The main steam temperature system of power plant has the characteristics of large inertia and large time delay. The classical cascade PID control is difficult to implement the precise control of the main steam temperature system. In this paper, the fusion algorithm of particle swarm optimization and cuckoo is used to optimize the controller parameters of the main steam temperature control system. By selecting the appropriate objective function, the main steam temperature control system of a 600 MW once-through boiler is optimized. Compared with the control results of PSO algorithm and practical tuning method, PSO-cuckoo fusion algorithm has better global optimization characteristics, better dynamic performance and anti-interference ability.
WANG Jin
,
CAI Tiaoyang
,
REN Meng
,
LYV Qing
. Parameter optimization of main steam temperature system controller based on PSO cuckoo fusion algorithm[J]. Journal of Hebei University(Natural Science Edition), 2021
, 41(2)
: 218
-224
.
DOI: 10.3969/j.issn.1000-1565.2021.02.016
[1] 韩璞,刘淼,王东风,等.过热汽温系统无记忆状态反馈H_∞鲁棒预测控制[J].动力工程学报,2018,38(1):36-42.DOI:10. 3969/j.issn.1674-7607.2018.01.007.
[2] 牛海明,于佼,丁常富,等. 基于多目标粒子群算法的过热汽温自抗扰控制 [J]. 中国电力,2020,53(3):126-132. DOI:10.11930/j.issn.1004-9649.201908096.
[3] 刘帅,刘长良.基于帝国竞争算法的主汽温控制系统参数优化研究[J].系统仿真学报,2017,29(2): 368-373. DOI:10.16182/j.issn1004731x.joss.201702018.
[4] TSENG C S, CHEN B S, UANG H J. Fuzzy tracking control design for nonlinear dynamic systems via T-S fuzzy model[J]. IEEE Trans Fuzzy Syst, 2001, 9(3): 381-392. DOI:10.1109/91.928735.
[5] 周宏宇,王小刚.基于改进粒子群算法的飞行器协同轨迹规划[J].自动化学报,2020,46(1):1-7. DOI:10.16383/j.aas.c190865.
[6] 许胜才,蔡军,程昀,等.基于拓扑结构与粒子变异改进的粒子群优化算法[J].控制与决策,2019,34(2): 419-428. DOI:10.13195/j.kzyjc.2017.1063.
[7] 高哲,廖晓钟.基于平均速度的混合自适应粒子群算法[J].控制与决策,2012,27(1): 152-155. DOI:10.13195/j.cd.2012.01.155.gaozh.029.
[8] 司文静,封喜波,耿立艳,等.基于ADPSO算法优化LSSVM的高速公路交通量预测方法[J].河北大学学报(自然科学版),2017, 37(3): 302-308. DOI:10.3969/j.issn.1000-1565.2017.03.013.
[9] ZAW M M, MON E E. Web document clustering by using PSO-based cuckoo search clustering algorithm[M] //Yang x s.Studies in Computational Intelligence. Cham: Springer International Publishing, 2014: 263-281. DOI:10.1007/978-3-319-13826-8_14.
[10] WANG F, LUO L G, HE X S, et al. Hybrid optimization algorithm of PSO and Cuckoo Search[Z]. 2011 2nd International Conference on Artificial Intelligence, Management Science and Electronic Commerce(AIMSEC), DengFeng, China, 2011: 1172-1175. DOI:10.1109/AIMSEC.2011.6010750.
[11] KARTHIKEYAN M, VENKATALAKSHMI K. Energy conscious clustering of wireless sensor network using PSO incorporated cuckoo search[Z]. 2012 Third International Conference on Computing, Communication and Networking Technologies(ICCCNT12), Coimbatore, India, 2012: 1-7. DOI:10.1109/ICCCNT.2012.6395963.
[12] YANG X S, DEB S. Cuckoo search via lévy flights[Z]. 2009 World Congress on Nature & Biologically Inspired Computing(NaBIC), Coimbatore, India, 2009: 210-214. DOI:10.1109/NABIC.2009.5393690.
[13] YANG X S. Nature-inspired metaheuristic algorithms[M]. znd. Uk:Luniver Press,2010:11-16.
[14] 范永胜,徐治皋,陈来九.基于动态特性机理分析的锅炉过热汽温自适应模糊控制系统研究[J].中国电机工程学报,1997,17(1): 23-28. DOI:10.13334/j.0258-8013.pcsee.1997.01.006. (