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.