NXT ROBOT Question

[TOOLMONKEY]

Can anybody help with the question below please

Using your LabView interface, input different values of power and record the output value of the number of wheel rotations. You can convert the latter into speed by measuring the diameter of the wheel. Then, type ‘ident’ in the command line of Matlab to launch a graphical user interface for system identification. Using the data collected for input power and recorded speed, you can derive the transfer function for your robot in the Laplace domain.

You will notice that it is possible to approximate the transfer function to a first order system.

Add disturbance to your system such as wind drag, road profile or friction. You might want to model the disturbance as a sinusoidal waveform.

Analyse the system response in LabView in order to tune the response.

Finally, write a LabView program to test your controller.

• Set both Integral and Derivative to 0
• Increase the value for Proportional controller to 0.5, 0.8, 1, 1.1, 1.3, and 1.5
• Select a suitable simulation stop time.
• Compare each simulation results and draw some conclusions.

Record the steady-state error. Has it dropped to near zero?

Record the rise time. Has it decreased to less than 0.5 second? And for what values of K_p?

Check whether this response is realistic i.e. a real cruise control system generally cannot change the speed of the vehicle from 0 to 10m/s in less than 0.5 second.

• Adjust the gain (K_p) to give a reasonable rise time and add an integral controller to eliminate the steady-state error.
• Change both K_p and K_i and see what happens to the response. When you adjust the integral gain K_i, start with a small value since a large K_i can destabilise the response. (K_i =0.001, 0.002, 0.003, 0.004).
• Then you need to adjust both the proportional gain K_p and the integral gain K_i to obtain the desired response. Record the values of K_p and K_i that can meet all the design criteria.

Write the PID-feedback control LabVIEW program as described above.

Check whether your system can stabilise speed to within 1%. What are the optimal PID parameters that you have found? Can you choose PID parameters to both reach the set speed quickly and also maintain the speed within good accuracy once the system has reached the set speed? Can you control the speed of small steps?

[TOOLMONKEY]

Using your LabView interface, input different values of power and record the output value of the number of wheel rotations. You can convert the latter into speed by measuring the diameter of the wheel. Then, type ‘ident’ in the command line of Matlab to launch a graphical user interface for system identification. Using the data collected for input power and recorded speed, you can derive the transfer function for your robot in the Laplace domain.

You will notice that it is possible to approximate the transfer function to a first order system.

Add disturbance to your system such as wind drag, road profile or friction. You might want to model the disturbance as a sinusoidal waveform.

Analyse the system response in LabView in order to tune the response.

Finally, write a LabView program to test your controller.

• Set both Integral and Derivative to 0
• Increase the value for Proportional controller to 0.5, 0.8, 1, 1.1, 1.3, and 1.5
• Select a suitable simulation stop time.
• Compare each simulation results and draw some conclusions.

Record the steady-state error. Has it dropped to near zero?

Record the rise time. Has it decreased to less than 0.5 second? And for what values of K_p?

Check whether this response is realistic i.e. a real cruise control system generally cannot change the speed of the vehicle from 0 to 10m/s in less than 0.5 second.

• Adjust the gain (K_p) to give a reasonable rise time and add an integral controller to eliminate the steady-state error.
• Change both K_p and K_i and see what happens to the response. When you adjust the integral gain K_i, start with a small value since a large K_i can destabilise the response. (K_i =0.001, 0.002, 0.003, 0.004).
• Then you need to adjust both the proportional gain K_p and the integral gain K_i to obtain the desired response. Record the values of K_p and K_i that can meet all the design criteria.

Write the PID-feedback control LabVIEW program as described above.

[TOOLMONKEY]

Check whether your system can stabilise speed to within 1%. What are the optimal PID parameters that you have found? Can you choose PID parameters to both reach the set speed quickly and also maintain the speed within good accuracy once the system has reached the set speed? Can you control the speed of small steps?

[RavensFan]

Duplicate Post.