Pub Date : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10166648
Hao Nie, Jinna Li
Optimal control design methods for multiple time-scale systems are a hot research topic in recent years. In this paper, a comprehensive overview of the design methods for optimal control of multiple time-scale systems is presented. Firstly, the mathematical model of the optimal control problem of multiple time-scale systems is given, and the key difficulties of the related research are analysed. Secondly, the design methods for optimal control of multiple time-scale systems based on the model and reinforcement learning (RL) methods are given respectively. Thirdly, the performance analysis and practical application of the multi-time scale system are analyzed. Finally, the current problems in solving the optimization of multiple time-scale systems are analysed, and the research directions of optimal control of multiple time-scale systems are prospected.
{"title":"An Overview of Optimal Control Methods for Singularly Perturbed Systems","authors":"Hao Nie, Jinna Li","doi":"10.1109/DDCLS58216.2023.10166648","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166648","url":null,"abstract":"Optimal control design methods for multiple time-scale systems are a hot research topic in recent years. In this paper, a comprehensive overview of the design methods for optimal control of multiple time-scale systems is presented. Firstly, the mathematical model of the optimal control problem of multiple time-scale systems is given, and the key difficulties of the related research are analysed. Secondly, the design methods for optimal control of multiple time-scale systems based on the model and reinforcement learning (RL) methods are given respectively. Thirdly, the performance analysis and practical application of the multi-time scale system are analyzed. Finally, the current problems in solving the optimization of multiple time-scale systems are analysed, and the research directions of optimal control of multiple time-scale systems are prospected.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133053999","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10165812
Xiangyin Fei, Changzhong Pan, Lan Zhou, Peiyin Xiong, Meiliu Li
The motion control of flexible joint manipulators (FJMs) is a hot topic in the field of robot control, and the uncertainties including parameter perturbations and disturbances are the key challenges in the development of control strategies for FJMs. In this paper, we take a two-link FJM with complex uncertainties as the object, and present a command filtered backstepping control approach based on reduced-order extended state observer (RESO) for the trajectory tracking control of the two-link FJM with high precision. To enhance the robustness of the control system, an RESO which takes parameter perturbations, friction term and external disturbances as the lumped disturbances is constructed to estimate and compensate for the disturbances. The second-order command filter technique is introduced to eliminate the “explosion of complexity” problem of the conventional backstepping method, and an error compensation dynamic system is developed to reduce the potential filtering errors. All signals of the closed-loop system are proved to be uniformly ultimately bounded by Lyapunov theorem. Simulation reaults are shown to demonstrate the effectiveness and efficiency of the proposed control method.
{"title":"Command Filtered Backstepping Control of a Two-Link Flexible Joint Manipulator with Uncertainties Based on Reduced-Order ESO","authors":"Xiangyin Fei, Changzhong Pan, Lan Zhou, Peiyin Xiong, Meiliu Li","doi":"10.1109/DDCLS58216.2023.10165812","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10165812","url":null,"abstract":"The motion control of flexible joint manipulators (FJMs) is a hot topic in the field of robot control, and the uncertainties including parameter perturbations and disturbances are the key challenges in the development of control strategies for FJMs. In this paper, we take a two-link FJM with complex uncertainties as the object, and present a command filtered backstepping control approach based on reduced-order extended state observer (RESO) for the trajectory tracking control of the two-link FJM with high precision. To enhance the robustness of the control system, an RESO which takes parameter perturbations, friction term and external disturbances as the lumped disturbances is constructed to estimate and compensate for the disturbances. The second-order command filter technique is introduced to eliminate the “explosion of complexity” problem of the conventional backstepping method, and an error compensation dynamic system is developed to reduce the potential filtering errors. All signals of the closed-loop system are proved to be uniformly ultimately bounded by Lyapunov theorem. Simulation reaults are shown to demonstrate the effectiveness and efficiency of the proposed control method.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124337698","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10165958
Liangbin Wang, Renhai Yu, Jin Lv, Bo Zhang, Fuzhi Wang, Fei Teng
The application of shipboard microgrids (SMGs) makes it possible to effectively use renewable new energy on the shipboard platform. As renewable energy sources are connected to SMGs in the form of distributed generators (DGs), the openness of the system increases and so does the risk of exposure to cyber attacks. In this paper, a resilient distributed secondary frequency control strategy for SMGs is constructed to resist false data injection (FDI) attacks. An attacker can tamper with the information in the communication links between the DGs of a SMG to prevent the DGs from outputting stable power, thereby causing oscillations in the entire SMG. To increase resilience to FDI attacks, the proposed resilient control strategy introduces a control network layer interconnected with the original data transmission layer to form a hierarchical communication network. By setting the SMG parameters, the proposed strategy can well reduce the negative effects of FDI attacks on DGs and ensure the stable operation of SMGs. Finally, the simulation results verify the effectiveness of the strategy.
{"title":"Resilient Distributed Secondary Control Strategy for New Energy Shipboard Microgrid Against Bounded FDI Attacks","authors":"Liangbin Wang, Renhai Yu, Jin Lv, Bo Zhang, Fuzhi Wang, Fei Teng","doi":"10.1109/DDCLS58216.2023.10165958","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10165958","url":null,"abstract":"The application of shipboard microgrids (SMGs) makes it possible to effectively use renewable new energy on the shipboard platform. As renewable energy sources are connected to SMGs in the form of distributed generators (DGs), the openness of the system increases and so does the risk of exposure to cyber attacks. In this paper, a resilient distributed secondary frequency control strategy for SMGs is constructed to resist false data injection (FDI) attacks. An attacker can tamper with the information in the communication links between the DGs of a SMG to prevent the DGs from outputting stable power, thereby causing oscillations in the entire SMG. To increase resilience to FDI attacks, the proposed resilient control strategy introduces a control network layer interconnected with the original data transmission layer to form a hierarchical communication network. By setting the SMG parameters, the proposed strategy can well reduce the negative effects of FDI attacks on DGs and ensure the stable operation of SMGs. Finally, the simulation results verify the effectiveness of the strategy.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"100 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124706104","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10166699
Xiaoyi Huang, Yung-Chung Wang, Jizheng Chu
The water supply network is an essential infrastructure for urban life, and designing a scientific and reasonable water supply network can not only reduce construction and operation and maintenance costs but also enhance the reliability of the system. However, the design of the system involves complex constraints, as well as optimizing the pipe network is a nonlinear problem that significantly impacts construction investments. Traditional optimization methods have demonstrated poor performance in pipe network optimization due to low convergence accuracy and weak global search capabilities. To address these shortcomings, this paper proposes an Improved Sparrow Search Algorithm (ISSA) that introduces a Levy flight strategy to increase spatial search diversity and eliminate the small search space in the late iteration period and random walk around the optimal solution. The improved algorithm is applied to Hanoi, New York, and ZJ pipe networks, showing that it can efficiently find the best cost design scheme while reducing calculation cost and realizing rapid optimization of the combination optimization problem.
{"title":"Water Supply Network Optimization based on Improved Sparrow Search Algorithm","authors":"Xiaoyi Huang, Yung-Chung Wang, Jizheng Chu","doi":"10.1109/DDCLS58216.2023.10166699","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166699","url":null,"abstract":"The water supply network is an essential infrastructure for urban life, and designing a scientific and reasonable water supply network can not only reduce construction and operation and maintenance costs but also enhance the reliability of the system. However, the design of the system involves complex constraints, as well as optimizing the pipe network is a nonlinear problem that significantly impacts construction investments. Traditional optimization methods have demonstrated poor performance in pipe network optimization due to low convergence accuracy and weak global search capabilities. To address these shortcomings, this paper proposes an Improved Sparrow Search Algorithm (ISSA) that introduces a Levy flight strategy to increase spatial search diversity and eliminate the small search space in the late iteration period and random walk around the optimal solution. The improved algorithm is applied to Hanoi, New York, and ZJ pipe networks, showing that it can efficiently find the best cost design scheme while reducing calculation cost and realizing rapid optimization of the combination optimization problem.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134518789","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10167386
Xincai Li, Chunxi Yang, Xiufeng Zhang, Gengen Li
In view of the defects of noise in the industrial data of the oxygen-rich top blown smelting and time lag in off-line detection of matte grade, it is difficult to accurately establish the prediction model of process parameters. A process parameter prediction model based on wavelet denoising sparrow search algorithm optimized support vector machine (WD-SSA-SVM) was proposed. Firstly, wavelet denoising is used to improve the quality of the data. Secondly, the sparrow search algorithm was used to optimize the support vector machine to establish the nonlinear relationship model between the melting process and the process index, and the model parameters were identified by the sample data after denoising, so as to effectively predict the process index of frosted sand grade in the process of the oxygen-rich top blown smelting. The experimental results on the actual production data of a smelter show that the WD-SSA-SVM model proposed in this paper has high accuracy, meets the accuracy requirements in the actual industrial production, and can effectively guide the optimization and adjustment of the operating parameters of the oxygen-rich top blown smelting process.
{"title":"Prediction of matte grade in the oxygen-rich top blown smelting based on WD-SSA-SVM algorithm","authors":"Xincai Li, Chunxi Yang, Xiufeng Zhang, Gengen Li","doi":"10.1109/DDCLS58216.2023.10167386","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167386","url":null,"abstract":"In view of the defects of noise in the industrial data of the oxygen-rich top blown smelting and time lag in off-line detection of matte grade, it is difficult to accurately establish the prediction model of process parameters. A process parameter prediction model based on wavelet denoising sparrow search algorithm optimized support vector machine (WD-SSA-SVM) was proposed. Firstly, wavelet denoising is used to improve the quality of the data. Secondly, the sparrow search algorithm was used to optimize the support vector machine to establish the nonlinear relationship model between the melting process and the process index, and the model parameters were identified by the sample data after denoising, so as to effectively predict the process index of frosted sand grade in the process of the oxygen-rich top blown smelting. The experimental results on the actual production data of a smelter show that the WD-SSA-SVM model proposed in this paper has high accuracy, meets the accuracy requirements in the actual industrial production, and can effectively guide the optimization and adjustment of the operating parameters of the oxygen-rich top blown smelting process.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134639961","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10167083
Zhen Li, Lei Jin, Guangjuan Ma, Shida Liu
Aiming at the problem of temperature control of transformer, a salp swarm algorithm-based model free adaptive control (SSA-MFAC) algorithm is proposed. In SSA-MFAC, the nonlinear dynamics of the transformer temperature control system is linearized using the dynamic linearization technology and a time-varying parameters named pseudo-partial derivative (PPD). Then, an SSA-MFAC controller is designed, and the salp swarm algorithm (SSA) is introduced to automatically optimize the controller parameters. Based on the salps group behavior in the ocean, the SSA method achieves the goal of controller parameter optimization by simulating the predatory behavior of the salps. The main advantage of SSA-MFAC method is that the controller only makes use of the operation data of the transformer constant temperature oil bath refrigeration unit instead of the specific mathematical model, and the controller parameters are obtained by using the SSA algorithm instead of experience. The algorithm is proved to be effective based on MATLAB/Simulink simulation platform.
{"title":"A Salp Swarm Algorithm-based Model-free Adaptive Control Method and Its Application in Transformer Constant Temperature System","authors":"Zhen Li, Lei Jin, Guangjuan Ma, Shida Liu","doi":"10.1109/DDCLS58216.2023.10167083","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167083","url":null,"abstract":"Aiming at the problem of temperature control of transformer, a salp swarm algorithm-based model free adaptive control (SSA-MFAC) algorithm is proposed. In SSA-MFAC, the nonlinear dynamics of the transformer temperature control system is linearized using the dynamic linearization technology and a time-varying parameters named pseudo-partial derivative (PPD). Then, an SSA-MFAC controller is designed, and the salp swarm algorithm (SSA) is introduced to automatically optimize the controller parameters. Based on the salps group behavior in the ocean, the SSA method achieves the goal of controller parameter optimization by simulating the predatory behavior of the salps. The main advantage of SSA-MFAC method is that the controller only makes use of the operation data of the transformer constant temperature oil bath refrigeration unit instead of the specific mathematical model, and the controller parameters are obtained by using the SSA algorithm instead of experience. The algorithm is proved to be effective based on MATLAB/Simulink simulation platform.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134535908","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10167229
Tao Yang, Youwu Du, Erlin Zhu, Bo Li, Zhenhua Han, Mingxing Fang
This paper presents a control strategy to reject disturbances for a permanent magnet synchronous motor (PMSM) system based on the equivalent-input-disturbance (EID) approach. Two EID estimators are devised to handle disturbances imposed on a current loop: one is used to estimate low-frequency components of disturbances, while the other is employed to estimate medium- and high-frequency components of disturbances. Another EID estimator is developed to estimate disturbances imposed on a speed loop of the motor. The estimates of disturbances are used for compensation on the control input channel of the current loop and the speed loop. It shows that disturbances are estimated separately and suppressed effectively for both loops. Simulation results demonstrate the validity and the superiority of the method.
{"title":"Refined Disturbance Rejection for Permanent Magnet Synchronous Motors with Multi-Source Disturbances Using Equivalent Input Disturbance Approach","authors":"Tao Yang, Youwu Du, Erlin Zhu, Bo Li, Zhenhua Han, Mingxing Fang","doi":"10.1109/DDCLS58216.2023.10167229","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167229","url":null,"abstract":"This paper presents a control strategy to reject disturbances for a permanent magnet synchronous motor (PMSM) system based on the equivalent-input-disturbance (EID) approach. Two EID estimators are devised to handle disturbances imposed on a current loop: one is used to estimate low-frequency components of disturbances, while the other is employed to estimate medium- and high-frequency components of disturbances. Another EID estimator is developed to estimate disturbances imposed on a speed loop of the motor. The estimates of disturbances are used for compensation on the control input channel of the current loop and the speed loop. It shows that disturbances are estimated separately and suppressed effectively for both loops. Simulation results demonstrate the validity and the superiority of the method.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"375 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133364108","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}
Facing the safety problems in industrial process, how to effectively diagnose process faults has become quite necessary and important. In this paper, a novel fault diagnosis approach integrated local reconstructed kernel principal component analysis(LRKPCA) with AdaBoost.M2 is proposed. Firstly, kernel principal component analysis(KPCA) is adopted to extract the global features through non-linear projection transformation. And local feature extraction based on t-distributed stochastic neighbor embedding(TSNE) is realized by minimizing the similarity of probability distribution of samples in high-dimensional space and low-dimensional space. Secondly, LRKPCA-based feature extraction method is proposed, in which the reconstruction error is calculated based on local features and mapped to the global feature space so that data dimension is reduced through coordinate reconstruction. Thirdly, AdaBoost.M2 is adopted to establish multi-classification model to realize fault diagnosis. Finally, the experimental results based on Tennessee Eastman process(TEP) show that the proposed method has higher diagnosis accuracy.
{"title":"A Novel Fault Diagnosis Approach Integrated LRKPCA with AdaBoost.M2 for Industrial Process","authors":"Yuan Xu, Xue Jiang, Qun Zhu, Yanlin He, Yang Zhang, Mingqing Zhang","doi":"10.1109/DDCLS58216.2023.10167144","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10167144","url":null,"abstract":"Facing the safety problems in industrial process, how to effectively diagnose process faults has become quite necessary and important. In this paper, a novel fault diagnosis approach integrated local reconstructed kernel principal component analysis(LRKPCA) with AdaBoost.M2 is proposed. Firstly, kernel principal component analysis(KPCA) is adopted to extract the global features through non-linear projection transformation. And local feature extraction based on t-distributed stochastic neighbor embedding(TSNE) is realized by minimizing the similarity of probability distribution of samples in high-dimensional space and low-dimensional space. Secondly, LRKPCA-based feature extraction method is proposed, in which the reconstruction error is calculated based on local features and mapped to the global feature space so that data dimension is reduced through coordinate reconstruction. Thirdly, AdaBoost.M2 is adopted to establish multi-classification model to realize fault diagnosis. Finally, the experimental results based on Tennessee Eastman process(TEP) show that the proposed method has higher diagnosis accuracy.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122789272","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10166698
Qi Zhang, Shenquan Wang, Wenchengyu Ji
In this paper, a fault detection (FD) method with moving window subspace identification method (MW-SIM) is proposed for the problem of difficult detection of incipient faults. Since the size of the window length has a direct relationship with the fault detection rate, the optimal window length is found by the sparrow search algorithm (SSA) to obtain the maximum fault detection rate. Furthermore, applying event-triggered strategy to subspace identification algorithms can effectively reduce data transmission. Finally, the effectiveness of the designed strategy is verified by the Tennessee Eastman (TE) process simulation.
{"title":"Event-triggered-based subspace identification fault detection with an optimized moving window","authors":"Qi Zhang, Shenquan Wang, Wenchengyu Ji","doi":"10.1109/DDCLS58216.2023.10166698","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10166698","url":null,"abstract":"In this paper, a fault detection (FD) method with moving window subspace identification method (MW-SIM) is proposed for the problem of difficult detection of incipient faults. Since the size of the window length has a direct relationship with the fault detection rate, the optimal window length is found by the sparrow search algorithm (SSA) to obtain the maximum fault detection rate. Furthermore, applying event-triggered strategy to subspace identification algorithms can effectively reduce data transmission. Finally, the effectiveness of the designed strategy is verified by the Tennessee Eastman (TE) process simulation.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117157737","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 : 2023-05-12DOI: 10.1109/DDCLS58216.2023.10165993
Qiu Ruikang, Li Shengquan, Cui Ronghua, Zhang Lujin, Li Juan
A linear active disturbance rejection control (LADRC) strategy is proposed to suppress the structural vibration caused by external excitations and internal uncertainties in intelligent structures under complex working conditions via an Anlu EG4S20B256 chip. First, the electromechanical coupling model of the whole vibration control system is obtained based on the dynamic equations of the all-clamped plate structure and the electromagnetic equations of the inertial actuator. Second, based on the system model, a third-order extended state observer (ESO) is designed to estimate the internal modelling errors and external excitation perturbations of the system in real time. In addition, the influence of internal and external disturbances on the control effect in the experiment is offset by a feedforward compensation. Finally, a vibration control platform based on the Anlu FPGA chip is built to verify the control effect of the proposed vibration active control strategy through physical real-time simulation.
{"title":"Intelligent Structure Control System Based on FPGA","authors":"Qiu Ruikang, Li Shengquan, Cui Ronghua, Zhang Lujin, Li Juan","doi":"10.1109/DDCLS58216.2023.10165993","DOIUrl":"https://doi.org/10.1109/DDCLS58216.2023.10165993","url":null,"abstract":"A linear active disturbance rejection control (LADRC) strategy is proposed to suppress the structural vibration caused by external excitations and internal uncertainties in intelligent structures under complex working conditions via an Anlu EG4S20B256 chip. First, the electromechanical coupling model of the whole vibration control system is obtained based on the dynamic equations of the all-clamped plate structure and the electromagnetic equations of the inertial actuator. Second, based on the system model, a third-order extended state observer (ESO) is designed to estimate the internal modelling errors and external excitation perturbations of the system in real time. In addition, the influence of internal and external disturbances on the control effect in the experiment is offset by a feedforward compensation. Finally, a vibration control platform based on the Anlu FPGA chip is built to verify the control effect of the proposed vibration active control strategy through physical real-time simulation.","PeriodicalId":415532,"journal":{"name":"2023 IEEE 12th Data Driven Control and Learning Systems Conference (DDCLS)","volume":"178 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121041175","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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