mpc-horizon-tuning

To tune MPC horizon length for tension control, select a prediction horizon N in the middle range (e.g., 5–15 for a discrete-time loop with dt=0.01s) to balance tracking performance against computational effort. This ensures stable operation without excessive calculation.

Design MPC cost matrices Q and R by weighting Q to prioritize precise tension tracking and R to penalize actuator effort. Adjusting these matrices lets you balance system responsiveness against input energy consumption in web-handling control loops.

An LQR terminal cost ensures MPC stability in tension control by approximating the infinite-horizon optimal cost at the end of the prediction window. This strategy guarantees closed-loop stability for discrete-time R2R systems.

Yes, this MPC horizon tuning approach applies directly to real-world tension control scenarios including web-handling lines and robotic arms. It provides horizon selection and cost-design guidance for stable tension tracking.

For discrete-time tension control with dt=0.01s, a recommended horizon range is 5–15 steps based on your system's settling time. This selection aligns horizon length with dynamics to prevent computational overload.