Many industrial facilities utilize pressure control gradients to prevent migration of hazardous species from containment areas to occupied zones, often using Proportional-Integral-Derivative (PID) control systems. When operators rebalance the facility, variation from the desired gradients can occur and the operating conditions can change enough that the PID parameters are no longer adequate to maintain a stable system. As a major goal of the Heating, Ventilation, and Air Conditioning (HVAC) control system is to optimize the pressure gradients and associated flows for the facility, a Linear Quadratic Tracker (LQT) method provides a time-based approach to guiding facility interactions. However, LQT methods are susceptible to modeling and measurement errors, and therefore the additional use of soft computing methods is proposed for implementation to account for errors and nonlinearities. The resulting hybrid controller design provides a framework for supervisory control of an HVAC system, and shows that significant improvements can be achieved when the overall plant dynamics of the ventilation system are considered in the control system design.