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Generalized predictive control parameter optimization for indirect air cooling system based on improved particle swarm optimization algorithm
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Zijian DONG1, Yang GAO1, Ning RAN2
Thermal Power Generation | 2026, 55(4) : 166 - 174
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Thermal Power Generation | 2026, 55(4): 166-174
• Power generation techonology forum •
Generalized predictive control parameter optimization for indirect air cooling system based on improved particle swarm optimization algorithm
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Zijian DONG1, Yang GAO1, Ning RAN2
Affiliations
  • 1.School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China
  • 2.College of Electronic Informational and Engineering, Hebei University, Baoding 071002, China
Published: 2026-04-25 doi: 10.19666/j.rlfd.202509026
Outline
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To address poor control performance of indirect air cooling systems under external disturbances, where conventional PID control fails to meet requirements of large time-delay, strong coupling, and nonlinear systems while generalized predictive control (GPC) offers superior performance but suffers from parameter tuning difficulties, an improved PSO-based GPC parameter tuning method is proposed. Transfer function and environmental wind speed disturbance models are established with a GPC controller using circulating water outlet temperature as the controlled variable. Targeting limitations of conventional PSO prone to local optima and low convergence accuracy, a DE-VPPSO hybrid algorithm combining differential evolution and velocity pausing mechanisms is designed, employing dual-population collaborative search to enhance search capability and convergence precision. The algorithm simultaneously optimizes four key GPC parameters: prediction horizon, control horizon, control weighting, and softening factor. Simulation results demonstrate that under step disturbances, wind speed disturbances, parameter mismatches, noise interference, and comprehensive operating conditions, the proposed method exhibits excellent control performance and robustness, effectively enhancing system performance.

indirect air cooling system  /  generalized predictive control  /  particle swarm optimization algorithm  /  controller parameter tuning
Zijian DONG, Yang GAO, Ning RAN. Generalized predictive control parameter optimization for indirect air cooling system based on improved particle swarm optimization algorithm[J]. Thermal Power Generation, 2026 , 55 (4) : 166 -174 . DOI: 10.19666/j.rlfd.202509026
Funding
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  • National Natural Science Foundation of China(62373132)
Appendix
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Year 2026 volume 55 Issue 4
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213
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Article Info
doi: 10.19666/j.rlfd.202509026
  • Receive Date：2025-09-25
  • Online Date：2026-08-14
  • Published：2026-04-25
Article Data
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History
  • Received：2025-09-25
  • Revised：2025-10-24
  • Accepted：2025-11-04
Funding
National Natural Science Foundation of China(62373132)
Affiliations
    1.School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China
    2.College of Electronic Informational and Engineering, Hebei University, Baoding 071002, China
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