ClosedLoopSteuerung

ClosedLoopSteuerung, commonly referred to as closed-loop control, is a method in which the output of a system is measured and compared with a desired reference value. The difference, or error, is fed into a controller that acts on the input to the plant to reduce the error. A typical closed-loop system consists of a reference input, a controller, the plant (the process to be controlled), a sensor to measure the output, and a feedback path that returns the measured output to the summing junction.

The controller can be a PID controller, which combines proportional, integral and derivative terms, but other approaches exist, including lead/lag compensators, adaptive controllers and model predictive control. Closed-loop control can be implemented in continuous time or discrete time, depending on whether the controller operates in real time on analog signals or on digital samples.

Advantages include improved tracking of the reference, disturbance rejection, and robustness to parameter variations. Drawbacks include the need for sensors and actuators, potential measurement noise amplification, and the possibility of instability or poor performance if the loop is poorly tuned or if the model is inaccurate.

Common applications are in industrial process control, robotics, automotive systems such as cruise control, electrical drives, and HVAC. Design often uses state-space or transfer-function representations and stability analysis such as Nyquist, Bode plots, or discrete-time methods. Performance is characterized by metrics like settling time, overshoot, rise time, and steady-state error.

Historically, closed-loop control emerged to compensate for disturbances and parameter changes in mechanical and electrical systems, evolving from simple servos and feedback amplifiers to modern digital controllers. The concept remains central to automation and control engineering.