{"title":"Distributed Fault Diagnosis Approach for Large-Scale Interconnected Systems with Communication Link Failures","authors":"Hao Wang, Hao Luo, Yuchen Jiang, M. Huo","doi":"10.1109/ICPS58381.2023.10128094","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128094","url":null,"abstract":"This paper considers the problem of distributed fault diagnosis of interconnected systems with communication link failures. The state coupling between subsystems brings great challenges to the design of fault diagnosis observers. In the distributed design scheme, it is usually necessary to transmit information between subsystem observers. Once any communication link failures, all fault diagnosis observers will not work. To solve this problem, two distributed algorithms based on average consensus are used for the design of distributed fault diagnosis observer respectively. In the case that the communication topology graph is a strongly connected graph, the proposed distributed algorithm can still achieve accurate diagnosis of the fault of the system. Finally, the three-tank system and the power network system are used to verify the feasibility and effectiveness of the proposed distributed design method.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117005186","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}
{"title":"Multimode DALSTM model for anomaly detection of nuclear reactor core","authors":"Yingnan Wang, Xin Wang, Ying-Lin Wang, Xianming Li, Chunhui Zhao, Zhihong Lv","doi":"10.1109/ICPS58381.2023.10128088","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128088","url":null,"abstract":"The nuclear reactor core is a life-critical system, whose reliable operation ensures the safety of a nuclear power plant. The reactor core temperature is a direct representation of the reactor core state. Therefore, the detection and analysis of core temperature anomalies is of great importance. However, multiple temperature variables are nonlinear and complexly coupled, showing different distribution characteristics with the variations of operating condition. For this reason, a multi-mode anomaly monitoring strategy for core temperature in nuclear power plant is proposed. To realize the nonlinear feature extraction of multiple temperature variables, a deep auto-encoder and long short-term memory (DALSTM) network are constructed. Considering the complex temperature distribution characteristics, the nonlinear features are clustered to divide the data into different subspaces. In this way, the distribution features are similar in the same subspace. Finally, local DALSTM models of core temperature in different subspaces are developed, and a multimode DALSTM monitoring strategy is designed. The monitoring statistics of the local models reflect the detailed variations of the process and achieve fine-grained detection of anomalous behavior. The effectiveness of the proposed model is verified by real operation data. The experimental results show that the method can achieve fast and accurate anomaly detection for reactor core temperature.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"79 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115994707","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}
Yulong Yang, Weihua Cao, Linwei Guo, Chao Gan, Min Wu
{"title":"Reinforcement Learning with Reward Shaping and Hybrid Exploration in Sparse Reward Scenes","authors":"Yulong Yang, Weihua Cao, Linwei Guo, Chao Gan, Min Wu","doi":"10.1109/ICPS58381.2023.10128012","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128012","url":null,"abstract":"High precision modeling in industrial systems is difficult and costly. Model-free intelligent control methods, represented by reinforcement learning, have been applied in industrial systems broadly. The hard evaluated of production states and the low value density of processing data causes sparse rewards, which lead to an insufficient performance of reinforcement learning. To overcome the difficulty of reinforcement learning in sparse reward scenes, a reinforcement learning method with reward shaping and hybrid exploration is proposed. By perfecting the rewards distribution in the state space of environment, the reward shaping can make the state-value estimation of reinforcement learning more accurate. By improving the rewards distribution in time dimension, the hybrid exploration can make the iteration of reinforcement learning more efficient and more stable. Finally, the effectiveness of the proposed method is verified by simulations.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126134611","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}
{"title":"Observer-based trajectory inclination control with weight-on-bit uncertainty in directional drilling systems","authors":"Zhen Cai, Shigang Wang, Gang Hao","doi":"10.1109/ICPS58381.2023.10128086","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128086","url":null,"abstract":"This study concerns trajectory inclination control with the uncertainty of weight-on-bit for the directional drilling process. The trajectory inclination model considers the variation of weight-on-bit and accounts for the uncertainty term of the model. A two-layer observer-based control scheme of the trajectory inclination is developed to compensate for the unavailability of direct measurement of trajectory inclination, the uncertainty of weight-on-bit, and external disturbances. The system's stability is analyzed through the Lyapunov function and then converted to a linear matrix inequality (LMI) form to obtain the control parameter gains. Eventually, some simulations manifest our control system can effectively eliminate the influence of uncertainty of weiaht-on-bit and external disturbances.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"9 5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131661600","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}
Yahao Yang, Junfeng Zhang, Shenmin Zhang, Huizhou Liu
{"title":"Mode Estimation and Event-Triggered Filter of Switched Positive Systems With Switching Faults","authors":"Yahao Yang, Junfeng Zhang, Shenmin Zhang, Huizhou Liu","doi":"10.1109/ICPS58381.2023.10128052","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128052","url":null,"abstract":"This paper proposes the static and dynamic event-triggered filters of switched positive systems with switching faults, respectively. Under the switching fault, the active mode to be implemented is unknown. A static event-triggering condition is established by virtue of 1-norm inequality. An active mode estimation approach is presented based on the observer of the systems. Unknown active mode is identified by judging the minimum of a norm with respect to the error of the system output and the observer output. Thus, an asynchronous filter is designed for estimating the output when the active mode is identified. Moreover, a new dynamic event-triggered filter is proposed for the considered systems with switching faults. By using multiple copositive Lyapunov functions, linear programming, and matrix decomposition approaches, the observer and filter gains are designed, respectively. Finally, one illustrative example is given to verify the effectiveness of the obtained results.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128845034","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}
Hongcheng Zhu, Chensheng Liu, Min Zhou, Yang Tang, Wenli Du
{"title":"Load Redistribution Attack in Optimal Power Flow with Phase Shifting Transformers","authors":"Hongcheng Zhu, Chensheng Liu, Min Zhou, Yang Tang, Wenli Du","doi":"10.1109/ICPS58381.2023.10127987","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10127987","url":null,"abstract":"With the increasing integration of distributed energy resources (DER) and corresponding fluctuations, phase shifting transformers (PSTs) have been considered as important electrical components to increase transmission capacity by integrating PST with optimal power flow (OPF). However, due to vulnerabilities of supervisory control and data acquisition (SCADA) systems, applications in power systems may be subject to various cyber-attacks. In this paper, we discuss the feasibility of load redistri-bution (LR) attacks against OPF with PST, and quantitatively evaluate the effect of LR attacks on power systems. Specifically, the interaction between LR attacker and OPF with PST is formulated as a Stackelberg game, where the attacker and power system, acting as the leader and follower, attempt to maximize and minimize the operation cost of power system, respectively. By replacing the lower OPF optimization with its Karush-Kuhn-Tucker (KKT) condition, the Stackelberg game is simplified into a single-level mixed integer programming, which can be easily solved. Simulations in the PJM 5-bus, IEEE 14-bus and IEEE 30-bus test systems verify the feasibility of LR attacks and quantitatively evaluate the effect of LR attacks on the operation cost of power systems.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126806466","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}
Qifu Chen, Jinhua She, Min Wu, Zhuofu Zhang, Zhenhong Liao
{"title":"Design and Development of Big Data System for Blast Furnace Ironmaking","authors":"Qifu Chen, Jinhua She, Min Wu, Zhuofu Zhang, Zhenhong Liao","doi":"10.1109/ICPS58381.2023.10127866","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10127866","url":null,"abstract":"The process of blast furnace ironmaking is com-posed of several sub-processes. The process of blast furnace smelting is complicated and the data of each sub-process are scattered and not concentrated. The traditional working mode of subjective judgment based on manual experience is not conducive to the stable production of the blast furnace. Therefore, this paper develops a big data system for the production process of blast furnace, which is of great significance to realize the digital production and intelligent production of blast furnace. According to the system architecture of blast furnace ironmaking, this paper mainly designs and develops the data acquisition layer, data storage layer, data analysis layer and data application layer of the big data system.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114227039","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}
{"title":"Health Condition Monitoring of Satellite Momentum Wheel Bearing Based on Canonical Variable Analysis and Sliding Interval Variance","authors":"Sirui Du, Shumei Zhang, Yang Zhao","doi":"10.1109/ICPS58381.2023.10128101","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128101","url":null,"abstract":"With the rapid development of space technology, the demand for satellite reliability is getting higher and higher. Momentum wheel is a key component of satellite attitude control system, and its reliability is an important factor affecting the life of satellite. The condition monitoring of momentum wheel bearing (MWB) is of great significance to ensure the long life and high reliable operation of the satellite. In this paper, a new monitoring method based on multivariate statistics and canonical variable analysis (CVA) is proposed, and a new health degree function is defined from both dynamic and static aspects. First, the time-frequency domain analysis technique is used to extract the features of MWB in time domain, frequency domain and time-frequency domain, and the multi-domain high-dimensional health condition feature set is constructed. Then, in order to reduce the complexity of the problem, feature reduction is realized based on CVA. On the basis of considering steady-state error and sliding interval variance (SIV), the health degree (HD) characterizing the performance condition of MWB is defined. Finally, the experimental results based on the bearing test-bed show that the proposed method is feasible and effective, and the data-driven health condition monitoring of satellite momentum wheel bearing is realized.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126985104","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}
{"title":"Equivalent Input Disturbance-based Model Predictive Control of Shaking Table System","authors":"Q. Lei, Cheng Wang","doi":"10.1109/ICPS58381.2023.10128075","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128075","url":null,"abstract":"The accuracy of seismic wave tracking of seismic shaking table has an important impact on the reliability of structural seismic tests. To precise realize waveform tracking of shaking table, an equivalent input disturbance-based model predictive control (MPCEID) method is developed in this paper. The MPCEID method is construct by incorporating disturbance information estimated by EID into optimization framework of MPC. Thus control system consist of two parts, where MPC is mainly used for tracking the reference input and EID part is mainly used for disturbance suppression. The disturbance missed by EID is compensated by the feedback suppression capability of MPC, thus the overall immunity of the system is enhanced. Meanwhile the EID part is used to estimate the disturbance and compensate uncertainty, and thus improve the robustness of MPC algorithm. In this paper, a hydraulically driven shaking table model is established. Then, disturbance and uncertainty is treated as total disturbances, MPCEID is designed to suppress total disturbances. Finally, simulation experiments are carried out under different scenarios. The validity of the proposed method is demonstrated by comparing the control performance of EID, MPC, and MPCEID.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133094428","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}
{"title":"Blast Furnace Gas Utilization Rate Prediction Model based on Northern Goshawk Optimization and Long Short-Term Memory in Massive Data Set","authors":"Yue Zhou, Weihua Cao, Zhuofu Zhang, Yan Yuan","doi":"10.1109/ICPS58381.2023.10128035","DOIUrl":"https://doi.org/10.1109/ICPS58381.2023.10128035","url":null,"abstract":"Affected by the global New Crown Pneumonia epidemic, energy prices in the global market continue to rise. The high quality production and energy saving of steel companies have become an important task. The blast furnace is the front-end core of the steel manufacturing process. The blast furnace gas utilization rate can effectively characterize the internal airflow distribution, blast furnace operation and energy consumption level of the blast furnace. The blast furnace Gas Utilization Rate (GUR) can effectively characterize the internal airflow distribution, blast furnace operation and energy consumption level. Most of the existing studies are based on data-driven models. The shallow neural network model is selected. But blast furnace iron making has complex uncertainty. Massive data samples under industrial information technology need to be processed. The robustness and generalization ability of the prediction model are not satisfactory. To address the above problems, this paper proposes a prediction model based on NGO-LSTM regression. The model parameter searchs can be intelligently. It achieves high-precision prediction results for massive data samples. Firstly, the selection of feature parameters is completed by maximal information coefficient. Secondly, the strong coupling of blast furnace ground needs to fully predict the relationship between the characteristic parameters. The Long Short-Term Memory (LSTM) neural network with certain memory capability is selected. And multiple parameters of this neural network model are optimized by the Northern Goshawk Optimization (NGO) algorithm. An NGO-LSTM regression prediction model is established. In this paper, experiments are carried out using actual production data. The experimental results show that the proposed method can accurately predict the blast furnace gas utilization rate. This can provide a reference for improving blast furnace product quality, reducing costs and increasing efficiency.","PeriodicalId":426122,"journal":{"name":"2023 IEEE 6th International Conference on Industrial Cyber-Physical Systems (ICPS)","volume":"167 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133457536","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}