Blockchain and Hybrid PSO Integration With Fuzzy PID Control to Optimize the Energy Usage for Lighting Control System
PID control, which stands for Proportional-Integral-Derivative control, is a widely used control technique in various fields, including lighting control systems, manufacturing industry, appliance power management, solar water heating systems and smart thermostats. The lighting control systems involv...
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| Published in | IEEE transactions on consumer electronics Vol. 70; no. 4; pp. 6965 - 6974 |
|---|---|
| Main Authors | , |
| Format | Journal Article |
| Language | English |
| Published |
New York
IEEE
01.11.2024
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0098-3063 1558-4127 |
| DOI | 10.1109/TCE.2024.3436686 |
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| Abstract | PID control, which stands for Proportional-Integral-Derivative control, is a widely used control technique in various fields, including lighting control systems, manufacturing industry, appliance power management, solar water heating systems and smart thermostats. The lighting control systems involve the use of minimal energy for controlling the lighting system inside the residential and industry premises for consumers to minimize the redundant consumption of energy during daylight hours or in unoccupied areas/rooms. The machine intelligence based algorithms and Fuzzy based PID control based algorithms play integral role in guaranteeing the accuracy and stability of the lighting control system. In lighting control system, the PID control algorithm is employed to regulate the lighting system in multiple aspects such as desired angle, temperature, outdoor light impact and intensity. This study focuses on saving the consumption of energy and enhancing the accuracy of PID control in lighting control system for consumers through the combination of Particle Swarm Optimization (PSO) and Blockchain technology. By optimizing the lighting control system with the aid of the hybrid PSO (IHPSO), the intelligent PID control algorithm shows improvements in controlling the lighting system in an automated manner. The system has been compared with the exiting methods for proving its performance over the existing techniques. Performance test experiments demonstrate that the IHPSO fuzzy PID control algorithm exhibits a smaller error speed compared to traditional methods. The effectiveness of the algorithm is evaluated using 100 units of samples, resulting in a higher accuracy rate ranging from 87% to 99%, with an average accuracy rate of 94% across the 100 residential units. The improved PSO algorithm is further assessed by repeatedly testing the same samples, showing significant superiority over other algorithms with a Mean Relative Error (MRE) of 2.357%, Mean Square Error (MSE) of 1.372%, and accuracy of 94%. These findings reveal that the proposed IHPSO fuzzy PID control mechanism is achieving high accuracy in saving the consumption of energy in lighting control system for consumers of electricity. |
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| AbstractList | PID control, which stands for Proportional-Integral-Derivative control, is a widely used control technique in various fields, including lighting control systems, manufacturing industry, appliance power management, solar water heating systems and smart thermostats. The lighting control systems involve the use of minimal energy for controlling the lighting system inside the residential and industry premises for consumers to minimize the redundant consumption of energy during daylight hours or in unoccupied areas/rooms. The machine intelligence based algorithms and Fuzzy based PID control based algorithms play integral role in guaranteeing the accuracy and stability of the lighting control system. In lighting control system, the PID control algorithm is employed to regulate the lighting system in multiple aspects such as desired angle, temperature, outdoor light impact and intensity. This study focuses on saving the consumption of energy and enhancing the accuracy of PID control in lighting control system for consumers through the combination of Particle Swarm Optimization (PSO) and Blockchain technology. By optimizing the lighting control system with the aid of the hybrid PSO (IHPSO), the intelligent PID control algorithm shows improvements in controlling the lighting system in an automated manner. The system has been compared with the exiting methods for proving its performance over the existing techniques. Performance test experiments demonstrate that the IHPSO fuzzy PID control algorithm exhibits a smaller error speed compared to traditional methods. The effectiveness of the algorithm is evaluated using 100 units of samples, resulting in a higher accuracy rate ranging from 87% to 99%, with an average accuracy rate of 94% across the 100 residential units. The improved PSO algorithm is further assessed by repeatedly testing the same samples, showing significant superiority over other algorithms with a Mean Relative Error (MRE) of 2.357%, Mean Square Error (MSE) of 1.372%, and accuracy of 94%. These findings reveal that the proposed IHPSO fuzzy PID control mechanism is achieving high accuracy in saving the consumption of energy in lighting control system for consumers of electricity. |
| Author | Zeng, Jianmei Cheng, Wei |
| Author_xml | – sequence: 1 givenname: Wei orcidid: 0009-0003-4288-2400 surname: Cheng fullname: Cheng, Wei email: chengwei0303201@163.com organization: College of Artificial Intelligence, Chongqing Business Vocational College, Chongqing, China – sequence: 2 givenname: Jianmei surname: Zeng fullname: Zeng, Jianmei email: lizibutian@126.com organization: College of Artificial Intelligence, Chongqing Business Vocational College, Chongqing, China |
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| SubjectTerms | Accuracy Algorithms Blockchain consumer electronics Consumers Control algorithms Control stability Control systems Control theory Energy consumption Fuzzy control Fuzzy PID Fuzzy systems Heating systems hybrid PSO Lighting Lighting control lighting control system Lighting systems Luminous intensity machine intelligence Motors Particle swarm optimization PD control Performance evaluation Performance tests PI control Power management Proportional integral derivative Residential energy Solar heating Swarm intelligence Water heaters Water heating |
| Title | Blockchain and Hybrid PSO Integration With Fuzzy PID Control to Optimize the Energy Usage for Lighting Control System |
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