Robust Model Predictive Control of VAV Air-Handling Units Concerning Uncertainties and Constraints

This paper presents a new strategy for robust temperature control of variable-air-volume (VAV) air-handling units (AHUs) that can deal with dynamic variations and the associated constraints in a straightforward manner. The dynamics of VAV AHUs is described by a first-order-plus-time-delay model, and the dynamic variations of the process gain, time constant, and time delay are described using uncertainty sets. These uncertainty sets are converted into an uncertainty polytope, and then an offline robust model predictive control (MPC) algorithm is employed for robust control design. The design procedure is illustrated step by step. An operating mode identification scheme is also developed based on the operating characteristics of VAV AHUs in order to reduce the size of uncertainty sets and, hence, to improve the control performance. Case studies are performed on a simulated VAV AHU. Results are presented to show that the proposed control strategy is able to enhance robustness without much user intervention, reduce the control activities, and satisfy constraints when implemented in the temperature control of VAV AHUs.