Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation meth...Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation method to remove outliers.Using the Pearson correlation coefficient and LightGBM feature score method,13 key operational variables were identified and used to establish a model to predict outlet nitrogen oxide(NO_(x))concentration in an SCR system with backpropagation neural network,long short-term memory(LSTM)and LSTM-attention fully connected(FC)model,respectively.The LSTM-attention FC model showed better accuracy and generalization capability compared with other models.Its mean square error,mean absolute error,and coefficient of determination on the training and test datasets were 11.32 and 12.51,3.65%and 3.97%,and 0.96 and 0.94,respectively.Furthermore,a combination of the LSTM-attention FC model with a genetic algorithm used to optimize four feature variables including ammonia pressure compensation,inlet pressure,gas inlet upper temperature,and outlet ammonia concentration.The outlet NO_(x)concentration could be controlled below 80±3 mg/m^(3),and the ammonia slip concentration could be controlled below 0.1 mg/m^(3),demonstrating that the optimization model can provide effective guidance for reducing NO_(x)emissions and ammonia slip of SCR systems.展开更多
In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number...In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.展开更多
局部阴影情况下,光伏阵列输出功率具有多峰值特性,针对最大功率点跟踪(Maximum power point tracking,MPPT)算法在实际应用中存在着收敛速度较慢,效率较低,且容易陷入局部功率极值的问题,将兼顾收敛速度、精度、功率稳定性的快速布谷鸟...局部阴影情况下,光伏阵列输出功率具有多峰值特性,针对最大功率点跟踪(Maximum power point tracking,MPPT)算法在实际应用中存在着收敛速度较慢,效率较低,且容易陷入局部功率极值的问题,将兼顾收敛速度、精度、功率稳定性的快速布谷鸟搜索(Fast cuckoo search,FCS)算法应用于光伏阵列最大功率追踪。FCS算法采用自适应步长和机会因子可避免过早收敛,全局搜索和跳出局部搜索能力强,收敛速度快,算法后期局部开发能力强,功率振荡小,功率输出稳定,最大功率追踪精度高。仿真表明,在静态阴影、动态阴影条件下,FCS算法较灰狼算法(Grey wolf optimizer,GWO)、粒子群算法(Particle swarm optimization,PSO)具有更快地收敛速度和更高的收敛精度,且稳定性好,有效地提升光伏阵列的输出效率。展开更多
This paper briefly states the features and advantages of FCS （fieldbus control system）. In view of condensate water fined processing system of domestic 600 MW supercritical coal-fired generating units, it designed a...This paper briefly states the features and advantages of FCS （fieldbus control system）. In view of condensate water fined processing system of domestic 600 MW supercritical coal-fired generating units, it designed and developed a FCS for entirely process control, designed computer monitoring software and organized network monitor the change of data. At the same time, making the simulation device of the system, the FCS control system scheme is implemented on this device. It is verified by practice that the system control technology is advanced, safe, reliable and operation well. It provides a complete project for automation technology upgrade program in power plant. In addition, this device can be used in the power industry technical personnel training and teaching of colleges and universities. It is worth promotion and reference.展开更多
基金This work was supported by the SINOPEC:Development of Remote Diagnosis Technology for FCC Flue Gas Desulfurization and Denitrification(320076).
文摘Samples(25500)were collected from a selective catalytic reduction(SCR)denitrification system in a fluid catalytic cracking unit and preprocessed using the quartile method and the K-nearest neighbors interpolation method to remove outliers.Using the Pearson correlation coefficient and LightGBM feature score method,13 key operational variables were identified and used to establish a model to predict outlet nitrogen oxide(NO_(x))concentration in an SCR system with backpropagation neural network,long short-term memory(LSTM)and LSTM-attention fully connected(FC)model,respectively.The LSTM-attention FC model showed better accuracy and generalization capability compared with other models.Its mean square error,mean absolute error,and coefficient of determination on the training and test datasets were 11.32 and 12.51,3.65%and 3.97%,and 0.96 and 0.94,respectively.Furthermore,a combination of the LSTM-attention FC model with a genetic algorithm used to optimize four feature variables including ammonia pressure compensation,inlet pressure,gas inlet upper temperature,and outlet ammonia concentration.The outlet NO_(x)concentration could be controlled below 80±3 mg/m^(3),and the ammonia slip concentration could be controlled below 0.1 mg/m^(3),demonstrating that the optimization model can provide effective guidance for reducing NO_(x)emissions and ammonia slip of SCR systems.
基金supported in part by the National Key Research and Development Program of China(2018YFA0702200)the National Natural Science Foundation of China(52377079,62203097,62373196)。
文摘In this paper,a class of time-varying output group formation containment control problem of general linear hetero-geneous multiagent systems(MASs)is investigated under directed topology.The MAS is composed of a number of tracking leaders,formation leaders and followers,where two different types of leaders are used to provide reference trajectories for movement and to achieve certain formations,respectively.Firstly,compen-sators are designed whose states are estimations of tracking lead-ers,based on which,a controller is developed for each formation leader to accomplish the expected formation.Secondly,two event-triggered compensators are proposed for each follower to evalu-ate the state and formation information of the formation leaders in the same group,respectively.Subsequently,a control protocol is designed for each follower,utilizing the output information,to guide the output towards the convex hull generated by the forma-tion leaders within the group.Next,the triggering sequence in this paper is decomposed into two sequences,and the inter-event intervals of these two triggering conditions are provided to rule out the Zeno behavior.Finally,a numerical simulation is intro-duced to confirm the validity of the proposed results.
文摘局部阴影情况下,光伏阵列输出功率具有多峰值特性,针对最大功率点跟踪(Maximum power point tracking,MPPT)算法在实际应用中存在着收敛速度较慢,效率较低,且容易陷入局部功率极值的问题,将兼顾收敛速度、精度、功率稳定性的快速布谷鸟搜索(Fast cuckoo search,FCS)算法应用于光伏阵列最大功率追踪。FCS算法采用自适应步长和机会因子可避免过早收敛,全局搜索和跳出局部搜索能力强,收敛速度快,算法后期局部开发能力强,功率振荡小,功率输出稳定,最大功率追踪精度高。仿真表明,在静态阴影、动态阴影条件下,FCS算法较灰狼算法(Grey wolf optimizer,GWO)、粒子群算法(Particle swarm optimization,PSO)具有更快地收敛速度和更高的收敛精度,且稳定性好,有效地提升光伏阵列的输出效率。
文摘This paper briefly states the features and advantages of FCS （fieldbus control system）. In view of condensate water fined processing system of domestic 600 MW supercritical coal-fired generating units, it designed and developed a FCS for entirely process control, designed computer monitoring software and organized network monitor the change of data. At the same time, making the simulation device of the system, the FCS control system scheme is implemented on this device. It is verified by practice that the system control technology is advanced, safe, reliable and operation well. It provides a complete project for automation technology upgrade program in power plant. In addition, this device can be used in the power industry technical personnel training and teaching of colleges and universities. It is worth promotion and reference.
