State space representations for different system configurations

In summary: Your Name]In summary, the problem at hand involves converting two systems' state space representations into s-domain, combining them and then converting the result back to the time domain. The suggested approach is to use the inverse Laplace transform to derive the state representation from the output. Another approach is to use the transfer function of each system to determine the overall transfer function for the combined system. The advice is to use the suggested methods and if there are any further questions, do not hesitate to ask for help.
  • #1
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Homework Statement


Homework Equations



This is the problem that I am trying to solve.

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The Attempt at a Solution



https://docs.google.com/file/d/0B0Wxm870SWTNV0xjdmVRc09TTm8/edit

The approach of solving this problem is to first convert the two systems' state space representations into s-domain, combine them, then finally convert the final result back to the frequency domain. I am stuck; I can find the output, y, but I don't know how do I derive the state representation from the output. Is my approach correct? or do I need to use another approach? Any suggestion will be appreciated; thank you in advance!
 
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  • #2


Thank you for sharing your problem and approach with us. It seems like you are on the right track by converting the systems into s-domain and combining them. However, in order to derive the state representation from the output, you will need to use the inverse Laplace transform. This will allow you to convert the combined s-domain representation back to the time domain, where you can then manipulate the equations to solve for the state variables.

Another approach you could consider is using the transfer function of each system to determine the overall transfer function for the combined system. This would involve multiplying the transfer functions together and then converting the result back to the time domain using the inverse Laplace transform.

I hope this helps and good luck with your problem solving! If you have any further questions, please don't hesitate to ask.
 

FAQ: State space representations for different system configurations

What is a state space representation?

A state space representation is a mathematical model that describes the behavior of a system over time. It uses a set of differential equations to represent the relationships between the system's inputs, outputs, and internal states.

Why is it important to use state space representations for different system configurations?

State space representations allow us to analyze and predict the behavior of a system in different configurations. This is important because it helps us understand how the system will respond to different inputs and how it can be controlled or optimized.

What are the advantages of using state space representations?

State space representations have several advantages over other modeling techniques. They are more flexible, can handle nonlinear systems, and can easily incorporate time-varying inputs. They also provide a clear visual representation of the system's behavior.

How do you construct a state space representation for a system?

To construct a state space representation, you first need to determine the system's inputs, outputs, and internal states. Then, you can use the system's equations to form a set of differential equations. These equations can be put into matrix form to create the state space representation.

Can state space representations be used for any type of system?

Yes, state space representations can be used for a wide range of systems, including mechanical, electrical, and chemical systems. They can also be used for both continuous and discrete-time systems.

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