Optimal Intelligent Control for HVAC Systems

  • Mohammad Hassan Khooban Department of Electrical and Robotic Engineering, Garmsar Branch, Islamic Azad University of IRAN
  • Mohammad Reza Soltanpour
  • Davood Nazari Maryam Abadi Department of Electrical and Robotic Engineering, Garmsar Branch, Islamic Azad University of IRAN
  • Zahra Esfahani


In this paper a novel Optimal Fuzzy Proportional-Integral-Derivative Controller (OFPIDC) is designed for controlling the air supply pressure of Heating, Ventilation and Air-Conditioning (HVAC) system. The parameters of input membership functions, output polynomial functions of first-order Sugeno, and PID controller coefficients are optimized simultaneously by random inertia weight Particle Swarm Optimization (RNW-PSO). Simulation results show the superiority of the proposed controller than similar non-optimal fuzzy controller

Author Biography

Mohammad Hassan Khooban, Department of Electrical and Robotic Engineering, Garmsar Branch, Islamic Azad University of IRAN
Department of Electrical and Robotic Engineering, Garmsar Branch, Islamic Azad University, Garmsar 91775-1111, Iran.


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How to Cite
KHOOBAN, Mohammad Hassan et al. Optimal Intelligent Control for HVAC Systems. Journal of Power Technologies, [S.l.], v. 92, n. 3, p. 192--200, oct. 2012. ISSN 2083-4195. Available at: <https://papers.itc.pw.edu.pl/index.php/JPT/article/view/327>. Date accessed: 28 june 2022.
Power Plant


HVAC Systems; Sugeno-Type Fuzzy Inference; Fuzzy Proportional-Integral-Derivative Controller (OFPIDC); Random inertia weight Particle Swarm Optimization (RNW-PSO)

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