How to make block arrangements in Simulink to convolute 2 continuous input signal?
For some reason, I have to be able to reset the convolute integral accumulation. Hence, I can't use the conv block in Simulink. Nor can't I use a transfer function block.
This is what I have tried so far. But it only match with the conv block for the first 0.5 second. It then jumps up and down randomly. I know that the implementation I have tried is not continuous, but I don't know how to implement it continuously: whether it is possible to integrate with respect to some other variable other than time in Simulink.
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For example, I have a controller consisting of integrator and sine web signal combined in the input. My question may be very naive to you, please help me to understand.
In the picture I have a frequency which is the input of an integrator then two cos and sine block. How to make each Simulink block discrete using ZOH and rate transition block in Simulink.
Two potential solutions
Change the sample time of the sinewave to something that is non-zero. This will make it a discrete signal
Use a Zero Order Hold (as you've mentioned) to convert the signal to discrete, you will need to specify a sample time for this block to perform the conversion. Setting the time to 0.5 will sample the signal every half second for example.
I've been trying to use Simulink for modelling an oscilloscope (including DSP). I am still very novice so please forgive me if the following question is way too easy: How do I implement AC coupling (remove DC component) in Simulink while using analog signals? I know there is a DC blocker, but it only accepts discrete signals and I want to discretize my signal later with an imperfect ADC.
I'm trying to use a MATLAB function for the AC coupling, but I cannot find a way to use the existing analog signal gained from the function declaration. Instead, all MATLAB documentary seems to want me to use an analog device on my computer (https://mathworks.com/help/daq/analog-data-acquisition.html).
Thank you for any efforts and/or suggestions! :)
I don't think using the Matlab Function Block will work since you need to hold a state. To simulate AC coupling, I believe that you need to create a high pass filter. This removes DC from the signal so that the waveform is centered around zero. The corner frequency generally needs to be very low so that there is no distortion of the waveform being measured. You can build this without any special toolboxes. You just need an integrator block, gain block and some summation blocks.
An example is provided below:
This example applies a DC step to the waveform at 1 second. The figure below provides the output
In the upper figure (input) the offset remains, but in the lower figure (output) the offset is removed.
If you want using the matlab AC Coupling function, try using the Matlab Function Block : https://fr.mathworks.com/help/simulink/ug/creating-an-example-model-that-uses-a-matlab-function-block.html . You can use it like any matlab function, i.e. function [out1, out2] = my_function(in1) but it will be defined in a simulink block.
I want to be able to externally have inputs for the lower passband edge frequency and higher passband edge frequencies for the butterworth filter block in the simulink signal processing toolbox in matlab. How can I achieve this. Currently you'll have to click the block to specify these frequencies and this is not possible at runtime.
Regards,
Alfred
Basically you are asking for a filter that has time varying parameters. The Butterworth filter block does not allow for this, and cannot be modified to do so, so you are going to have to roll your own. This can be achieved in several ways:
Determining the difference equations that you need to implement, then creating a filter out of fundamental blocks (product, summation and unit delay blocks) where the "parameters" you want to change are fed into the product blocks as signals.
Using a block such as Transfer Fcn Direct Form II Time Varying. (This assumes you can parameterize the changes you need as a gain-scheduled signal.)
Write an S-Function (or perhaps a MATLAB Function block) to implement any detailed/specific functionality.
I believe I am doing something fundamentally wrong when trying to import and test a transfer function in Simulink which was created within the System Identification Toolbox (SIT).
To give a simple example of what I am doing.
I have an input which is an offset sinusoidal wave from 12 seconds to 25 seconds with an amplitude of 1 and a frequency of 1.5rad/s which gives a measured output.
I have used SIT to create a simple 2 pole 1 zero transfer function which gives the following agreement:
I have then tried to import this transfer function into Simulink for investigation in the following configuration which has a sinusoidal input of frequency 1.5rad/s and a starting t=12. The LTI system block refers to the transfer function variable within the workspace:
When I run this simulation for 13 seconds the input to the block is as expected but the post transfer function signal shows little agreement with what would be expected and is an order of magnitude out.
pre:
post:
Could someone give any insight into where I am going wrong and why the output from the tf in simulink shows little resemblance to the model output displayed in the SIT. I have a basic grasp of control theory but I am struggling to make sense of this.
This could be due to different initial conditions used in SimuLink and the SI Toolbox, the latter should estimate initial conditions with the model, while Simulink does nothing special with initial conditions unless you specify them yourself.
To me it seems that your original signals are in periodic regime, since your output looks almost like a sine wave as well. In periodic regime, initial conditions have little effect. You can verify my assumption by simulating your model for a longer amount of time: if at the end, your signal reaches the right amplitude and phase lag as in your data, you will know that the initial conditions were wrong.
In any case, you can get the estimated initial state from the toolbox, I think using the InitialState property of the resulting object.
Another thing that might go wrong, is the time discretization that you use in Simulink in case you estimated a continuous time model (one in the Laplace variable s, not in z or q).
edit: In that case I would recommend you check what Simulink uses to discretize your CT model, by using c2d in MATLAB and a setup like the one below in Simulink. In MATLAB you can also "simulate" the response to a CT model using lsim, where you have to specify a discretization method.
This set-up allows you to load in a CT model and a discretized variant (in this case a state-space representation). By comparing the signals, you can see whether the discretization method you use is the same one that SimuLink uses (this depends on the integration method you set in the settings).
I have a Simulink model that includes the following subsystem.
The bm_train_adapter block will call a MATLAB function of the same name, passing all the input arguments in a single vector.
The subsystem has been given a sample time of 900 (secs), which is why all the signals are colored in red (for discrete signals).
However, in the debugger I have observed that the bm_train_adapter function gets called twice at each simulation timestep. This yields horribly wrong results since the function includes side-effects.
Why is Simulink calling my interpreted MATLAB function more than once per timestep? How can I prevent this?
I think this is because of your solver setup. In your Configuration Parameters window, check out the Solver Options pane.
I believe the discrete and ode1 solvers will call once per timestep. ode2 will call twice per timestep, ode4 will call 4 times per timestep, etc.
This behavior is very helpful for simulating continuous dynamics, but it can be confusing when interacting with discrete elements.
The reason was that my model had algebraic loops caused by unit delay blocks in subsystems. To solve these loops, the solver had no choice but to evaluate some blocks more than once.
The solution was to move out all unit delays from their subsystems.