Behavior:PID Control

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PID Control
Type Behavior (Algorithm)
Requires Capabilities Any sensing capability that provides error measurement
Enables Activities Activity:Line Following (smooth), precise position control, speed control
Difficulty Intermediate
Status Stub - Algorithm not yet implemented


PID Control is a behavior (algorithm) that uses proportional, integral, and derivative terms to minimize error in control systems.

Overview

This is a stub page. This behavior is not yet implemented in any BRS robot. This page exists to:

  • Document the algorithmic concept
  • Invite community members to implement it
  • Provide a starting point for algorithm design

Required Capabilities

This behavior requires:

Enables Activities

Implementing this behavior enables:

Algorithm Outline

PID control is a feedback loop that continuously calculates an error value and applies a correction:

  • **P (Proportional)**: Correction proportional to current error
  • **I (Integral)**: Correction based on accumulated past errors
  • **D (Derivative)**: Correction based on rate of error change

The output is: output = Kp × error + Ki × ∫error·dt + Kd × d(error)/dt

Pseudocode

# PID Controller
error = setpoint - measured_value
integral = integral + error * dt
derivative = (error - previous_error) / dt

output = Kp * error + Ki * integral + Kd * derivative

previous_error = error
apply_output(output)

Implementation Challenges

  • **Tuning**: Finding optimal Kp, Ki, Kd values requires experimentation
  • **Integral windup**: Integral term can accumulate excessively
  • **Derivative noise**: Derivative is sensitive to sensor noise
  • **Sampling rate**: PID requires consistent timing for accurate integral/derivative

Contributing

Want to implement this behavior? Here's how:

  1. Study the algorithm outline above
  2. Implement in your language of choice (MicroPython, C++, Arduino)
  3. Test on a robot with the required capabilities
  4. Create an Implementation page (e.g., YourRobot:PID Control Implementation)
  5. Update this page with algorithm refinements
  6. Share working code on GitHub

See Also