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Robot%20Sensors

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Robot Sensors Kevin Watson and Rich Petras Overview Sensors Micro Switch Gyro Encoders Command Sequencing PID Control MicroSwitch Digital input Be sure to set as an ... – PowerPoint PPT presentation

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Title: Robot%20Sensors


1
Robot Sensors
  • Kevin Watson
  • and
  • Rich Petras

2
Overview
  • Sensors
  • Micro Switch
  • Gyro
  • Encoders
  • Command Sequencing
  • PID Control

3
MicroSwitch
  • Digital input
  • Be sure to set as an input in User_Initialization(
    )

4
Encoders
  • Kinds
  • Mechanical
  • Optical
  • Types of output
  • Resolution

5
Gyros
  • Types
  • Mechanical
  • Ring Laser
  • MEMS
  • Using
  • Bias
  • Drift
  • Integration

6
Command Sequencing
  • Why do we want to do this?
  • How does it work?
  • Robot example....

7
What is PID Control ?
  • PID control can be used any time you have a
    variable that you want to control and a way of
    measuring that variable.

8
P I D
  • P - Proportional - The amount of control is based
    on (proportional to) the error between where we
    want to be and where we are.
  • I - Integral - The amount of control is based on
    the total error over time - the summation or
    integral
  • D - Differential - The amount of control is based
    on how fast the error is changing - the
    difference.

9
What are Gains ?
  • The gains tell you how important each of the PID
    terms are.
  • Kp - Proportional Gain - Determines how fast your
    system reacts to error
  • Ki - Integral Gain - Determines how hard your
    system will push to overcome error.
  • Kd - Differential Gain - Limits the change in
    response to error. Helps to dampen or smooth the
    reactions.

10
How do I Tune my System ?
  • Start by setting the gains low. You can set Ki
    and Kd to zero to start.
  • Increase Kp until the system starts to react
    quickly enough. It will overshoot if you set it
    too high.
  • Now increase Kd to compensate for overshoot. Now
    the system should react smoothly.

11
How do I Tune my System ?
  • But you might notice that it never reaches the
    goal. That is because resistance in the system
    is holding it back and as you near the goal, the
    proportional term gets smaller.
  • Now it is time to increase Ki. Over time the
    error will build and the I term allows the system
    to overcome resistance.
  • Now go back and adjust each of the terms to get
    the response you want.
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