Which type of process control can be used if accuracy is not critical?

Which type of process control can be used if accuracy is not critical?

• A. feedback control
• B. floating proportional control
• C. feed forward control
• D. proportional control

Answer: (C)

Feedforward control anticipates disturbances and adjusts the input before the process output is affected. It uses a model of the process and measurements of known disturbances to pre‑emptively correct the manipulated variable, so you don’t have to rely on the output error to drive the correction. When accuracy isn’t critical, this quick, preemptive action can keep the system near the desired condition without demanding precise measurement of the process variable or a tight, error-correcting loop. The trade-off is that feedforward only corrects for disturbances you can measure or predict; if disturbances are unknown or the model is off, some error can still appear, which is why it’s common to pair feedforward with feedback for robust performance. In contrast, purely feedback methods depend on the difference between setpoint and actual output to drive corrections, which improves accuracy but may respond more slowly or require tighter control of the measured variable.

Feedforward control anticipates disturbances and adjusts the input before the process output is affected. It uses a model of the process and measurements of known disturbances to pre‑emptively correct the manipulated variable, so you don’t have to rely on the output error to drive the correction. When accuracy isn’t critical, this quick, preemptive action can keep the system near the desired condition without demanding precise measurement of the process variable or a tight, error-correcting loop. The trade-off is that feedforward only corrects for disturbances you can measure or predict; if disturbances are unknown or the model is off, some error can still appear, which is why it’s common to pair feedforward with feedback for robust performance. In contrast, purely feedback methods depend on the difference between setpoint and actual output to drive corrections, which improves accuracy but may respond more slowly or require tighter control of the measured variable.