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Comparative analysis of versatile temperature-controlled systems using fuzzy logic controllers

Ivan I. Gorial

Ivan I. Gorial

Control and Systems Engineering Department, University of TechnologyBaghdad, Iraq
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Gorial, Ivan I.
  
17. Okt. 2024
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Artikel-Kategorie: Research article
Online veröffentlicht: 17. Okt. 2024
Eingereicht: 26. Juli 2024
DOI: https://doi.org/10.2478/ijssis-2024-0033
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© 2024 Ivan I. Gorial, published by Sciendo
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Figure 1:

Block representation of a knowledge-base and inference engine.
Block representation of a knowledge-base and inference engine.

Figure 2:

FLC for a temperature-controlled fan system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC for a temperature-controlled fan system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 3:

FLC-based temperature control for a fan system structure: inputs and output regulation. FL, fuzzy logic.
FLC-based temperature control for a fan system structure: inputs and output regulation. FL, fuzzy logic.

Figure 4:

FIS for temperature-controlled fan: membership functions and rule base.
FIS for temperature-controlled fan: membership functions and rule base.

Figure 5:

FLC for a temperature-controlled heater system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC for a temperature-controlled heater system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 6:

FLC-based temperature control for a heater system structure: inputs and output regulation. FL, fuzzy logic.
FLC-based temperature control for a heater system structure: inputs and output regulation. FL, fuzzy logic.

Figure 7:

FIS for temperature-controlled heater: membership functions and rule base.
FIS for temperature-controlled heater: membership functions and rule base.

Figure 8:

FLC for a cool-controlled fan system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC for a cool-controlled fan system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 9:

FLC-based cool control for a fan system structure: inputs and output regulation. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC-based cool control for a fan system structure: inputs and output regulation. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 10:

FIS for cool-controlled fan: membership functions and rule base.
FIS for cool-controlled fan: membership functions and rule base.

Figure 11:

FLC for a cool-controlled heater system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC for a cool-controlled heater system: input and output membership functions. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 12:

FLC-based cool control for a heater system structure: inputs and output regulation. FL, fuzzy logic; FLC, fuzzy logic controller.
FLC-based cool control for a heater system structure: inputs and output regulation. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 13:

FIS for cool-controlled heater: membership functions and rule base.
FIS for cool-controlled heater: membership functions and rule base.

Figure 14:

3D FLC control surface plots for fan speed and heater power adjustments. FL, fuzzy logic; FLC, fuzzy logic controller.
3D FLC control surface plots for fan speed and heater power adjustments. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 15:

Temperature-controlled fan system using FLC. FL, fuzzy logic; FLC, fuzzy logic controller.
Temperature-controlled fan system using FLC. FL, fuzzy logic; FLC, fuzzy logic controller.

Figure 16:

Temperature control performance and heater power output over time.
Temperature control performance and heater power output over time.

Figure 17:

Cooling system performance: controlled temperature and fan speed over time.
Cooling system performance: controlled temperature and fan speed over time.

Figure 18:

Heating system performance: controlled temperature and heater power over time.
Heating system performance: controlled temperature and heater power over time.

Figure 19:

Comparison of temperature-controlled and cool-controlled systems using FLCs. FLCs, fuzzy logic controllers.
Comparison of temperature-controlled and cool-controlled systems using FLCs. FLCs, fuzzy logic controllers.

Performance analysis of temperature and cool-controlled systems

System type Initial temperature (°C) Desired temperature (°C) Final temperature (°C) Final fan speed/heater power (%) Mean temperature error (°C) Max temperature error (°C) Comments
Temperature-controlled fan system 30 25 Slightly above 25 Dynamically adjusted −0.0319 - Maintains target temperature with minimal overshoot. Effective for precise cooling, slightly need for error correction
Temperature-controlled heater system Varies around 20 22 20.842 7.2501 1.4696 1.9873 Maintains temperature close to desired with minor deviations. Suitable for stable heating and requires minor fine-tuning
Cool-controlled fan system Varies around 25 Cooler than ambient Maintains cooler env. 30 - - Efficiently maintains cooler environment than ambient. Ideal for cooling applications with consistent control
Cool-controlled heater system Not specified Prevents exceeding threshold Maintains set temp. 60 - - Effectively prevents overheating by adjusting heater power. Suitable for strict temperature control and could improve energy efficiency

Comprehensive comparison of our study with selected references [21], [22] and [28]

Aspect Our study Ahmad et al. [22] Nyiekaa et al. [21] Schuster et al. [28]
Objective Evaluate FLC-based temperature and cooling systems for stable conditions and energy efficiency Address thermal comfort, heat wave resilience, and indoor air quality in warm climates Design and construct a temperature control system to maintain a desired temperature in enclosed area Explore cool-controlled heating systems for improved thermal comfort and energy efficiency in building automation
Methodology Utilize FIS to dynamically adjust fan speed and heater power based on input variables, such as temperature error and rate of temperature change Investigate the integration of advanced control algorithms and natural ventilation strategies Use a temperature controller system designed to maintain a desired temperature automatically Integrate cool-controlled heating systems with building automation to optimize energy use
Control objective Maintain stable conditions in residential, industrial, and electronic cooling applications Enhance thermal comfort and indoor air quality in warm climates Maintain a specific temperature within an enclosed area Maintain thermal comfort and enhance energy efficiency in heating systems
Results Achieved a mean temperature error of −0.0319°C for fan system and 1.4696°C for heater system; effective temperature control and energy efficiency Potential of advanced fan systems to improve thermal comfort and indoor air quality Successfully maintained a specified temperature within enclosed area Potential for improved energy efficiency and user satisfaction through building automation
System applications Residential, industrial, and electronic cooling Warm climates and natural ventilation systems Enclosed areas requiring stable temperature control Building automation and heating systems
System focus Both heating and cooling applications, preventing overheating and maintaining desired conditions Primarily cooling applications to enhance thermal comfort and air quality Heating applications to maintain stable temperature Heating applications for thermal comfort and energy efficiency
Energy efficiency Substantial energy savings compared to traditional methods Enhanced through advanced ventilation strategies Energy-efficient temperature maintenance Improved through integration with building automation

Comprehensive comparison of temperature-controlled and cool-controlled systems using FLC

Aspect Temperature-controlled fan system Temperature-controlled heater system Cool-controlled fan system Cool-controlled heater system
Performance Maintains target temperature with minimal overshoot Maintains temperature close to desired with minor deviations Efficiently maintains a cooler environment than ambient Prevents overheating effectively by adjusting heater power
Effectiveness Effective for precise cooling Suitable for stable heating in varied conditions Ideal for cooling applications with consistent airflow Useful for environments requiring strict temperature control
Improvement needed Slight need for error correction Lower mean error and minor temperature fine-tuning needed Fan speed optimization may improve energy efficiency Better heater power management for energy efficiency
Initial temperature (°C) 30 Varies around 20 Varies around 25 Not specified (example uses 20)
Desired temperature (°C) 25 22 Cooler than ambient (e.g., maintaining 25) Prevent temperature from exceeding a threshold
Final temperature (°C) Slightly above 25 20.842 Not specified; focused on maintaining a cooler environment Managed to stay around set temperature with control actions
Final fan speed/heater power (%) Fan speed dynamically adjusted 7.2501 Fan speed: 30 Heater power: 60
Mean temperature error (°C) −0.0319 1.4696 - -
Max temperature error (°C) - 1.9873 - -
Comments on results Maintains target temperature with minimal overshoot. Effective for precise cooling and slightly needed for error correction Maintains temperature close to desired with minor deviations. Suitable for stable heating and requires minor fine-tuning Efficiently maintains a cooler environment than ambient. Ideal for cooling applications with consistent control Effectively prevents overheating by adjusting heater power. Suitable for strict temperature control and could improve energy efficiency
Control objective Reduce and maintain temperature at a lower set point Increase and maintain temperature at a higher set point Reduce temperature below ambient, maintaining cooler conditions Prevent temperature from rising above a certain point
Control strategy Adjust fan speed based on the error and the rate of change Adjust heater power based on the error and the rate of change Adjust fan speed dynamically to reduce temperature fluctuations Adjust heater power dynamically to prevent the temperature increase
Ambient temperature Not directly controlled Simulated fluctuation: 20 + 2 × sin (time) Simulated fluctuation: 25 + 10 × sin (time/10) Simulated varying conditions: e.g., 20 + 10 × sin (time)
System complexity Moderate, requiring dynamic fan speed adjustment Moderate, requiring dynamic heater power adjustment Moderate, adjusting fan speed to manage temperature variations Moderate, adjusting heater power to manage temperature increases
Energy efficiency Moderate efficiency, depends on fan speed adjustments Moderate efficiency, adjusting heater power to manage temperature Moderate efficiency, dynamic fan speed adjustment to manage cooling Moderate efficiency, managing heater power to prevent overheating
Key output variables Fan speed Heater power Fan speed Heater power
Response characteristics Increases airflow to cool environment Increases heat to warm environment Increases airflow to reduce temperature effectively Modulates heating to prevent excessive temperature
Typical applications HVAC systems, data centers Residential heating, industrial processes Cooling systems for electronics, data centers Heating systems in environments, requiring strict temperature control
System focus Cooling by regulating fan speed Heating by modulating heater power Cooling by increasing fan speed to manage temperature fluctuations Cooling by preventing overheating through heater power modulation
Primary function Cools the environment by regulating airflow Heats the environment by adjusting heat output Prevents overheating by regulating heat output Cools the environment by increasing airflow
Key input variables Temperature, fan speed, and sometimes humidity Temperature and rate of temperature change Temperature and rate of temperature increase Temperature, fan speed, and sometimes humidity
Output variables Fan speed adjustments Heater power adjustments Heater power adjustments Fan speed adjustments
Environmental suitability Best for warm climates, needing cooling Best for cold climates, needing heating Suitable for hot environments, needing to avoid overheating Suitable for environments, needing consistent cooling
Control complexity Requires managing airflow and sometimes humidity Focused on direct heat output control Balances heating and cooling mechanisms to prevent overheating Focuses on managing airflow and sometimes additional cooling
Temperature regulation Maintains or reduces temperature effectively Increases and maintains temperature Maintains a maximum temperature to prevent overheating Reduces temperature by maximizing airflow
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