Editing Proportional–integral–derivative controller (section)

===Overview of tuning methods===
There are several methods for tuning a PID loop. The most effective methods generally involve developing some form of process model and then choosing P, I, and D based on the dynamic model parameters. Manual tuning methods can be relatively time-consuming, particularly for systems with long loop times.

The choice of method depends largely on whether the loop can be taken offline for tuning, and on the response time of the system. If the system can be taken offline, the best tuning method often involves subjecting the system to a step change in input, measuring the output as a function of time, and using this response to determine the control parameters.{{Citation needed|date=May 2013}}

{| class="wikitable"
|+ Choosing a tuning method
! Method
! Advantages
! Disadvantages
|-
! [[#Manual tuning|Manual tuning]]
| No mathematics required; online.
| This is an iterative, experience-based, trial-and-error procedure that can be relatively time consuming. Operators may find "bad" parameters without proper training.<ref name ="simc">{{cite web |last=Skogestad|first=Sigurd  |date=2003 |title=Simple analytic rules for model reduction and PID controller tuning |url=https://folk.ntnu.no/skoge/publications/2003/tuningPID/finalpaper.pdf/C18/E6-43-03-03.pdf}}</ref>
|-
! [[#Ziegler–Nichols method|Ziegler–Nichols]]
| Online tuning, with no tuning parameter therefore easy to deploy.
| Process upsets may occur in the tuning, can yield very aggressive parameters. Does not work well with time-delay processes. {{Citation needed|date=May 2013}}
|-
! Tyreus Luyben
| Online tuning, an extension of the Ziegler–Nichols method, that is generally less aggressive.
| Process upsets may occur in the tuning; operator needs to select a parameter for the method which requires insight.
|-
! [[#Tuning software|Software tools]]
| Consistent tuning; online or offline – can employ computer-automated control system design (''[[CAutoD]]'') techniques; may include valve and sensor analysis; allows simulation before downloading; can support non-steady-state (NSS) tuning.
| "Black box tuning" that requires specification of an objective describing the optimal behaviour.
|-
! [[#Cohen–Coon parameters|Cohen–Coon]]
| Good process models{{Citation needed|date=May 2013}}.
| Offline; only good for first-order processes.{{Citation needed|date=May 2013}}
|-
![[#Relay (Åström–Hägglund) method|Åström-Hägglund]]
| Unlike the Ziegler–Nichols method this will not introduce a risk of loop instability. Little prior process knowledge required.<ref name="warwick.ac.uk">{{cite web | url=https://warwick.ac.uk/fac/cross_fac/iatl/reinvention/archive/volume5issue2/hornsey/ | title=A Review of Relay Auto-tuning Methods for the Tuning of PID-type Controllers }}</ref>
| May give excessive derivative action and sluggish response. Later extensions resolve these issues, but require a more complex tuning procedure.<ref name="warwick.ac.uk"/>
|-
! Simple control rule (SIMC)
| Analytically derived, works on time delayed processes, has an additional tuning parameter that allows additional flexibility. Tuning can be performed with step-response model.<ref name="simc" />
| Offline method; cannot be applied to oscillatory processes. Operator must choose the additional tuning parameter.<ref name="simc" />
|}