Time response for optimal tracking problem

In summary, to plot the time response for an optimal tracking problem, you will need to define the system, calculate the feedback gain, and use it to calculate the closed loop matrix. Then, define the state space model with the initial condition and plot the time response using the lsim function in MATLAB.
  • #1
sbashrawi
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Homework Statement

Hi guys
I want to know how to plot time responce for optimal tracking problem.
I have the following information
state equation
dx = AX+Bu
Y =Cx
want to track a comand z= [z1;z2] constant
I know that we need to find the feedback gain by
sys= ss(A,B,C,D)
[K,S,E] = lqr(sys,Q,R)
the initial condition is given
closed loop matrix is given by A_closed = A - B*K

HOw can I use these information: A_cloosed, Z , initial contion to plot the time response
in matalb ?

Any help please

Homework Equations


The Attempt at a Solution

 
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  • #2
Assuming you are familiar with the MATLAB syntax, you can use the following commands to plot the time response of your system.First, define the system: sys = ss(A,B,C,D);Next, calculate the feedback gain K: [K,S,E] = lqr(sys,Q,R);After that, calculate the closed loop matrix A_closed: A_closed = A - B*K;Then, define the state space model with the initial condition: x0 = [x10;x20]; % initial conditionmodel = ss(A_closed,B,C,D,x0);Finally, plot the time response: t = 0:0.01:10; % time vectorz = [z1;z2]; % command signal[y,t] = lsim(model,z,t);plot(t,y);
 

FAQ: Time response for optimal tracking problem

What is the definition of "time response" in the context of optimal tracking problem?

The time response refers to the behavior of a system over time in response to a given input. In the context of optimal tracking problem, it refers to the ability of a system to accurately track a desired output over time.

How is the time response for optimal tracking problem evaluated?

The time response for optimal tracking problem is evaluated by measuring the system's performance in terms of its ability to track the desired output, as well as its speed and accuracy in doing so. This can be quantified using metrics such as rise time, settling time, and steady-state error.

What factors influence the time response for optimal tracking problem?

The time response for optimal tracking problem is influenced by various factors, such as the system's design, the type of control algorithm used, the characteristics of the input signal, and external disturbances. Additionally, the choice of performance metrics and the desired level of accuracy also play a role in determining the time response.

How can the time response for optimal tracking problem be improved?

The time response for optimal tracking problem can be improved by optimizing the system design, using advanced control algorithms, and implementing feedback control to compensate for disturbances. Additionally, using performance metrics and tuning the system parameters can also help improve the time response.

Can the time response for optimal tracking problem be predicted?

While the time response for optimal tracking problem can be estimated using mathematical models and simulations, it is difficult to predict it with complete accuracy due to the presence of uncertainties and external disturbances. However, by using advanced control techniques and continuously monitoring and adjusting the system, the time response can be improved and brought closer to the desired performance.

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