The controlled plant is the part of a control theory model that receives the control input and produces the plant output, including the mechanism that applies the command. The controller is specified separately. In the illustrative ordinary differential equation , the controlled plant accumulates the control input and control disturbance; it does not itself choose .
A plant input is a signal supplied to the controlled plant. The chosen plant input is its control input; other influences can enter as control disturbances. This use concerns a dynamical system, rather than the input of a computation.
A plant output is a quantity exposed by the controlled plant, often modeled as . In the illustrative model it is . An output of a computation has a different meaning.
The measured output is the information about the plant output available to the controller. It may differ from the actual plant output because of measurement noise or feedback delay. In the ideal examples , so the controller observes the actual current state exactly.
A sensor bias is a systematic offset between the measured output and the physical plant output, modeled here as with constant . Unlike zero-mean measurement noise, a sensor bias persists when repeated readouts are averaged. A sensor bias affects the physical meaning of a zero tracking error; for a temperature readout, independent thermometer calibration can detect it.
A control disturbance is an influence on the controlled plant that is not the chosen control input. In , a constant increases by per unit whenever .
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In control theory, a "plant" refers to the system or process that is being controlled or regulated. It can be any physical system, such as a mechanical device, electrical circuit, chemical process, or even a software system, which requires control systems to manage its behavior and performance. The characteristics of a plant can include: 1. **Inputs**: Variables that can be manipulated to influence the behavior of the system (e.g., forces, voltages, or flow rates).