Development of a Digital PID-like Adaptive Controller and its Application in HVAC systems

This paper presents the development of a digital Proportional
Integral Derivative (PID)-like adaptive controller and its
application on Heating, Ventilating and Air Conditioning (HVAC)
systems. The HVAC process model is often approximately
described as a first-order-plus-deadtime (FOPDT) model, with
process parameters which can vary with time due to changing
operating conditions, nonlinearities and other environmental
factors. By using the recursive least squares (RLS) algorithm, upto-date estimates of the process parameters can be adaptively
obtained while the system operates. A simple but effective design
method for an adaptive control strategy in such a situation is
described in this paper. The design method easily compensates a
time delay and is robust to non-minimum phase behaviours. Based
on the estimated model parameters, the overall control strategy is
then able to adaptively track the setpoint with a pre-specified
response without needing to be retuned or reconfigured later if the
operating conditions vary. As HVAC systems sometimes have a
zero, an implementation of the proposed control algorithm is
applied to minimum and non-minimum phase HVAC models, and
favourable results were obtained in comparison with another
adaptive control scheme found in literature. The digital PID-like
adaptive control algorithm was also applied to PT326 – Heat
Process Trainer, and a good control performance was obtained.