运行于多变边界条件下给火电机组深度节能理论研究带来新的挑战。针对这一问题,提出了多变条件下火电机组能耗基准状态概念,利用机组的海量实际运行数据,基于模糊粗糙集(fuzzy rough set,FRS)约简和模糊均值聚类(fuzzy C mean,FCM)等数...运行于多变边界条件下给火电机组深度节能理论研究带来新的挑战。针对这一问题,提出了多变条件下火电机组能耗基准状态概念,利用机组的海量实际运行数据,基于模糊粗糙集(fuzzy rough set,FRS)约简和模糊均值聚类(fuzzy C mean,FCM)等数据挖掘方法构建机组性能优化知识库,在可比历史边界条件下动态寻优确定机组能耗基准状态。以某600MW亚临界机组为案例开展了实例研究,结果表明该方法具有快速、自适应性、高度复现性和可动态调整优化等特点,适用于机组在不同工况和边界条件下的能耗分析与节能诊断。展开更多
A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance i...A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.展开更多
文摘运行于多变边界条件下给火电机组深度节能理论研究带来新的挑战。针对这一问题,提出了多变条件下火电机组能耗基准状态概念,利用机组的海量实际运行数据,基于模糊粗糙集(fuzzy rough set,FRS)约简和模糊均值聚类(fuzzy C mean,FCM)等数据挖掘方法构建机组性能优化知识库,在可比历史边界条件下动态寻优确定机组能耗基准状态。以某600MW亚临界机组为案例开展了实例研究,结果表明该方法具有快速、自适应性、高度复现性和可动态调整优化等特点,适用于机组在不同工况和边界条件下的能耗分析与节能诊断。
基金Projects(52175120,52211530085)supported by the National Natural Science Foundation of ChinaProject(CSTB2022NSCQ-MSX0318)supported by the Natural Science Foundation of Chongqing,China。
基金This work was supported by the Provincial Natural Science Foundation of Hunan(No.04JJ6033) the Research Foundation of Hunan Education Bureau (No.03C066).
文摘A sliding mode variable structure control （SMVSC） based on a coordinating optimization algorithm has been developed. Steady state error and control switching frequency are used to constitute the system performance indexes in the coordinating optimization, while the tuning rate of boundary layer width （BLW） is employed as the optimization parameter. Based on the mathematical relationship between the BLW and steady-state error, an optimized BLW tuning rate is added to the nonlinear control term of SMVSC. Simulation experiment results applied to the positioning control of an electro-hydraulic servo system show the comprehensive superiority in dynamical and static state performance by using the proposed controller is better than that by using SMVSC without optimized BLW tuning rate. This succeeds in coordinately considering both chattering reduction and high-precision control realization in SMVSC.
