Arduino that runs C++ code through a serial USB interface. It is easier to plot values with Python than C++ if you can create an interface for your application. GitHub source code is here.
For the digital control systems, you need to sample the data and execute the controller at every sampling time. z-transform converts the continuous system to the discrete system.
For exampl, if your sampling time is '1', you can express a simple time-series model as below,
y(t) = a1*u(t-1) + a2*u(t-2)
--> y(t) = a1*z^-1*u(t) + a2*z^-2*u(t)
--> y(t) = A(z)u(t), where A(z) = a1*z^-1 + a2*z^-2
a1, a2 = FIR coefficients
However, this time-shift operator 'z^-1' does not appear in your code. It is implicitly expressed with your sampling-time and FOR or DO loop depending on the language that you are using.
Please see the python code for velocity form of PID controller. Velocity form is a little bit easier to implement because you don't worry about the additional logic for the anti-reset windup.
for i in range(1, ns): #ns = simulation time
# PID Velocity form
e[i] = sp[i] - pv[i]
P[i] = Kc * (e[i] - e[i-1])
I[i] = Kc*delta_t/tauI * (e[i])
D[i] = Kc*tauD/delta_t * (pv[i] - 2*(pv[i-1]) + pv[i-2])
op[i] = op[i-1] + P[i] + I[i] + D[i]
if op[i] < oplo or op[i] > ophi:
# clip output
op[i] = max(oplo,min(ophi,op[i]))
You can also find an example of a PID controller using a GEKKO package in the following link.
https://apmonitor.com/wiki/index.php/Main/GekkoPythonOptimization
Yes it is possible. Have you considered using someone else's code? Or do you want to write it yourself? If you have no problem using allready written code, check out Github. It has a lot of PID projects. For example PID-controller. It has a usage example and you only have to pass in your p, i and d parameters (which you allready got from Matlab).
Good luck!
Basically, you should send the values somewhere. Reading through the comments, you want to make a plot of the output variable in time, so I guess your best bet (and easier way) is to use gnuplot.
Basically, output the data in a text file, then use gnuplot to display it.
Related
I would like to use a convolution LSTM in my research but I'm having a difficult time figuring out the exact way to implement this class in tensorflow. Here is what I have so far. I get no errors, but I am seriously doubting my implementation. Can anyone confirm if I am doing this correctly?
n_input = 4
x = tf.placeholder(tf.float32,shape=[None,n_input,HEIGHT,WIDTH,2])
y = tf.placeholder(tf.float32,shape=[None,HEIGHT,WIDTH,2])
convLSTM_cell = tf.contrib.rnn.ConvLSTMCell(
conv_ndims=2,
input_shape = [HEIGHT,WIDTH,DEPTH],
output_channels=2,
kernel_shape=[3,3]
)
outputs, states = tf.nn.dynamic_rnn(convLSTM_cell, x, dtype=tf.float32)
weights = tf.Variable(tf.random_normal([3,3,2,2]))
biases = tf.Variable(tf.random_normal([2]))
conv_out = tf.nn.conv2d(outputs[-1],weights,strides=[1,1,1,1],padding='SAME')
out = tf.nn.sigmoid(conv_out + biases)
UPDATE:
printing the size of outputs gives the shape=(?,4,436,1024,2) but I think I want (?,5,436,1024,2) or (?,1,436,1024,2).
UPDATE2:
So according to a fellow lab mate, the 4 outputs corresponds to the lstm outputs for each frame and so it is working correctly. Apparently all I have to do is take output #4 and that is the predicted future time frame.
A stackoverflow confirmation would put my mind at ease on this whole thing.
Yes, you are correct!
The output dimension will match the input dimension. If you actually want the (?,5,436,1024,2) output, you will have to look at the history, state.h. the last four [-4] of it will still correspond to the output.
I am new to Python, coming from MATLAB, and long ago from C. I have written a script in MATLAB which simulates sediment transport in rivers as a Markov Process. The code randomly places circles of a random diameter within a rectangular area of a specified dimension. The circles are non-uniform is size, drawn randomly from a specified range of sizes. I do not know how many times I will step through the circle placement operation so I use a while loop to complete the process. In an attempt to be more community oriented, I am translating the MATLAB script to Python. I used the online tool OMPC to get started, and have been working through it manually from the auto-translated version (was not that helpful, which is not surprising). To debug the code as I go, I use the
MATLAB generated results to generally compare and contrast against results in Python. It seems clear to me that I have declared variables in a way that introduces problems as calculations proceed in the script. Here are two examples of consistent problems between different instances of code execution. First, the code generated what I think are arrays within arrays because the script is returning results which look like:
array([[ True]
[False]], dtype=bool)
This result was generated for the following code snippet at the overlap_logix operation:
CenterCoord_Array = np.asarray(CenterCoordinates)
Diameter_Array = np.asarray(Diameter)
dist_check = ((CenterCoord_Array[:,0] - x_Center) ** 2 + (CenterCoord_Array[:,1] - y_Center) ** 2) ** 0.5
radius_check = (Diameter_Array / 2) + radius
radius_check_update = np.reshape(radius_check,(len(radius_check),1))
radius_overlap = (radius_check_update >= dist_check)
# Now actually check the overalp condition.
if np.sum([radius_overlap]) == 0:
# The new circle does not overlap so proceed.
newCircle_Found = 1
debug_value = 2
elif np.sum([radius_overlap]) == 1:
# The new circle overlaps with one other circle
overlap = np.arange(0,len(radius_overlap), dtype=int)
overlap_update = np.reshape(overlap,(len(overlap),1))
overlap_logix = (radius_overlap == 1)
idx_true = overlap_update[overlap_logix]
radius = dist_check(idx_true,1) - (Diameter(idx_true,1) / 2)
A similar result for the same run was produced for variables:
radius_check_update
radius_overlap
overlap_update
Here is the same code snippet for the working MATLAB version (as requested):
distcheck = ((Circles.CenterCoordinates(1,:)-x_Center).^2 + (Circles.CenterCoordinates(2,:)-y_Center).^2).^0.5;
radius_check = (Circles.Diameter ./ 2) + radius;
radius_overlap = (radius_check >= distcheck);
% Now actually check the overalp condition.
if sum(radius_overlap) == 0
% The new circle does not overlap so proceed.
newCircle_Found = 1;
debug_value = 2;
elseif sum(radius_overlap) == 1
% The new circle overlaps with one other circle
temp = 1:size(radius_overlap,2);
idx_true = temp(radius_overlap == 1);
radius = distcheck(1,idx_true) - (Circles.Diameter(1,idx_true)/2);
In the Python version I have created arrays from lists to more easily operate on the contents (the first two lines of the code snippet). The array within array result and creating arrays to access data suggests to me that I have incorrectly declared variable types, but I am not sure. Furthermore, some variables have a size, for example, (2L,) (the numerical dimension will change as circles are placed) where there is no second dimension. This produces obvious problems when I try to use the array in an operation with another array with a size (2L,1L). Because of these problems I started reshaping arrays, and then I stopped because I decided these were hacks because I had declared one, or more than one variable incorrectly. Second, for the same run I encountered the following error:
TypeError: 'numpy.ndarray' object is not callable
for the operation:
radius = dist_check(idx_true,1) - (Diameter(idx_true,1) / 2)
which occurs at the bottom of the above code snippet. I have posted the entire script at the following link because it is probably more useful to execute the script for oneself:
https://github.com/smchartrand/MarkovProcess_Bedload
I have set-up the code to run with some initial parameter values so decisions do not need to be made; these parameter values produce the expected results in the MATLAB-based script, which look something like this when plotted:
So, I seem to specifically be having issues with operations on lines 151-165, depending on the test value np.sum([radius_overlap]) and I think it is because I incorrectly declared variable types, but I am really not sure. I can say with confidence that the Python version and the MATLAB version are consistent in output through the first step of the while loop, and code line 127 which is entering the second step of the while loop. Below this point in the code the above documented issues eventually cause the script to crash. Sometimes the script executes to 15% complete, and sometimes it does not make it to 5% - this is due to the random nature of circle placement. I am preparing the code in the Spyder (Python 2.7) IDE and will share the working code publicly as a part of my research. I would greatly appreciate any help that can be offered to identify my mistakes and misapplications of python coding practice.
I believe I have answered my own question, and maybe it will be of use for someone down the road. The main sources of instruction for me can be found at the following three web pages:
Stackoverflow Question 176011
SciPy FAQ
SciPy NumPy for Matlab users
The third web page was very helpful for me coming from MATLAB. Here is the modified and working python code snippet which relates to the original snippet provided above:
dist_check = ((CenterCoordinates[0,:] - x_Center) ** 2 + (CenterCoordinates[1,:] - y_Center) ** 2) ** 0.5
radius_check = (Diameter / 2) + radius
radius_overlap = (radius_check >= dist_check)
# Now actually check the overalp condition.
if np.sum([radius_overlap]) == 0:
# The new circle does not overlap so proceed.
newCircle_Found = 1
debug_value = 2
elif np.sum([radius_overlap]) == 1:
# The new circle overlaps with one other circle
overlap = np.arange(0,len(radius_overlap[0]), dtype=int).reshape(1, len(radius_overlap[0]))
overlap_logix = (radius_overlap == 1)
idx_true = overlap[overlap_logix]
radius = dist_check[idx_true] - (Diameter[0,idx_true] / 2)
In the end it was clear to me that it was more straightforward for this example to use numpy arrays vs. lists to store results for each iteration of filling the rectangular area. For the corrected code snippet this means I initialized the variables:
CenterCoordinates, and
Diameter
as numpy arrays whereas I initialized them as lists in the posted question. This made a few mathematical operations more straightforward. I was also incorrectly indexing into variables with parentheses () as opposed to the correct method using brackets []. Here is an example of a correction I made which helped the code execute as envisioned:
Incorrect: radius = dist_check(idx_true,1) - (Diameter(idx_true,1) / 2)
Correct: radius = dist_check[idx_true] - (Diameter[0,idx_true] / 2)
This example also shows that I had issues with array dimensions which I corrected variable by variable. I am still not sure if my working code is the most pythonic or most efficient way to fill a rectangular area in a random fashion, but I have tested it about 100 times with success. The revised and working code can be downloaded here:
Working Python Script to Randomly Fill Rectangular Area with Circles
Here is an image of a final results for a successful run of the working code:
The main lessons for me were (1) numpy arrays are more efficient for repetitive numerical calculations, and (2) dimensionality of arrays which I created were not always what I expected them to be and care must be practiced when establishing arrays. Thanks to those who looked at my question and asked for clarification.
I am new to matlab, and coding is not my job, I just use it for some side projects. So I don't really know what I am talking about, and I hope you'll understand that :)
So I installed matlab on my computer and would like to use its libraries to plot some very simple graphs during the execution of my code (histograms, scatter plots, whatever). Plotting those graphs is not the first purpose of my code, I just find that easier to plot them during the execution rather than exporting them as a CSV file, and then plotting manually through excel.
Question: I managed to make visual C++ "communicate" with matlab. I am passing some data using arrays, but I'd also like to pass a string (a path such as "C:\test\") as I'd like to automatically save those graphs once generated into a precise directory. I haven't found any way of doing it so far.
Here is a bit of my c++ code, which is really simple:
Engine *ep;
ep = engOpen(NULL);
double *ArrayOne;
double *ArrayTwo;
const int Asize = Area.size();
ArrayOne = new double[Asize];
ArrayTwo = new double[Asize];
for (int i = 0; i <= Area.size() - 1; i++) {
ArrayOne[i] = Area[i][1];
ArrayTwo[i] = Area[i][2]
}
mxArray* ONE = mxCreateDoubleMatrix(Asize, 1, mxREAL);
memcpy((void*)mxGetPr(ONE), (void*)ArrayOne, sizeof(double)*Asize);
engPutVariable(ep, "one", ONE);
mxArray* TWO = mxCreateDoubleMatrix(Asize, 1, mxREAL);
memcpy((void*)mxGetPr(TWO), (void*)ArrayTwo, sizeof(double)*Asize);
engPutVariable(ep, "two", TWO);
engEvalString(ep, "plottest");
delete[]ArrayOne;
delete[]ArrayTwo;
engClose(ep);
And the file Plottest.m:
h1= histogram(one);
h1.EdgeColor = 'black';
h1.FaceColor = 'white';
hold on;
h2 = histogram(two);
h2.EdgeColor = 'blue';
h2.FaceColor = [0.5 0.5 0.5];
alpha(h1,.5);
alpha(h2,.8);
saveas(gcf,'C:\PhD\SVG2GMSH\SVG\test.png');
How can I replace my hard coded path into my m file ("C:\PhD\SVG2GMSH\SVG\test.png") by a more elegant variable that would contain it ?
Thank you for your help. Also, let me know if you have any other suggestions in order to make my code look/work better :)
Flo
I don't see what benefit a variable would bring when you'd only need to update the value of the variable anyway.
Your best bet is to use a relative path: saveas(gcf, 'test.png') then the file is taken from the current working directory. The documentation doesn't actually outright state this, but it's basically how computers work, so… give it a go!
I have a Matlab script that I'm trying to convert to C++ (see below) because it is extremely slow. I'm a C++ newbie and to start I tried using codegen but it doesn't work (I got the message ??? This text contains non-empty top-level expressions. It appears to be a script.)
Do you have any suggestion on how to start to convert the code? Also, what is the best C++ function to do the job of fitsread?
Here is my code:
clear;
number_projections = 10;
imgs_per_proj = 2000; % Number of images per projection
% Lets load the reference images relative to the various wavelengths
R1 = zeros(imgs_per_proj, 512, 512);
R2 = zeros(imgs_per_proj, 512, 512);
l = 0;
for k = 1:imgs_per_proj
s = sprintf('Ref/R1_000_%05i.fits',k-1);
t = sprintf('Ref/R2_000_%05i.fits',k-1);
l = l + 1;
R1(l,:,:) = fitsread(s);
R2(l,:,:) = fitsread(t);
end
codegen requires that the MATLAB code you're trying to convert be in a function and it seems you are trying to convert a script
However, even if you do that, fitsread does not appear to be a supported function within codegen. Here's a list of supported functions:
http://www.mathworks.com/help/simulink/ug/functions-supported-for-code-generation--alphabetical-list.html
There's no "built-in" function within C++ that's going to replace fitsread - for that you need a library. There's a C++ FITS library called CCFits that you can find here: http://heasarc.gsfc.nasa.gov/fitsio/CCfits/
They should have tutorials that you could follow.
I'm programming a Steinberg VST-Plugin in XCode 4.6.
I've already implemented a Highpass-filter which works correctly. Now I'm trying to do some nonlinear distortion with a quadratic function. After I implemented the few lines below and loaded the plugin into the host, I get immediatly an Output from the plugin - you can hear nothing, but the meter is up high.
I really can't imagine why. The processReplacing function where the math takes place should only be called when playing sound, not when the plugin is loaded. When I remove the few lines of code below, everything is okay and sounds right, so I assume it has nothing to do with the rest of the plugin-code.
The problem takes place in two hosts, so its probably not a VST-bug.
Has anybody ever experienced a similar problem?
Many Thanks,
Fabian
void Exciter::processReplacing(float** inputs, float** outputs, VstInt32 sampleFrames){
for(int i = 0; i < sampleFrames; i++) {
tempsample = inputs[0][i];
//Exciter - Transformation in positive region, quadratic distortion and backscaling
tempsample = tempsample + 1.0f;
tempsample = powf(tempsample, 2.0f);
tempsample = tempsample / 2.0f;
tempsample -= 1.0f;
//Mix-Knob: Dry/Wet ------------------------------------------------
outputs[0][i] = mix*(tempsample) + (1-mix)*inputs[0][i];
EDIT: I added logfile-outputs to each function and it occurs, that the processReplacing function is called permanently, not only when playback is turned on ... But why?
You pretty much answered the question yourself with your edit. processReplacing is called repeatedly. This is part of the VST specification.
VST plug-ins are targeted for real time effects processing. Don't confuse or misinterpret this as lookahead. By real time, I mean inserting the plug-in into a channel and playing an instrument while the DAW is recording. So you can see that in order to mitigate latency, the host is always sending the plug-in an audio buffer (whether it's silence or not).