In the case of nonlinear systems, optimal parameters might change, depending on what “state” the system is in. The most common reason people experience performance issues with PID control is the fact that incorrect gain parameters are chosen for P, I and D. One way that engineers have made use of PID in nonlinear systems is through the technique of gain scheduling.

There are, however, certain techniques to apply the same PID algorithm to systems that don’t necessarily meet these criteria. Should the heater be turned on all the way or only part of the way? The basic PID controller compares a single input to a setpoint value and calculates a single output value to control the system, and the algorithm assumes that the response will be linear and not change over time. The challenge then comes from figuring out how much to adjust control outputs to achieve the best response. Controlling temperature, for example, can be done by measuring the current temperature, comparing it to the desired temperature value, and then using a heater or fan to move the temperature closer to the desired setpoint. Modern computer-based control systems utilize feedback by taking a sensor measurement, comparing it to some desired setpoint and then adjusting a control output based on this difference.

Originally these systems utilized mechanical means, for example a float valve, to control temperatures, speeds and fluid levels. Feedback control has been used since antiquity in the control of mechanical systems.

Pid controller for labview