MyRoboPath
kinematics15 min readUpdated 2026-03-12Intermediate

PID Controller Tuning for Robotics: Practical Anti-Windup & Derivative Filtering

Step-by-step engineering guide to tuning Proportional-Integral-Derivative (PID) controllers for DC motors, robotic arm joints, and drone attitude with low-pass derivative filters.

Dr. Soraya Al-Mansoor
Dr. Soraya Al-Mansoor
Professor of Robotics & Nonlinear Control

Key Engineering Takeaways

  • Proportional gain (Kp) reduces rise time; Derivative gain (Kd) dampens overshoot; Integral gain (Ki) eliminates steady-state error.
  • Unconstrained integral accumulation when actuators saturate causes severe overshoot (Integral Windup). Always implement conditional clamping.
  • Raw numerical differentiation of noisy encoder or IMU data magnifies noise. Always apply a 1st-order low-pass filter to the derivative term.
Prerequisites
  • Basic differential calculus

The Continuous & Discrete PID Equation

The continuous time control output $u(t)$ is: $$u(t) = K_p e(t) + K_i \int_0^t e(\tau)d\tau + K_d \frac{de(t)}{dt}$$ In discrete digital firmware executing at fixed sampling time $\Delta t$: $$u[k] = K_p e[k] + K_i \sum_{j=0}^k e[j]\Delta t + K_d \frac{e[k] - e[k-1]}{\Delta t}$$
Tags:#PID#Control Systems#Anti-Windup#Derivative Filter#Tuning#Ziegler-Nichols