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

Gorial, Ivan I.

doi:10.2478/ijssis-2024-0033

Figures & Tables

Block representation of a knowledge-base and inference engine.

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

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

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

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

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

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

FLC for a cool-controlled fan system: input and output membership functions. 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.

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

FLC for a cool-controlled heater system: input and output membership functions. 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.

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

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

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

Temperature control performance and heater power output over time.

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

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

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

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

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Performance analysis of temperature and cool-controlled systems

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

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

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