Self-Tuning Control with Fuzzy Rule-Based Supervision for HVAC Applications

Ling, Keck Voon; Dexter, A.L.; Geng, G.; Haves, P.

doi:10.1016/s1474-6670(17)51320-8

Cited by 2 publications

(4 citation statements)

References 7 publications

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“…Fuzzy techniques have been used in BIEMS, giving significantly better outcomes than traditional control systems. Practical applications employing fuzzy and neural control in HVAC systems are also being used, with the overall aim of lowering energy consumption and costs [18][19][20][21][22].…”

Section: Fuzzy Logic Controllermentioning

confidence: 99%

Modeling, Analysis, and Design of a Fuzzy Logic Controller for an AHU in the S.J. Carew Building at Memorial University

2018

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Proper functioning of heating, ventilation, and air conditioning (HVAC) systems is important for efficient thermal management, as well as operational costs. Most of these systems use nonlinear time variances to handle disturbances, along with controllers that try to balance rise times and stability. The latest generation of fuzzy logic controllers (FLC) is algorithm-based and is used to control indoor temperatures, CO 2 concentrations in air handling units (AHUs), and fan speeds. These types of controllers work through the manipulation of dampers, fans, and valves to adjust flow rates of water and air. In this paper, modulating equal percentage globe valves, fans speed, and dampers position have been modeled according to exact flow rates of hot water and air into the building, and a new approach to adapting FLC through the modification of fuzzy rules surface is presented. The novel system is a redesign of an FLC using MATLAB/Simulink, with the results showing an enhancement in thermal comfort levels.

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Section: Fuzzy Logic Controllermentioning

confidence: 99%

Modeling, Analysis, and Design of a Fuzzy Logic Controller for an AHU in the S.J. Carew Building at Memorial University

2018

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“…The literature review in the areas of adaptive fuzzy logic and self tuning controller reveals adaptive techniques that have been applied to both HVAC unit control and system control along with the other industrial problems (Wallenberg 1991, Ling and Dexter, 1991, So et al, 1995. Results for an adaptive controller show stable behavior and better performance compared with conventional control algorithms.…”

Section: Discussionmentioning

confidence: 99%

“…Several studies (So et al 1995, Ling and Dexter, 1991, Wang and Jin, 2000 using adaptive control in the HVAC area have demonstrated that adaptive control leads to reduction in energy costs in comparison to conventional control strategies while still maintaining comfort conditions for building occupants.…”

Section: Discussionmentioning

confidence: 99%

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Development of an adaptive fuzzy logic controller for HVAC system

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Self-Tuning Control with Fuzzy Rule-Based Supervision for HVAC Applications

Cited by 2 publications

References 7 publications

Modeling, Analysis, and Design of a Fuzzy Logic Controller for an AHU in the S.J. Carew Building at Memorial University

Modeling, Analysis, and Design of a Fuzzy Logic Controller for an AHU in the S.J. Carew Building at Memorial University

Development of an adaptive fuzzy logic controller for HVAC system

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