Brett, There's a lot of stuff here but I realise that there are constraints on you developing this library that might be obviated by a pull request. You might want to have a look at the method of peak detection I have implemented here. I think it is a considerable improvement. There's also a bunch of new auto tune rules.

Summary of changes:

Changes to the peak convergence method:

peak times and values now recorded for both minima and maxima in array peakTime[] and longer array peaks[]
new method of assessing convergence for peaks based on amplitude over last 1.5 cycles rather than levels of recent maxima
new variable inputCount counts number of inputs in lastInputs[] so that peaks are not called before lastInputs[] has been filled

Finite state machine:

new private variable enum AutoTunerState state records current state of algorithm
Runtime() initiates autotuner immediately first time around instead of waiting until next sampleTime

Enumerated types:

tuning algorithms selected by enum Control type
enum AutoTuneState state used instead of flag variable running to indicate autotuner state
enum PeakType used to describe whether peaks are maxima or minima
enum Mode used to describe whether under Automatic or Manual control
enum Direction used to describe sign of gain

Changes to private methods and variables:

minimum value of nLookBack set to 20 in method SetLookbackSec()
int variables nLookBack, peakCount changed to byte
got rid of private variable justevaled whose value was never checked
private variables justchanged, isMin, isMax, absMax, absMin made local to Runtime() *private method FinishUp() inlined so that phaseLag and inducedAmplitude can be local to Runtime()

New tuning rules:

new tuning rules selectable by setting enum Control type
new private variables Kp, Ti, Td for calculation of gain parameters
private variables Ku, Kp made local to FinishUp();
induced amplitude calculated as average over previous 1.5 cycles instead of difference between most extreme values ever observed

New variables and methods used by the AMIGOF_PI algorithm:

private variable K_process estimates the process gain from the steady state response to a step up in output
private variable originalNoiseBand saves value of noiseBand, which is tuned by the AMIGOF_PI algorithm
private method CheckStable() checks whether the values in lastInputs[] have converged to values within noiseBand of each other

New simulations:

lag-dominated and delay-dominated processes. Ziegler-Nichols PI works surprisingly well, but some of the more conservative methods I have implemented are worth a look.

Dithering:

implemented as a compile option. I haven't found this very useful.

br3ttb / Arduino-PID-AutoTune-Library

Peak detection overhaul, new tuning rules, etc. #10

Summary of changes: