Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721978
Yupeng Zhai, X. Li, Kang Wang
Crime prediction is of great significance to the food safety defense work of major events. The traditional crime prediction depends on the experience of police officers, which is highly subjective and can not be predicted in advance. This paper analyzes and processes food safety police data, combines the characteristics of food crimes, uses stacking model fusion method to predict the food crime tendency of key personnel, and verifies the model through the Recall Rate. The results show that the integrated learning model has high accuracy and can effectively predict the food crime tendency of key personnel.
{"title":"Research on the Prediction Model of Key Personnel's Food Crime Based on Stacking Model Fusion","authors":"Yupeng Zhai, X. Li, Kang Wang","doi":"10.1109/ICCSS53909.2021.9721978","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721978","url":null,"abstract":"Crime prediction is of great significance to the food safety defense work of major events. The traditional crime prediction depends on the experience of police officers, which is highly subjective and can not be predicted in advance. This paper analyzes and processes food safety police data, combines the characteristics of food crimes, uses stacking model fusion method to predict the food crime tendency of key personnel, and verifies the model through the Recall Rate. The results show that the integrated learning model has high accuracy and can effectively predict the food crime tendency of key personnel.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"43 ","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993143","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Graph neural networks are widespreadly used in the field of graph data analysis and processing. Recent methods either reduce the spatial receptive field for low algorithm complexity, or greatly lose efficiency in order to realize attention mechanism. To tackle this issue, we propose Iteration Graph Network (IGN), which uses an iterative inversion method to aggregate node feature and the k-localized neighbor information of nodes. In the graph-based semi-supervised node classification task, our method surpasses the state-of-the-art method in the benchmark datasets and experiment conclusion show that our model outperforms graph attention networks (GAT) and is more than 3 times faster than graph attention networks, consumes more than 6 times less memory than GAT. Our code will be make publicly available.
{"title":"Iteration Graph Network","authors":"Wenchuan Zhang, Weihua Ou, Shili Niu, Ruxin Wang, Ziqi Zhu, Shen Ke","doi":"10.1109/ICCSS53909.2021.9721961","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721961","url":null,"abstract":"Graph neural networks are widespreadly used in the field of graph data analysis and processing. Recent methods either reduce the spatial receptive field for low algorithm complexity, or greatly lose efficiency in order to realize attention mechanism. To tackle this issue, we propose Iteration Graph Network (IGN), which uses an iterative inversion method to aggregate node feature and the k-localized neighbor information of nodes. In the graph-based semi-supervised node classification task, our method surpasses the state-of-the-art method in the benchmark datasets and experiment conclusion show that our model outperforms graph attention networks (GAT) and is more than 3 times faster than graph attention networks, consumes more than 6 times less memory than GAT. Our code will be make publicly available.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130462067","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721943
Chang-Yue Zhang, Shiyuan Han, Jin Zhou, Baozhu Li, Xiao-Jie Yu, Kang Yao
The communication between vehicles has attracted more and more attention in intelligent transportation system(ITS). Due to the rapid movement of vehicles, the topology of network nodes changes rapidly, resulting in collisions between vehicles. Therefore, the design of efficient and reliable media access control protocol is very necessary to solve the communication problem between vehicles. In this paper, a merge collision prediction TDMA-MAC in distributed VANET(MCPMAC) is proposed to solve the merging collision problem. In MCPMAC, when multiple vehicles occupying the same time slot meet within the two hop communication range, one vehicle continues to use the time slot by comparing the time stamp of the vehicle access time slot, and the other vehicles sequentially select the idle time slot to reduce the probability of merging collision between vehicles. Simulation results show MCPMAC protocol has higher reliability and lower number of collisions than the existing MAC protocols.
{"title":"A Merge Collision Prediction TDMA-MAC Protocol in Distributed VANET","authors":"Chang-Yue Zhang, Shiyuan Han, Jin Zhou, Baozhu Li, Xiao-Jie Yu, Kang Yao","doi":"10.1109/ICCSS53909.2021.9721943","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721943","url":null,"abstract":"The communication between vehicles has attracted more and more attention in intelligent transportation system(ITS). Due to the rapid movement of vehicles, the topology of network nodes changes rapidly, resulting in collisions between vehicles. Therefore, the design of efficient and reliable media access control protocol is very necessary to solve the communication problem between vehicles. In this paper, a merge collision prediction TDMA-MAC in distributed VANET(MCPMAC) is proposed to solve the merging collision problem. In MCPMAC, when multiple vehicles occupying the same time slot meet within the two hop communication range, one vehicle continues to use the time slot by comparing the time stamp of the vehicle access time slot, and the other vehicles sequentially select the idle time slot to reduce the probability of merging collision between vehicles. Simulation results show MCPMAC protocol has higher reliability and lower number of collisions than the existing MAC protocols.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132029402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721952
Xiaoyue Cao, Chunfang Liu, Xiaoli Li
Although robotic grippers have been extensively used in industry nowadays, most of them still are lack of tactile perception to achieve some dexterous manipulation like grasping an unknown object using appropriate force. Hence, to make the grippers gain multiple types of tactile information, we combine the gripper with the dual-modal vision-based tactile sensor in our experiment. Different from existed texture recognition experiments, we build own texture dataset included 12 kinds of samples using the novel tactile transducer. At the same time, we compare K-Nearest Neighbor (KNN) with Residual Network (ResNet), the experiment results showcase that the accuracy of KNN, is only 66.11%, while the accuracy of ResNet based on deep convolution neural network is as high as 100.00%. In addition, to detect the contact force, we employ the nonlinear characteristic of BP neural network to establish the mapping relation between the two-dimensional displacement image of markers and the three-dimensional (3D) force vector. Experiments are implemented to demonstrate the sensor’s performance of predicting the force within 4% margin of error.
{"title":"Texture Recognition and Three-Dimensional Force Measurement Using Vision-based Tactile Sensor","authors":"Xiaoyue Cao, Chunfang Liu, Xiaoli Li","doi":"10.1109/ICCSS53909.2021.9721952","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721952","url":null,"abstract":"Although robotic grippers have been extensively used in industry nowadays, most of them still are lack of tactile perception to achieve some dexterous manipulation like grasping an unknown object using appropriate force. Hence, to make the grippers gain multiple types of tactile information, we combine the gripper with the dual-modal vision-based tactile sensor in our experiment. Different from existed texture recognition experiments, we build own texture dataset included 12 kinds of samples using the novel tactile transducer. At the same time, we compare K-Nearest Neighbor (KNN) with Residual Network (ResNet), the experiment results showcase that the accuracy of KNN, is only 66.11%, while the accuracy of ResNet based on deep convolution neural network is as high as 100.00%. In addition, to detect the contact force, we employ the nonlinear characteristic of BP neural network to establish the mapping relation between the two-dimensional displacement image of markers and the three-dimensional (3D) force vector. Experiments are implemented to demonstrate the sensor’s performance of predicting the force within 4% margin of error.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134534436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721955
Hongxin Dong, Zhongyang Han, Jun Zhao, Wei Wang
Energy supply security is the basis to ensure a stable operation of integrated energy system (IES). The selection of appropriate indicators and calculation methods play a pivotal role in the field of security assessment. Considering the strong coupling of multi-energy flows, large system scale and complex structure, the traditional methods which only consider single energy flow and a fixed load mode are not accurate enough to evaluate the energy supply security. To solve the above problems, a load margin assessment method based on the improved continuation power flow (CPF) is proposed in this study. Firstly, according to the steady state of electricity-heat system, a general mechanism-based model related to load increase is developed as the basic algorithm for the CPF process. Next, the CPF method is extended to the IES, where the directions of the load increase are set by the first-order difference to describe the states of the system in real-time. Considering that the load increase should be restricted in a practical range for real-world application, this paper proposes a non-negative lower load limit setting method based on empirical probability distribution. Finally, experiments on both a typical IES and an IES of an industrial park in China are performed, which validates the effectiveness and practicability of the proposed method for quantitative security assessment of electricity-heat system.
{"title":"Load Margin Assessment of Electricity-heat System Based on the Improved CPF","authors":"Hongxin Dong, Zhongyang Han, Jun Zhao, Wei Wang","doi":"10.1109/ICCSS53909.2021.9721955","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721955","url":null,"abstract":"Energy supply security is the basis to ensure a stable operation of integrated energy system (IES). The selection of appropriate indicators and calculation methods play a pivotal role in the field of security assessment. Considering the strong coupling of multi-energy flows, large system scale and complex structure, the traditional methods which only consider single energy flow and a fixed load mode are not accurate enough to evaluate the energy supply security. To solve the above problems, a load margin assessment method based on the improved continuation power flow (CPF) is proposed in this study. Firstly, according to the steady state of electricity-heat system, a general mechanism-based model related to load increase is developed as the basic algorithm for the CPF process. Next, the CPF method is extended to the IES, where the directions of the load increase are set by the first-order difference to describe the states of the system in real-time. Considering that the load increase should be restricted in a practical range for real-world application, this paper proposes a non-negative lower load limit setting method based on empirical probability distribution. Finally, experiments on both a typical IES and an IES of an industrial park in China are performed, which validates the effectiveness and practicability of the proposed method for quantitative security assessment of electricity-heat system.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"49 3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133754349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721964
Yuning Cao, Zhiguang Feng, Yanmin Liu
The inquiry into real-time reachable set estimation for singular systems is conducted in this paper. By applying Lyapunov stability principle, the method mentioned underneath can estimate the reachable set in real time, A competent condition is set up in the form of linear matrix inequality (LMI) to ensure that the reachable set of singular system is confined in real-time by an array of ellipsoids. The authority of the results presented in this paper is illuminated by a numerical example.
{"title":"Real-time Reachable Set Estimation of Discrete-time Singular Systems","authors":"Yuning Cao, Zhiguang Feng, Yanmin Liu","doi":"10.1109/ICCSS53909.2021.9721964","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721964","url":null,"abstract":"The inquiry into real-time reachable set estimation for singular systems is conducted in this paper. By applying Lyapunov stability principle, the method mentioned underneath can estimate the reachable set in real time, A competent condition is set up in the form of linear matrix inequality (LMI) to ensure that the reachable set of singular system is confined in real-time by an array of ellipsoids. The authority of the results presented in this paper is illuminated by a numerical example.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"159 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134094443","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9722003
Xinyue Qiao, Yuxin Wu, De-yuan Meng
In the process of forming average consensus, the privacy that the agents do not want to disclose may be maliciously speculated and used by others. To avoid breaches of privacy for multi-agent systems subject to directed topologies, we propose a novel privacy-preserving average consensus algorithm that employs an improved Laplacian-type control protocol. It is shown that all agents can achieve accurate average consensus without the weight-balance condition despite directed topologies. To ward off internal malicious agents, we add edge-based zero-sum interference signals in the process of transferring information. Thus, by introducing a private parameter, all agents can be protected against malicious eavesdroppers who know the entire topology and can intercept communication links. Two simulation examples are presented to demonstrate the validity of our algorithms for realizing the average consensus under the impacts of malicious adversaries.
{"title":"Privacy-Preserving Average Consensus for Multi-agent Systems with Directed Topologies","authors":"Xinyue Qiao, Yuxin Wu, De-yuan Meng","doi":"10.1109/ICCSS53909.2021.9722003","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9722003","url":null,"abstract":"In the process of forming average consensus, the privacy that the agents do not want to disclose may be maliciously speculated and used by others. To avoid breaches of privacy for multi-agent systems subject to directed topologies, we propose a novel privacy-preserving average consensus algorithm that employs an improved Laplacian-type control protocol. It is shown that all agents can achieve accurate average consensus without the weight-balance condition despite directed topologies. To ward off internal malicious agents, we add edge-based zero-sum interference signals in the process of transferring information. Thus, by introducing a private parameter, all agents can be protected against malicious eavesdroppers who know the entire topology and can intercept communication links. Two simulation examples are presented to demonstrate the validity of our algorithms for realizing the average consensus under the impacts of malicious adversaries.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134599589","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9722006
Tianzheng Wang, Jian Tang, Heng Xia, Xiaotong Pan
The complex industrial process is consisted of multiple loops with coupling relation. They have the characteristics of strong nonlinearity and non-stationary. So it is difficult to describe them with precise mathematical models. Thus, the design of control systems about complex industrial process mainly relies on repeated experiments and debugging on the actual system. Moreover, the novel operational optimization control algorithms cannot directly applied to the operation of industrial processes in terms of factors like safety requirement and economic cost. Therefore, it is necessary to build simulation platforms of complex industrial process to solve these issues. In order to construct an effective simulation platform, a review on different simulation platforms is made in this paper. The existing simulation platforms for industrial process are divided into four categories. They are real control system and real controlled object, real control system and virtual controlled object, virtual control system and real controlled object and virtual control system and virtual controlled object. Then, their structure and application background are analyzed in detail. The existing problems are also summarized. Finally, the conclusion and prospect of simulation platforms for industrial process are given out.
{"title":"A Review on Simulation Platforms for Complex Industrial Process","authors":"Tianzheng Wang, Jian Tang, Heng Xia, Xiaotong Pan","doi":"10.1109/ICCSS53909.2021.9722006","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9722006","url":null,"abstract":"The complex industrial process is consisted of multiple loops with coupling relation. They have the characteristics of strong nonlinearity and non-stationary. So it is difficult to describe them with precise mathematical models. Thus, the design of control systems about complex industrial process mainly relies on repeated experiments and debugging on the actual system. Moreover, the novel operational optimization control algorithms cannot directly applied to the operation of industrial processes in terms of factors like safety requirement and economic cost. Therefore, it is necessary to build simulation platforms of complex industrial process to solve these issues. In order to construct an effective simulation platform, a review on different simulation platforms is made in this paper. The existing simulation platforms for industrial process are divided into four categories. They are real control system and real controlled object, real control system and virtual controlled object, virtual control system and real controlled object and virtual control system and virtual controlled object. Then, their structure and application background are analyzed in detail. The existing problems are also summarized. Finally, the conclusion and prospect of simulation platforms for industrial process are given out.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114732329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721998
Pengyu Song, Chunhui Zhao, Jinliang Ding, Youxian Sun, Xuanxuan Jin
The structure of modern industrial processes has been gradually complicated to adapt to diversified production requirements. Process variables generally have temporal characteristics. Meanwhile, complex spatial interactions between variables also pose challenges for process modeling. In this study, a parallel temporal and spatial feature extraction framework is proposed and applied to fault detection and isolation in industrial processes. On the one hand, unlike the existing methods with mixed spatiotemporal information, we design independent temporal and spatial modeling structures. The temporal characteristics of each process variable are simultaneously extracted in the designed temporal submodule. Furthermore, the spatial connections between variables are captured through sparse adjacency network extraction and information fusion. In this way, the temporal and spatial information can be individually observed to provide interpretable monitoring results. On the other hand, considering the different spatiotemporal anomalies caused by various fault types, we establish a targeted isolation strategy to provide reliable fault analysis. For temporal faults, the reconstruction error indicators are designed to quantify the abnormality of the variable. Moreover, a network reconstruction model is developed to measure the spatial structure deviation and locate the fault source. The performance of the proposed method is verified through a real industrial example.
{"title":"Parallel Temporal and Spatial Modeling for Interpretable Fault Detection and Isolation of Industrial Processes","authors":"Pengyu Song, Chunhui Zhao, Jinliang Ding, Youxian Sun, Xuanxuan Jin","doi":"10.1109/ICCSS53909.2021.9721998","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721998","url":null,"abstract":"The structure of modern industrial processes has been gradually complicated to adapt to diversified production requirements. Process variables generally have temporal characteristics. Meanwhile, complex spatial interactions between variables also pose challenges for process modeling. In this study, a parallel temporal and spatial feature extraction framework is proposed and applied to fault detection and isolation in industrial processes. On the one hand, unlike the existing methods with mixed spatiotemporal information, we design independent temporal and spatial modeling structures. The temporal characteristics of each process variable are simultaneously extracted in the designed temporal submodule. Furthermore, the spatial connections between variables are captured through sparse adjacency network extraction and information fusion. In this way, the temporal and spatial information can be individually observed to provide interpretable monitoring results. On the other hand, considering the different spatiotemporal anomalies caused by various fault types, we establish a targeted isolation strategy to provide reliable fault analysis. For temporal faults, the reconstruction error indicators are designed to quantify the abnormality of the variable. Moreover, a network reconstruction model is developed to measure the spatial structure deviation and locate the fault source. The performance of the proposed method is verified through a real industrial example.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"86 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116307594","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-10DOI: 10.1109/ICCSS53909.2021.9721996
Wang Tong, Han Hong-gui, Sun Hao-yuan, Yang Hong-yan, Wu Xiao-long
The control of internal flow and external carbon is crucial for the municipal wastewater denitrification process. However, due to the disturbance and interactions in the process, it is difficult to achieve suitable control performance. To solve this problem, a robust multivariable control (RMC) scheme is proposed to improve the process control efficiency. First, a mechanism-based control method is designed to provide an explicit control signal that mitigates the effect of load changes. Second, a robust control method, using a fuzzy neural network sliding mode controller, is developed to improve the tracking accuracy. Third, an adaptive learning algorithm is proposed to tune the parameters of RMC so that the closed-loop system is stable in the term of Lyapunov stability theory. Finally, the benchmark simulations of municipal wastewater denitrification process demonstrate that, compared with other control strategies, the proposed method yields a stable control performance with an obvious energy saving effect.
{"title":"Robust Multivariable Control for Municipal Wastewater Denitrification Process","authors":"Wang Tong, Han Hong-gui, Sun Hao-yuan, Yang Hong-yan, Wu Xiao-long","doi":"10.1109/ICCSS53909.2021.9721996","DOIUrl":"https://doi.org/10.1109/ICCSS53909.2021.9721996","url":null,"abstract":"The control of internal flow and external carbon is crucial for the municipal wastewater denitrification process. However, due to the disturbance and interactions in the process, it is difficult to achieve suitable control performance. To solve this problem, a robust multivariable control (RMC) scheme is proposed to improve the process control efficiency. First, a mechanism-based control method is designed to provide an explicit control signal that mitigates the effect of load changes. Second, a robust control method, using a fuzzy neural network sliding mode controller, is developed to improve the tracking accuracy. Third, an adaptive learning algorithm is proposed to tune the parameters of RMC so that the closed-loop system is stable in the term of Lyapunov stability theory. Finally, the benchmark simulations of municipal wastewater denitrification process demonstrate that, compared with other control strategies, the proposed method yields a stable control performance with an obvious energy saving effect.","PeriodicalId":435816,"journal":{"name":"2021 8th International Conference on Information, Cybernetics, and Computational Social Systems (ICCSS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-12-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130786508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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