HVAC nonlinearity compensation using cascaded control architectures

Buildings consume a large percentage of energy used in the United States, with a significant portion expended on heating, ventilation, and air-conditioning systems. These systems regulate internal environments to provide consistent comfort for optimum productivity. There exists a large opportunity for reduction of energy use and costs associated with HVAC systems without sacrificing comfort. As most HVAC systems are interconnected and highly nonlinear, control of these systems becomes difficult. Traditional proportional-integral derivative (PID) control has documented issues with large sustained oscillations of the actuator known as hunting behavior. A significant body of work has already been generated to explore alternate control algorithms to reduce this problem. This paper uses four case studies to demonstrate the ability of simple cascaded control architectures to compensate for static and dynamic nonlinearities that make up the dominant nonlinear behavior of most HVAC systems. The cascaded loop is highly modular, as it does not require explicit models of system characteristics. The architecture is also easily implementable, as it uses standard PID control loops and often does not require additional sensors. Elimination of hunting behavior not only extends actuator lifespan, but also reduces labor costs associated with identification and retuning of control loops.