摘要
对于难于建模的复杂系统,专家系统可以显著改善控制效果,但不同的系统需要的知识库各不相同,给专家系统的建立带来了困难。迭代学习控制可以不依赖系统的数学模型,利用以前控制周期的参数自动生成经验知识,建立专家系统;同时考虑被控系统中所具有的不确定性,因此提出具有柔性特点的迭代学习控制ILC控制器;运用柔性ILC建立的专家系统对空调进行控制,可以达到理想的控制效果。
Expert systems may improve the control effect of some complex systems without a mathematic model. However, to build the experience database of expert systems is difficult because the control knowledge is different from each other. Iterative learning control（ILC） can produce control experience from the historical data to build up the expert system. Considering some uncertain factors, a flexible measure is adopted in ILC. The expert system based on F-ILC achieves high control performance, which is proved by an application in air conditioning system.
出处
《合肥工业大学学报（自然科学版）》
CAS
CSCD
北大核心
2009年第11期1691-1695,共5页
Journal of Hefei University of Technology：Natural Science
基金
河北省科技研究与发展计划资助项目(06213547)
天津市应用基础研究计划资助项目(07JCYBJC05300)
关键词
迭代学习控制
柔性
专家系统
空调
iterative learning control
flexibility
expert system
air conditioning
