摘要
控制器的性能通常表现为多个属性指标,综合涉及了随机性和确定性性能,为此,提出了一个相适应的评价方法。根据特定控制回路对于控制性能的不同要求,对各属性指标分配不同的权重;考虑到不同扰动对于控制性能评价基准的影响,提出了一个基于BP神经网络的过程扰动识别方法;基于历史数据建立评价基准,应用多属性决策方法得出控制器的综合属性评价值,数值实例仿真和TE过程实验证明了所提出方法的有效性。
Performance of a controller usually involves many attributes,including stochastic and deterministic ones.This paper proposes an assessment approach on controller performance.According to different demands of a specific control loop,an appropriate weight is assigned to every attribute index. Besides,considering the impact of different disturbances on assessment benchmarks,a BP network-based process disturbance identification is introduced.Moreover,the assessment benchmark is established based on historical data and a multi-attribute decision-making method is employed to achieve a comprehensive attribute assessment result.Both numerical simulation and TE process experiment demonstrate the effectiveness of the proposed method.
出处
《华东理工大学学报（自然科学版）》
CAS
CSCD
北大核心
2014年第2期244-249,共6页
Journal of East China University of Science and Technology
关键词
控制器性能评价
多属性决策
神经网络
controller performance assessment
multi-attribute decision-making
neural networks
