Application of Fuzzy PID Control Algorithm in Optimal Control of Central Air-Conditioning Chilled Water System
With the continuous increase in energy consumption, how to improve the energy efficiency of central air-conditioning systems and reduce energy consumption has become an important issue in the field of building environment control. In response to the problems of large parameter time-lag, long time required to reach steady state, difficulty in adapting parameters to a large range, low prediction precision of temperature difference control, and high energy consumption in traditional PID (proportional-integral-derivative)-controlled central air-conditioning chilled water systems, this article combines energy consumption requirements and adopts an optimized SSA (sparrow search algorithm)-fuzzy PID control algorithm to study the optimal control of systems. Firstly, based on the fuzzy PID control algorithm, dynamic exploration is carried out using a random search strategy during the search process. Then, the chaotic mapping is adopted to improve the diversity and coverage of the search, and Gaussian and Cauchy mutations are applied to improve the local search capability. Finally, the optimized SSA-fuzzy PID control algorithm is validated in a simulated environment and subjected to optimal control performance testing in practice. The experiment focuses on the systems in a workshop of an industrial enterprise, and the research is conducted through simulation and real cases. The results show that the steady-state error of the optimized SSA-fuzzy PID control algorithm is 1.2%, which is 1.3% lower than the PID control algorithm, and the energy consumption is only 8.5%. The experiment shows that the optimized SSA-fuzzy PID control algorithm significantly reduces the energy consumption of the systems control and improves precision, promoting the energy-saving use of the systems.
Authors
- Guangpeng Li (ORCID: https://orcid.org/0000-0001-8318-5853)
- Yingli Zhou
Institutions
- Shandong Institute of Commerce & Technology (CN)
Publication Details
- Published
- 2024-12-04
- DOI
- https://doi.org/10.1109/icmnwc63764.2024.10871973
- Primary Topic
- Advanced Algorithms and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00