Temperature controller optimization by computational intelligence
Апстракт
In this paper a temperature control system for an automated educational classroom is optimized with several advanced computationally intelligent methods. Controller development and optimization has been based on developed and extensively tested mathematical and simulation model of the observed object. For the observed object cascade P-PI temperature controller has been designed and conventionally tuned. To improve performance and energy efficiency of the system, several meta heuristic optimizations of the controller have been attempted, namely genetic algorithm optimization, simulated annealing optimization, particle swarm optimization and ant colony optimization. Efficiency of the best results obtained with proposed computationally intelligent optimization methods has been compared with conventional controller tuning. Results presented in this paper demonstrate that heuristic optimization of advanced temperature controller can provide improved energy efficiency along with other perfor...mance improvements and improvements regarding equipment wear. Not only that presented methodology provides for determination and tuning of the core controller, but it also allows that advanced control concepts such as anti-windup controller gain are optimized simultaneously, which is of significant importance since interrelation of all control system parameters has important influence on the stability and performance of the system as a whole. Based on the results obtained, general conclusions are presented indicating that meta heuristic computationally intelligent optimization of heating, ventilation, and air conditioning control systems is a feasible concept with strong potential in providing improved performance, comfort and energy efficiency.
Кључне речи:
thermal system / temperature control / controller optimization / computational intelligenceИзвор:
Thermal Science, 2016, 20, S1541-S1552Издавач:
- Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd
Финансирање / пројекти:
- Интелигентни системи управљања климатизације у циљу постизања енергетски ефикасних режима у сложеним условима експлоатације (RS-MESTD-Technological Development (TD or TR)-33047)
- Истраживање магнетнохидродинамичких струјања (MHD) у околини тела, процепима и каналима и примена у развоју MHD пумпи (RS-MESTD-Technological Development (TD or TR)-35016)
DOI: 10.2298/TSCI16S5541C
ISSN: 0354-9836
WoS: 000389964200031
Scopus: 2-s2.0-85012040928
Колекције
Институција/група
Mašinski fakultetTY - JOUR AU - Ćojbašić, Žarko AU - Ristanović, Milan AU - Marković, Nemanja R. AU - Tesanović, Stefan Z. PY - 2016 UR - https://machinery.mas.bg.ac.rs/handle/123456789/2431 AB - In this paper a temperature control system for an automated educational classroom is optimized with several advanced computationally intelligent methods. Controller development and optimization has been based on developed and extensively tested mathematical and simulation model of the observed object. For the observed object cascade P-PI temperature controller has been designed and conventionally tuned. To improve performance and energy efficiency of the system, several meta heuristic optimizations of the controller have been attempted, namely genetic algorithm optimization, simulated annealing optimization, particle swarm optimization and ant colony optimization. Efficiency of the best results obtained with proposed computationally intelligent optimization methods has been compared with conventional controller tuning. Results presented in this paper demonstrate that heuristic optimization of advanced temperature controller can provide improved energy efficiency along with other performance improvements and improvements regarding equipment wear. Not only that presented methodology provides for determination and tuning of the core controller, but it also allows that advanced control concepts such as anti-windup controller gain are optimized simultaneously, which is of significant importance since interrelation of all control system parameters has important influence on the stability and performance of the system as a whole. Based on the results obtained, general conclusions are presented indicating that meta heuristic computationally intelligent optimization of heating, ventilation, and air conditioning control systems is a feasible concept with strong potential in providing improved performance, comfort and energy efficiency. PB - Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd T2 - Thermal Science T1 - Temperature controller optimization by computational intelligence EP - S1552 SP - S1541 VL - 20 DO - 10.2298/TSCI16S5541C ER -
@article{ author = "Ćojbašić, Žarko and Ristanović, Milan and Marković, Nemanja R. and Tesanović, Stefan Z.", year = "2016", abstract = "In this paper a temperature control system for an automated educational classroom is optimized with several advanced computationally intelligent methods. Controller development and optimization has been based on developed and extensively tested mathematical and simulation model of the observed object. For the observed object cascade P-PI temperature controller has been designed and conventionally tuned. To improve performance and energy efficiency of the system, several meta heuristic optimizations of the controller have been attempted, namely genetic algorithm optimization, simulated annealing optimization, particle swarm optimization and ant colony optimization. Efficiency of the best results obtained with proposed computationally intelligent optimization methods has been compared with conventional controller tuning. Results presented in this paper demonstrate that heuristic optimization of advanced temperature controller can provide improved energy efficiency along with other performance improvements and improvements regarding equipment wear. Not only that presented methodology provides for determination and tuning of the core controller, but it also allows that advanced control concepts such as anti-windup controller gain are optimized simultaneously, which is of significant importance since interrelation of all control system parameters has important influence on the stability and performance of the system as a whole. Based on the results obtained, general conclusions are presented indicating that meta heuristic computationally intelligent optimization of heating, ventilation, and air conditioning control systems is a feasible concept with strong potential in providing improved performance, comfort and energy efficiency.", publisher = "Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd", journal = "Thermal Science", title = "Temperature controller optimization by computational intelligence", pages = "S1552-S1541", volume = "20", doi = "10.2298/TSCI16S5541C" }
Ćojbašić, Ž., Ristanović, M., Marković, N. R.,& Tesanović, S. Z.. (2016). Temperature controller optimization by computational intelligence. in Thermal Science Univerzitet u Beogradu - Institut za nuklearne nauke Vinča, Beograd., 20, S1541-S1552. https://doi.org/10.2298/TSCI16S5541C
Ćojbašić Ž, Ristanović M, Marković NR, Tesanović SZ. Temperature controller optimization by computational intelligence. in Thermal Science. 2016;20:S1541-S1552. doi:10.2298/TSCI16S5541C .
Ćojbašić, Žarko, Ristanović, Milan, Marković, Nemanja R., Tesanović, Stefan Z., "Temperature controller optimization by computational intelligence" in Thermal Science, 20 (2016):S1541-S1552, https://doi.org/10.2298/TSCI16S5541C . .