Demonstration of a hybrid Intelligent control strategy for critical building HVAC systems

C. Rieger, D. S. Naidu

Research output: Contribution to journalArticlepeer-review

2 Scopus citations


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. Within these facilities, PID control is often inadequate to maintain desired performance due to changing operating conditions, a common issue in process applications [1]. As the goal of the heating, ventilation and air-conditioning (HVAC) control system is to optimize the pressure gradients and associated flows for the plant, linear quadratic tracking (LQT) provides a time-based approach to guiding plant interactions. However, LQT methods are susceptible to modelling and measurement errors, and therefore a hybrid design using the integration of soft control methods with hard control methods is developed and demonstrated to account for these errors and non-linearities.

Original languageEnglish (US)
Pages (from-to)110-119
Number of pages10
JournalControl and Intelligent Systems
Issue number2
StatePublished - Jun 3 2010


  • Fuzzy logic (FL)
  • HVAC
  • Linear quadratic tracking (LQT)
  • Neural network (NN)
  • Optimal tracking


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