Online strategies for adaptive tuning of PI controllers in HVAC systems

To improve the setpoint tracking and disturbance attenuation properties of the Discharge Air Temperature (DAT) control loop in HVAC systems, online adaptive PI tuning strategies are developed. The feasibility of adaptive control strategies for DAT systems is first studied by formulating and solving three adaptive control problems. These are: a model following adaptive (MFA) control problem, a control-model based adaptive (CMBA) control problem and an H P adaptive PI (HIAPI) control problem. The DAT system is modelled as a first-order-plus-dead-time (FOPDT) model. Both MFA and HIAPI controls are model-based techniques whereas CMBA is a model-less control strategy. Motivated by computer simulation results, two control strategies namely: CMBA and HIAPI are chosen as ideal candidates for implementation in a HVAC test facility. Both CMBA and HIAPI control algorithms are written in Powers Processor Control Language for online implementation. Several experimental tests are conducted under variable setpoints, variable disturbances, and multiple loop interactions. Experimental results show that CMBA control tuning method is simple to implement (does not require system identification) and robust to changes in setpoints and operating conditions. It is found to give stable and smooth response. The HIAPI tuning strategy requires system identification; as such it is sensitive to changes in operating conditions. Results show that HIAPI tuning control also gives good output responses under a wide range of operating condition