Simulink: designing a 2nd order sliding controller

In summary, the model that has been obtained for the slip controller issue includes the diffequation for the slip, the input that force the system to zero error, and the reference block. It is now time to implement the model in a software program such as Simulink or Matlab. The input required for the model is provided, and it is assumed that the dynamics of the slip is given by:where T is the input, g is a constant, R is the observed value, \lambda is the slip, and J is the inertia. The reference block is \lambda_desired, and SMC is used to get the input needed for the system.
  • #1
Payam30
46
1
Hi,
I've had obtained a mathematical model for the slip controller issue.
cwyNyiR.png

As you see I have the diffequation for the slip. and the input that force the system to zero error is provided as well. Now it's time to implement it in simulink or matlab.
I took a look at the example provided on mathwork. Here is a screen shot
SXq2FER.png

The controller is supposed to force \lambda to a certain value. The optimal input is provided as well. So the reference block should be \lambda_desired. That's correct and then it goes to SMC and it gives the input to the system. What is that system? is it the dynamics of the slip? I have only the dynamics in mathematical way and no transfer function. You see that the dynamics of the slip is:
ZQTA0Lg.png

where T is the input . g is constant. R supposed to be observed by a observer. \lambda is slip and J is inertia. \mu is friction and assumed to be constant. \omega is the rotational speed on the wheel. How do I convert this to transfer function. I really need help since I ve done a lot and stuck in this. Please help me with this.
 
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  • #2
I don't understand a lot of the specifics of your problem, but I have a general comment:
In many applications of Simulink, you do not know the transfer functions of some of the physics and they would be tremendously complicated. You use a Simulink diagram to implement the equations for the dynamics of the slip and run simulations to get results. There are tools to obtain Bode plots and estimate parameters.
 
Last edited:
  • #3
Thank you for your response.
As you see in the picture, the input should go to the dynamic. The dynamic of the slip is :
## \dot{\lambda} = (- \frac{g}{R\omega} + \frac{Rmg(\lambda -1)}{\omega J})\mu - \frac{(\lambda -1)}{\omega J}T##
So this is the case:
Reference value ---> SMC -----> dynamics --->output
the output will get feedback to the SMC. My question is. I don't have any transfer function of the dynamics so how do I do this? how to I implement the dynamics in simulink
 
  • #4
That equation for ##\dot{\lambda}## can be represented as a signal network with blocks for signal summing, multiplication, inversion, etc. Feed the result of that network into an integration block to obtain ##\lambda## and use that signal in the network as needed.
 
  • #5
You mean that I should solve the differential equation instead of using the transfer funktion? That could work...
 
  • #6
Yes. Simulink is used in a great number of simulations where the transfer function is not known but the equations can be represented in signal networks. It provides tools that can be used to analyse the system (Bode plots, etc.)
 
  • #7
You were right. I did following scheme:
Lo11xdN.jpg

The SMC is as following:
[tex] u = u_d - \frac{K}{b} sat(\frac{\sigma}{\theta}) [/tex]
I have actually problem with founding [itex] \theta [/itex]. This is the boundry thickness. anyone with insights in SMC.
 
  • #8
Solved. Thanks
 

1. What is Simulink and how is it used in designing a 2nd order sliding controller?

Simulink is a graphical programming environment used for modeling, simulating, and analyzing dynamic systems. It is commonly used in control system design. When designing a 2nd order sliding controller, Simulink allows for the creation of a block diagram representation of the system, making it easier to visualize and analyze the controller's performance.

2. What is a 2nd order sliding controller and how does it work?

A 2nd order sliding controller is a type of control system that uses sliding mode control to achieve robustness and stability in the face of changes or disturbances in the system. It works by continuously adjusting the control input based on the system's current state and the desired state, using a sliding surface to guide the control input towards the desired state.

3. What are the advantages of using a 2nd order sliding controller in system design?

There are several advantages to using a 2nd order sliding controller in system design. It is robust to disturbances and model uncertainties, meaning it can maintain stability and performance even in the presence of external factors. It also has a fast response time and can achieve precise control of the system, making it useful in applications where accuracy and speed are important.

4. Are there any limitations or drawbacks to using a 2nd order sliding controller?

While 2nd order sliding controllers have many advantages, there are also some limitations and drawbacks to consider. They can be more complex to design and implement compared to other control strategies, and they may require more tuning and adjustment to achieve optimal performance. Additionally, they may not be suitable for systems with highly nonlinear dynamics.

5. How can Simulink be used to optimize a 2nd order sliding controller?

Simulink offers various tools and features to help optimize a 2nd order sliding controller. These include built-in simulation and analysis tools, as well as the ability to easily modify and test different controller parameters and designs. Additionally, Simulink can be integrated with other optimization tools and techniques for more advanced and precise controller tuning.

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