Control of Mechatronic Systems

From transfer functions to servo axes. Transfer functions, PID control and practical tuning, and servo motion control with trajectories, cascaded loops and feedforward.

• Transfer Functions — Transfer functions describe a linear system's input–output behaviour in the Laplace domain. Learn how to derive them, poles and zeros, first- and second-order systems, time-domain specs and the final-value theorem.
• PID Control — The PID controller is used in over 90 % of industrial loops. Learn what P, I and D each do, tuning with Ziegler–Nichols and practical rules, anti-windup, derivative filtering and a digital implementation.
• PID Tuning & Digital Implementation — Making PID work on real plants. Learn PID forms (ideal, parallel, series), tuning methods (Ziegler–Nichols open and closed loop, Cohen–Coon, IMC/lambda, SIMC), derivative filtering and derivative-on-measurement, setpoint weighting, integral windup and anti-windup, bumpless transfer, discretisation and sample time — with a full discrete PID simulator in Python comparing Z-N and SIMC tuning.
• Servo Motion Control: Trajectories & Cascaded Loops — Making axes move precisely and smoothly. Learn motion profiles (trapezoidal, S-curve, jerk limits), cascaded current–velocity–position loops and why each is faster than the next, tuning procedures, feedforward (velocity, acceleration, friction), following error, multi-axis coordination (interpolation, electronic gearing and camming), resonance and notch filters, and motion controllers and networks — with Python for profiles and a cascaded-loop simulation.