Respondida
How to remove delay from idtf object?
You will need an invertible realization. Try high order transfer function estimations with no delays. Or, if the estimated model...

casi 4 años hace | 0

| aceptada

Respondida
Testing different optimization methods on a state space model by solving ODEs
The closest infrastructure to this style of numerical optimization approach is "grey box identification". See idgrey, idnlgrey, ...

casi 4 años hace | 0

| aceptada

Respondida
nlarx model initial conditions
You can prefix estimation data (both input and output signals) with nd zeros, where nd = maximum lag in the model. Initial condi...

casi 4 años hace | 0

| aceptada

Respondida
How to force tfest to estimate the process with "only real poles" ?
TFEST cannot guarantee real poles. If you can work with <=3 poles and <=1 zero, try PROCEST. This is a process model estimator...

casi 4 años hace | 3

| aceptada

Respondida
What is the difference between FRD and IDFRD
Both FRD and IDFRD are used to store Freqyency Response Data, that is, the complex frequency response vector (Mag.*exp(i*Phase))...

casi 4 años hace | 1

| aceptada

Respondida
How to estimate the parameter in a customized transfer function
Grey-box identification is an option. You will need to write a function that takes K0 and a0 as inputs, and returns state-space ...

casi 4 años hace | 0

Respondida
Minimum input data resolution
Look up Nyquist Sampling Theorem. If you are sampling (hopefully with anti-aliasing) at 1Hz then you cannot theoretically captur...

alrededor de 4 años hace | 0

| aceptada

Respondida
Well-identified fitted process model does not behave like data on simulink
You are almost there. Convert the model into state-space form and use it for simulation. For initial conditions, you will need t...

alrededor de 4 años hace | 0

| aceptada

Respondida
How to calculate the transfer function for a 16 input system?
Try also TFEST. Although you might want to reduce the number of inputs by PCA or PLS analysis.

alrededor de 4 años hace | 0

Respondida
nlarx model compare and predict (horizon kept 1) fit totally differs
The difference between (finite-horizon) prediction and simulation is a fundamental concept, something you could read books/artic...

alrededor de 4 años hace | 0

| aceptada

Respondida
Can nlgreyest() estimate open-loop unstable models?
With greyest, either parameterize K matrix using the ODE function, or choose to esitmate it separately by using the "Disturbance...

alrededor de 4 años hace | 0

Respondida
System Identification of Closed Loop Data and Unstable Plant
The first reference: [1] System Identification — Theory For the User, Lennart Ljung, Section 13.4-13.5, 2nd ed, PTR Prentice Ha...

alrededor de 4 años hace | 0

| aceptada

Respondida
Accessing the GUI function programatically.
I will repeat Aditya Baru's comment as an answer. The App now supports MATLAB code generation (creating a function from the tas...

alrededor de 4 años hace | 1

| aceptada

Respondida
How to set parameters of Recursive Polynomial Model Estimator in Simulink
The Recursive Polynomial Model Estimator supports single output estimations only.

alrededor de 4 años hace | 0

| aceptada

Respondida
System Identification - Frequency Domain
Make an attempt with stability enforced. opt = tfestOptions('EnforceStability', true); model=tfest(f_data,6,opt) Also, you ...

alrededor de 4 años hace | 2

| aceptada

Respondida
System Identification Toolboox error dialog
What dataset are you using for validation? Does it suply the inputs and outputs that the model needs?

alrededor de 4 años hace | 0

Respondida
Does the order (index) of inputs and outputs matter in MIMO system identification?
Yes the order matters since within a given noise level, there are many models that can explain the data. Settings related to sea...

alrededor de 4 años hace | 0

| aceptada

Respondida
System Identification Toolbox: How can we modify the starting parameters for the armax-algorithm?
You can set the A, B, C values explicitly, as in estimatedPolymodel.A = ARCoeff Or, call the IDPOLY constructor with A, B, C p...

alrededor de 4 años hace | 0

| aceptada

Respondida
How to identify a sytem by the System Identification Toolbox that is invertable ?
Tyically yes. If you are estimating state-space model, use "feedthough" name-value pair, as in ssest(Data, order, 'Feedthrough'...

alrededor de 4 años hace | 0

Respondida
how to convert a xls to a data ensemble for import into diagnostic feature app
If the data is not too big to fit into MATLAB memory, I would suggest importing it into MATLAB first as a set of tables or timet...

alrededor de 4 años hace | 0

Respondida
How can I find initial states for simulation?
Initial states show the effect of the environment on the system. They are not a property of the system to be determined uniquely...

alrededor de 4 años hace | 1

| aceptada

Respondida
System Identification toolbox: how to print estimated ARMA-coefficients for each iteration step in armax-algorithm
Use "full" display option, as in: opt=armaxOptions('Display','full'); estimatedPolymodel=armax(iddata(outputdata,inputdata,tsa...

alrededor de 4 años hace | 1

| aceptada

Respondida
how to use state space model?
If you want to reproduce the response of "predict" by (manual) simulation, you will need to generate the right prediction model ...

alrededor de 4 años hace | 1

Respondida
how to plot on the same bode plot a manual function plot() with function bode()?
You could try: G = frd(f1(w),w); % assuming f1(w) is a complex numeric vector bode(G,f2)

alrededor de 4 años hace | 0

Respondida
Residual analysis of 100% fit model using system identification toolbox
With simulated data with no noise, it is difficult to read the residual results since there is no baseline noise floor. That is,...

alrededor de 4 años hace | 0

| aceptada

Respondida
Fitting complex function to measurement values
Let X be your data matrix. [~,I]=unique(X(:,1),'stable'); h=X(I,2).*exp(1i*X(I,3)/180*pi); w=X(I,1)*2*pi; G=idfrd(h,w,'Ts',0...

alrededor de 4 años hace | 0

Respondida
MISO system identification tool box step response
Yes, use LSIM with input: U = [u, u], where u is a step signal.

alrededor de 4 años hace | 0

| aceptada

Respondida
Merging MISO ARX models
What you need is horizontal concatenation, not MERGE which is about statistical merger of identical (same I/Os and model structu...

alrededor de 4 años hace | 0

| aceptada

Respondida
How to Improve the computation speed for 'ARMAX' function?
If you have access to Parallel Computing Toolbox, you could consider replacing the for-loop with a "parfor" loop. Other things t...

alrededor de 4 años hace | 0

Respondida
How to estimate the inital state with an ssest output model
In short, you cannot. SSEST is a black-box identification function (unless you pass in a full initialized @idss model as input),...

alrededor de 4 años hace | 0

| aceptada