Are Initial Conditions Ignored in Solving Control Systems Problems?

In summary, the conversation is about solving a control systems problem by converting a difference equation into a transfer function. The initial conditions are assumed to be zero and the goal is to get the system into a state space representation using the z transform. The matrices involved are typically referred to as A, B, C, and D, but in this case, G and H are being used instead. This method is correct according to the textbook being referenced.
  • #1
Lancelot59
646
1
I'm attempting to solve a control systems problem, however I'm stuck on the first step.

The system is specified with a difference equation:
[tex]y(k+2)+y(k+1)+0.16y(k)=u(k+1)+2u(k)[/tex]

So I need to convert this back onto the usual pulse transfer function form to use one of the standard methods of deriving the matrix.

The thing is I can't get to the transfer function. Due to the k shifts there are all of the initial condition constant terms such as z*y(0) that don't appear in the solutions at all.

Neither the problem or the solution specify that those conditions are zero. Are the initial conditions just being ignored, or am I missing something here?

Thanks!
 
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  • #2
By definition, a transfer function assumes zero initial conditions.

What matrix? Are you looking for the z transform?
 
  • #3
rude man said:
By definition, a transfer function assumes zero initial conditions.

What matrix? Are you looking for the z transform?

I need to get the whole system into some form of state space equation.

So I was going to take the z transform of that difference equation, then take the zeros and poles of that z domain transfer function to get the G and H matrices of the state space representation.
 
  • #4
Yes that is a correct method

note: I have always referred to the state space matrices as A,B,C & D.
I am assuming G & H are the system dynamics and input effects matrices respectivly
 
  • #5
donpacino said:
Yes that is a correct method

note: I have always referred to the state space matrices as A,B,C & D.
I am assuming G & H are the system dynamics and input effects matrices respectivly

Yes. For reference I'm using the Discrete Time Controls systems textbook by Ogata.
 

Related to Are Initial Conditions Ignored in Solving Control Systems Problems?

1. What is a control system?

A control system is a system of devices or processes that are designed to control, regulate, or manipulate other systems or processes in order to achieve a desired output or behavior.

2. What are the different types of control systems?

There are three main types of control systems: open-loop, closed-loop, and feedforward. Open-loop control systems have no feedback and rely solely on the input to produce the output. Closed-loop control systems use feedback to adjust the output based on the desired input. Feedforward control systems use a combination of open-loop and closed-loop control to anticipate and adjust for disturbances in the system.

3. What is the purpose of a control system?

The purpose of a control system is to maintain or regulate the output of a system or process in order to achieve a desired goal or behavior. Control systems are used in a variety of applications, from simple household appliances to complex industrial processes.

4. What are the components of a control system?

A control system typically consists of four main components: sensors, controllers, actuators, and feedback. Sensors measure the current state of the system, controllers process this information and determine the appropriate output, actuators carry out the desired action, and feedback provides information to the controller to adjust the output if needed.

5. What are the advantages of using a control system?

There are several advantages to using a control system, including increased efficiency, improved accuracy, and the ability to automate repetitive tasks. Control systems can also reduce human error and improve safety, particularly in complex or hazardous environments. Additionally, control systems can be optimized and fine-tuned for optimal performance, leading to cost savings and improved overall system performance.

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