Tools are now available to identify the process dynamics and calculate tuning settings. The tools can indicate a relative speed (faster or slower) of the new tuning versus the old tuning. However, the new tuning settings depend upon the lambda factor or the desired speed chosen. Thus it is still up to the user or consultant to decide whether the loop should be faster or slower.
For me, the period and amplitude of the oscillations provide a clue. Oscillations with a period much less than natural period of the loop are effectively uncontrollable noise. Oscillations with a period in the neighborhood of the natural period of the loop will get amplified by control action. In either case, the loop needs to be slowed down and the source of the oscillations tracked down and reduced. The natural period for a single time constant plus dead time (first order plus dead time) approximation of a self-regulating process varies from about 2 to 4 times the dead time.
Limit cycles (constant amplitude oscillations) are generally indicative of valve problems. A slower tuning will make the oscillations slower. This may be good or bad. If the oscillations are upsetting other loops, you probably want to slow them down. If the oscillations are being attenuated out by a downstream volume, it might be better to make the oscillations faster to get more effective filtering action by the volume and reduce the dead time from the valve stick-slip and dead band by a higher controller gain.
If the oscillations are not limit cycles and are much slower than the loop, the source could be a slow oscillating disturbance upstream, in which case it is better to speed up the loop.
If the loop’s response is never really oscillatory (e.g. a predominant period 100 times larger than the natural period), then the loop should be speeded up for set point changes and those occasional upsets as long as big abrupt changes in the control valve don’t upset other loops. For reactors, columns, and large mixed volumes, big steps in the controller output disturb the operator more than the process.
A power spectrum analysis can show the frequencies (periods) with the greatest power.
So you can still see the forest and not just the trees while deep in the woods, there are a couple of concepts to remember. First, there is tradeoff between reducing fluctuations in the controlled variable (e.g. composition, level, temperature, and pressure) and increasing the fluctuations in the manipulated variable (e.g. flow) of a loop. A controller tuned for a faster response, transfers more variability from the controlled variable to the manipulated variable whose movement can upset other loops. Second, there a tradeoff between tuning speed (aggressiveness) and robustness (stability). A controller tuned for a smooth but faster response, will develop oscillations for a smaller increase in process dead time or process gain. Tuning is overly conservative because faster tuning presents a greater risk for oscillations in this loop and other loops. A loop that behaved badly is remembered more than a hundred loops that became more responsive from a change in tuning. A good loop performance monitoring and tuning tool is essential for evaluation and confidence.
If the amplitude of the oscillations and the standard deviation are small, who cares?