controlparameter

A control parameter is a tunable value within a controller that determines how the controller reacts to errors between a desired reference signal and the measured process variable. In classical feedback control, these parameters define the control law that translates error into a control action.

A common example is the PID controller, where the gains Kp, Ki, and Kd are control parameters. Other controllers have parameters such as the horizon length and weighting matrices in model predictive control, or the break frequencies in lead/lag compensators. These parameters are selected to shape the controller’s behavior.

The choice of control parameters influences transient performance (rise time, settling time, overshoot), steady-state error, energy or actuation usage, and robustness to disturbances and model uncertainty. They are distinct from physical plant parameters (such as mass, inertia, or resistance) and from the reference signal; they are adjusted to achieve a desired performance profile.

Tuning methods range from manual adjustment and heuristic rules (for example, Ziegler–Nichols or Cohen–Coon) to systematic approaches based on system models, frequency response, or optimization. Adaptive and self-tuning controllers modify parameters online in response to observed performance, and gain scheduling adjusts parameters according to operating conditions.

In software and automation contexts, control parameters are often exposed as configurable knobs or learned by data-driven or reinforcement learning methods. Proper tuning is essential for achieving stable operation, acceptable response characteristics, and robust performance under disturbances.