Adaptive Tuning

A perfectly-tuned PID controller can degrade over time and perform poorly or become oscillatory. There are two main reasons for these changes:

  1. The controlled process is non-linear, and the process operation has entered a region with significantly different process parameters than those used during the tuning.
  2. The process operating conditions have changed since the auto-tuning was performed.

The use of a gain scheduler, which adjusts the PID controller gain as a function of the operating point, is often sufficient for solving the first problem. In more demanding applications, where not only process gain, but also lag and deadtime, depends on the operating point, the PID controller is auto-tuned in several ranges. Based on the point of operation at any given time, the associated process model is used to set the PID gain, reset, and rate. In between points where the process model was identified, the PID tuning is set based on weighted averages, taking into account the process model in adjacent ranges and the distance from the ranges boundaries

To achieve the desired performance in the second case, the tuning should be repeated periodically or upon changes in controller performance, reflected in increased control variability. If this procedure is triggered and controlled automatically, the operation is called adaptive tuning. Adaptive tuning can also be applied in the first case. As we discuss in Chapter 5 of Advanced Control Foundation – Tools, Techniques and Applications, adaptive tuners for PID controllers may be classified as illustrated below.

There has been significant effort over the years to implement adaptive tuning. My next few blog will cover the adaptive tuning technique utilized in the DeltaV control system. This adaptive control capability is based on a technique known as model switching and parameter interpolation.