自动化学报2018，Vol.44Issue(2)：299-310,12.DOI:10.16383/j.aas.2018.c160623
虚拟未建模动态补偿驱动的双率自适应控制
Dual-rate Adaptive Control Driven by Virtual Unmodeled Dynamics Compensation in Industrial Heat Exchange Process
摘要
Abstract
Industrial heat exchanging process is a complex industrial process,in which of heat exchange between steam and circulating water aims to ensure water temperature within the target range formatted by users.As a result of steam pressure fluctuation,returned water flow-rate fluctuation and fouling in heat exchanger,the parameters of a plant model may vary frequently,which is why the integral action loses its effectiveness.When the above disturbances occur violently and frequently,the integral action of cascade control would fail.This would cause fluctuations on the steam flow-rate and the supplied water temperature,or even lead to serve system resonance.To solve the above problems,in this paper,considering the heat exchange process runs near its operating point,low-order linear models and virtual unmodeled dynamics are used to express plant model.By combining the dual-rate control technique and adaptive signal method,an adaptive dual-rate controller is proposed,whose inner loop feedback variable is the steam flow and whose outer loop feedback variable is the supply water temperature.The stability of the control system ia analyzed theoretically.A semi-physical simulation experiment using the mechanism model as the virtual plant.The result shows that the control method proposed in this paper has adaptive capacity without any identification,and that the supply water temperature can also be controlled within the target range of process requirements.关键词
虚拟未建模动态补偿/工业换热过程/区间控制/PI控制Key words
Virtual unmodeled dynamics compensation/industrial heat exchange/interval control/PI control引用本文复制引用
杨天皓,李健,贾瑶,刘腾飞,柴天佑..虚拟未建模动态补偿驱动的双率自适应控制[J].自动化学报,2018,44(2):299-310,12.基金项目
国家高技术研究发展计划(863计划)(2015AA043802),国家自然科学基金(61603393),中国博士后科学基金(2015M581355)资助 Supported by National High Technology Research and Development Program of China (863 Program) (2015AA043802),National Natural Science Foundation of China (61603393),and China Postdoctoral Science Foundation (2015M581355) （863计划）
