Pub Date : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455683
Xueyi Zhang, Kai Zhang, Kai-xiang Peng, Chuang-jian Zhang, Liang Ma
In the modern complex industrial process, such as hot strip mill process (HSMP), the safety and optimality of the production process may deteriorate and operation performance will be degraded due to the wear of equipment, mode conversion and random disturbances. If the process is not adjusted and maintained, there may be more serious faults resulting in greater economic losses and potential safety hazards. Hence, it is essential to develop comprehensive operation performance evaluation. In this paper, a novel lifecycle operation performance evaluation framework based on multi-step total projection to latent structures (T-PLS) is proposed, which is used to deal with normal or faulty performance evaluate problems in the plant-wide HSMP. Firstly, HSMP can be divided into upstream, midstream and downstream by the actual process. Then, the T-PLS monitoring model is established gradually in each stream. Based on the pre-designed transmission rules of fault prior information, comprehensive statistical indexes are constructed to judge whether the process is in normal or faulty operation state. After that, the lifecycle performance evaluations are realized by different evaluation rules. Finally, the feasibility and effectiveness of the proposed method are illustrated through a real HSMP.
{"title":"A Novel Lifecycle Operation Performance Evaluation Framework for Plant-Wide Industrial Processes","authors":"Xueyi Zhang, Kai Zhang, Kai-xiang Peng, Chuang-jian Zhang, Liang Ma","doi":"10.1109/DDCLS52934.2021.9455683","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455683","url":null,"abstract":"In the modern complex industrial process, such as hot strip mill process (HSMP), the safety and optimality of the production process may deteriorate and operation performance will be degraded due to the wear of equipment, mode conversion and random disturbances. If the process is not adjusted and maintained, there may be more serious faults resulting in greater economic losses and potential safety hazards. Hence, it is essential to develop comprehensive operation performance evaluation. In this paper, a novel lifecycle operation performance evaluation framework based on multi-step total projection to latent structures (T-PLS) is proposed, which is used to deal with normal or faulty performance evaluate problems in the plant-wide HSMP. Firstly, HSMP can be divided into upstream, midstream and downstream by the actual process. Then, the T-PLS monitoring model is established gradually in each stream. Based on the pre-designed transmission rules of fault prior information, comprehensive statistical indexes are constructed to judge whether the process is in normal or faulty operation state. After that, the lifecycle performance evaluations are realized by different evaluation rules. Finally, the feasibility and effectiveness of the proposed method are illustrated through a real HSMP.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128330259","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455598
Kaixin Liu, Yu Fan, Kuan Zhang, Jian-guo Yang, Yuan Yao, Yi Liu
In the non-destructive evaluation of infrared thermography, the thermographic data modeling and analysis steps play an important role in improving the inspection results. However, thermal image analysis still faces challenges such as a small number of informative images and difficulty in extracting defect features. In this work, a novel generative manifold learning thermography (GMLT) method for defect detection of composite materials is proposed. In detail, the spectral normalization generative adversarial network is used as a data augmentation strategy to generate more informative thermal images. Sequentially, the MLT-based thermographic data analysis method is adopted to extract and visualize defects in the thermal images. Experiments on carbon fiber reinforced polymers verify the effectiveness and advantages of the proposed method. Key Words: non-destructive evaluation, generative adversarial network, manifold learning, thermographic data analysis, carbon fiber reinforced polymer
{"title":"Generative manifold learning thermography for non-destructive evaluation of defects in composite materials","authors":"Kaixin Liu, Yu Fan, Kuan Zhang, Jian-guo Yang, Yuan Yao, Yi Liu","doi":"10.1109/DDCLS52934.2021.9455598","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455598","url":null,"abstract":"In the non-destructive evaluation of infrared thermography, the thermographic data modeling and analysis steps play an important role in improving the inspection results. However, thermal image analysis still faces challenges such as a small number of informative images and difficulty in extracting defect features. In this work, a novel generative manifold learning thermography (GMLT) method for defect detection of composite materials is proposed. In detail, the spectral normalization generative adversarial network is used as a data augmentation strategy to generate more informative thermal images. Sequentially, the MLT-based thermographic data analysis method is adopted to extract and visualize defects in the thermal images. Experiments on carbon fiber reinforced polymers verify the effectiveness and advantages of the proposed method. Key Words: non-destructive evaluation, generative adversarial network, manifold learning, thermographic data analysis, carbon fiber reinforced polymer","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114973594","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455635
Yongkang Ying, Shan Liu
Object pose estimation is important for robots to understand and interact with the real world. This problem is challenging because the various objects, clutter and occlusions between objects in the scene. Deep learning methods show better performances than traditional problems in this problem but training a convolutional neural network needs lots of annotated data which is expensive to obtain. This paper proposes a general method by using domain transfer technology to efficiently solve object pose estimation problem. Besides, the proposed method obtains mask to achieve high quality performance by combing an instance segmentation framework, Mask R-CNN. We present the results of our experiments with the LineMOD dataset. We also deploy our method to robotic grasp object based on the estimated pose.
{"title":"Mask-based Object Pose Estimation with Domain Transfer","authors":"Yongkang Ying, Shan Liu","doi":"10.1109/DDCLS52934.2021.9455635","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455635","url":null,"abstract":"Object pose estimation is important for robots to understand and interact with the real world. This problem is challenging because the various objects, clutter and occlusions between objects in the scene. Deep learning methods show better performances than traditional problems in this problem but training a convolutional neural network needs lots of annotated data which is expensive to obtain. This paper proposes a general method by using domain transfer technology to efficiently solve object pose estimation problem. Besides, the proposed method obtains mask to achieve high quality performance by combing an instance segmentation framework, Mask R-CNN. We present the results of our experiments with the LineMOD dataset. We also deploy our method to robotic grasp object based on the estimated pose.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133995192","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455451
Yinsong Wang, Ru G. Chen
The control and optimization of Selective Catalytic Reduction (SCR) system has been one of the research hotspots of thermal power units. Accurate measurement of the Nitrogen Oxide (NOx) concentration at the entrance of SCR is of great significance for SCR control and optimization. Firstly, Elastic Net (Enet) method is used to variable selection. This method improves the penalty coefficient by convex combination of $L_{1}$ and $L_{2}$ norm, which has the advantages of ridge regression (RR) and Least Absolute Shrinkage and Selection Operator (LASSO), and overcome the problem of collinearity and group effects in the data when using the LASSO Method. Then, focusing on the advantages of the Gauss process regression (GPR) model, such as the easy acquisition of the super parameters, the flexibility of non parametric inference and the probability significance of output, the Enet-GPR soft-sensor model is established. Field data simulation results show that the proposed method has excellent prediction accuracy and generalization performance.
{"title":"A Soft-Sensor Model for NOx Concentration Based on Enet-GPR","authors":"Yinsong Wang, Ru G. Chen","doi":"10.1109/DDCLS52934.2021.9455451","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455451","url":null,"abstract":"The control and optimization of Selective Catalytic Reduction (SCR) system has been one of the research hotspots of thermal power units. Accurate measurement of the Nitrogen Oxide (NOx) concentration at the entrance of SCR is of great significance for SCR control and optimization. Firstly, Elastic Net (Enet) method is used to variable selection. This method improves the penalty coefficient by convex combination of $L_{1}$ and $L_{2}$ norm, which has the advantages of ridge regression (RR) and Least Absolute Shrinkage and Selection Operator (LASSO), and overcome the problem of collinearity and group effects in the data when using the LASSO Method. Then, focusing on the advantages of the Gauss process regression (GPR) model, such as the easy acquisition of the super parameters, the flexibility of non parametric inference and the probability significance of output, the Enet-GPR soft-sensor model is established. Field data simulation results show that the proposed method has excellent prediction accuracy and generalization performance.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134505699","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455566
Jiaqi Lv, Yu Wang, Shuo Wang, Rui Wang, L. Cheng, M. Tan
In this paper, a disturbance observer based control (DOBC) framework is proposed to achieve the motion control of an underwater biomimetic vehicle-manipulator system (UBVMS) driven by bionic flippers with mismatched disturbances. First, a disturbance observer is established to estimate the mismatched disturbances in finite time. Then, a novel arctangent non-singularity sliding mode manifold incorporating the disturbance observer is proposed to counteract the lumped mismatched disturbances. The stability of the system is validated by the Lyapunov theory. Finally, various comparative simulations are carried out to validate the performance of our proposed DOBC framework in the presence of mismatched disturbances.
{"title":"Disturbance Observer Based Control for an Underwater Biomimetic Vehicle-Manipulator System with Mismatched Disturbances","authors":"Jiaqi Lv, Yu Wang, Shuo Wang, Rui Wang, L. Cheng, M. Tan","doi":"10.1109/DDCLS52934.2021.9455566","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455566","url":null,"abstract":"In this paper, a disturbance observer based control (DOBC) framework is proposed to achieve the motion control of an underwater biomimetic vehicle-manipulator system (UBVMS) driven by bionic flippers with mismatched disturbances. First, a disturbance observer is established to estimate the mismatched disturbances in finite time. Then, a novel arctangent non-singularity sliding mode manifold incorporating the disturbance observer is proposed to counteract the lumped mismatched disturbances. The stability of the system is validated by the Lyapunov theory. Finally, various comparative simulations are carried out to validate the performance of our proposed DOBC framework in the presence of mismatched disturbances.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114080944","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 : 2021-05-14DOI: 10.1109/ddcls52934.2021.9455624
Huiying Wu, S. Jin, Chenkun Yin, Jianmin Zheng, Z. Hou
In this paper, a model free adaptive predictive tracking control method for the robotic manipulators with uncertain parameters is proposed. The compact form dynamic linearization method is used to transform the nonlinear robotic manipulator into a dynamic linearized data model. Then, the model free adaptive predictive tracking control algorithm is designed based on the robot manipulator data model. The proposed control method does not need accurate system model information, merely uses the input and output data of the robot manipulator which is a data-driven control method. Numerical simulations are carried out for PUMA560 robotic manipulator, and the effectiveness of the designed algorithm is verified by the simulation results.
{"title":"Model Free Adaptive Predictive Tracking Control for Robot Manipulators with Uncertain Parameters","authors":"Huiying Wu, S. Jin, Chenkun Yin, Jianmin Zheng, Z. Hou","doi":"10.1109/ddcls52934.2021.9455624","DOIUrl":"https://doi.org/10.1109/ddcls52934.2021.9455624","url":null,"abstract":"In this paper, a model free adaptive predictive tracking control method for the robotic manipulators with uncertain parameters is proposed. The compact form dynamic linearization method is used to transform the nonlinear robotic manipulator into a dynamic linearized data model. Then, the model free adaptive predictive tracking control algorithm is designed based on the robot manipulator data model. The proposed control method does not need accurate system model information, merely uses the input and output data of the robot manipulator which is a data-driven control method. Numerical simulations are carried out for PUMA560 robotic manipulator, and the effectiveness of the designed algorithm is verified by the simulation results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114086923","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455614
Shengzhi Han, Qishui Zhong, Kaibo Shi, Jin Yang
The consensus issue for the nonlinear multiagent systems (MASs) with transmission delays subjected to deception attacks is addressed based on sampled-data control. Due to the universality of cyber attacks, this paper considers a kind of deception attacks which occur randomly at sampling instant and can modify the communication information. By employing the two-sided looped-functional method, an augmented Lyapunov-Krasovskii functional (LKF) is constructed to fully utilize the information on the sampling interval, which makes some free matrices be not necessarily positive definite. Then, the sufficient criteria are presented to ensure the consensus of MASs with deception attacks. Furthermore, the controller gain matrix and the maximal sampling interval are obtained based on the decoupled approach. Finally, the numerical example is exploited to verify the effectiveness of our results.
{"title":"Consensus of Nonlinear Multiagent Systems with Transmission Delays and Deception Attacks via Sampled-Data Control","authors":"Shengzhi Han, Qishui Zhong, Kaibo Shi, Jin Yang","doi":"10.1109/DDCLS52934.2021.9455614","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455614","url":null,"abstract":"The consensus issue for the nonlinear multiagent systems (MASs) with transmission delays subjected to deception attacks is addressed based on sampled-data control. Due to the universality of cyber attacks, this paper considers a kind of deception attacks which occur randomly at sampling instant and can modify the communication information. By employing the two-sided looped-functional method, an augmented Lyapunov-Krasovskii functional (LKF) is constructed to fully utilize the information on the sampling interval, which makes some free matrices be not necessarily positive definite. Then, the sufficient criteria are presented to ensure the consensus of MASs with deception attacks. Furthermore, the controller gain matrix and the maximal sampling interval are obtained based on the decoupled approach. Finally, the numerical example is exploited to verify the effectiveness of our results.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114129726","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455531
Hongqing Liu, L. Xiong, Hui Cao, Mingxian Li, Xinghua Liu, Yue Wang, Lei Yang
To solve the frequency problem caused by high wind power penetration, control strategies such as rapid power compensation (RPC) have been adopted to release the frequency regulation capability of new energy sources quickly. However, when the wind turbine (WT) adopts the RPC strategy to participate in the system frequency regulation, it cannot adapt to the random disturbance. In this paper, a disturbance adaptive RPC (ARPC) strategy is proposed. When the system is disturbed, the signal excitation method is used to estimate the external disturbance. According to the estimated disturbance, the WT rotational inertia is quickly used to compensate for the grid's unbalanced power. When the system frequency deviation and the rate of change of frequency (RoCoF) evaluation indexes meet the threshold requirements, the control strategy switches from ARPC to droop control, which can ensure the WT exit frequency regulation smoothly, and further reduce the frequency deviation and improve the frequency quality. Finally, analyzing the operation mode and determining the relevant switching logic, the proposed ARPC strategy's detailed implementation is developed. Simulation results proved the effectiveness and advancement of the ARPC based strategy.
{"title":"On frequency regulation control strategy of wind turbine based on disturbance adaptiveness","authors":"Hongqing Liu, L. Xiong, Hui Cao, Mingxian Li, Xinghua Liu, Yue Wang, Lei Yang","doi":"10.1109/DDCLS52934.2021.9455531","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455531","url":null,"abstract":"To solve the frequency problem caused by high wind power penetration, control strategies such as rapid power compensation (RPC) have been adopted to release the frequency regulation capability of new energy sources quickly. However, when the wind turbine (WT) adopts the RPC strategy to participate in the system frequency regulation, it cannot adapt to the random disturbance. In this paper, a disturbance adaptive RPC (ARPC) strategy is proposed. When the system is disturbed, the signal excitation method is used to estimate the external disturbance. According to the estimated disturbance, the WT rotational inertia is quickly used to compensate for the grid's unbalanced power. When the system frequency deviation and the rate of change of frequency (RoCoF) evaluation indexes meet the threshold requirements, the control strategy switches from ARPC to droop control, which can ensure the WT exit frequency regulation smoothly, and further reduce the frequency deviation and improve the frequency quality. Finally, analyzing the operation mode and determining the relevant switching logic, the proposed ARPC strategy's detailed implementation is developed. Simulation results proved the effectiveness and advancement of the ARPC based strategy.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133326499","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 : 2021-05-14DOI: 10.1109/ddcls52934.2021.9455505
Su Guo-jun
The production process of semiconductor manufacturing system is very complex. To establish a reliable scheduling model of semiconductor manufacturing system is very important for testing the whole production line system, evaluating different scheduling schemes, and optimizing production resource scheduling. In this paper, a model of semiconductor manufacturing system based on characteristic Petri net is proposed. By simplifying the non main characteristic elements of Petri net model of semiconductor manufacturing system, the model can effectively overcome the danger of model scale expansion brought by basic Petri net in the case of complex system. Finally, the modeling of semiconductor manufacturing system and its calculation example are realized by the above modeling method.
{"title":"On optimal scheduling of semiconductor manufacturing system based on characteristic Petri net model","authors":"Su Guo-jun","doi":"10.1109/ddcls52934.2021.9455505","DOIUrl":"https://doi.org/10.1109/ddcls52934.2021.9455505","url":null,"abstract":"The production process of semiconductor manufacturing system is very complex. To establish a reliable scheduling model of semiconductor manufacturing system is very important for testing the whole production line system, evaluating different scheduling schemes, and optimizing production resource scheduling. In this paper, a model of semiconductor manufacturing system based on characteristic Petri net is proposed. By simplifying the non main characteristic elements of Petri net model of semiconductor manufacturing system, the model can effectively overcome the danger of model scale expansion brought by basic Petri net in the case of complex system. Finally, the modeling of semiconductor manufacturing system and its calculation example are realized by the above modeling method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121723602","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 : 2021-05-14DOI: 10.1109/DDCLS52934.2021.9455512
Manli Zhang, Min Wu, Shengnan Tian, Jinhua She
This paper concerns the design and optimisation of two-dimensional (2D) repetitive control of nonlinear systems based on the Takagi-Sugeno (T-S) fuzzy model. First, a continuous-discrete 2D model of nonlinear repetitive-control systems based on T-S fuzzy model is constructed by utilizing the 2D characteristics of continuous control and discrete learning actions in the repetitive-control process. Next, a fuzzy Lyapunov-Krasovskii functional derives the linear-matrix-inequality-based stability condition with a low conservatism. Two positive and two nonzero parameters in the fuzzy Lyapunov-Krasovskii functional tune the control and learning actions. Then the particle swarm optimisation algorithm based on a 2D performance index searches for the best parameter combination, resulting in the optimal 2D controller gains. A numerical example is given to demonstrate the effectiveness of the method.
{"title":"An Enhanced Fuzzy Repetitive-Control Design and Optimisation Method based on 2D Performance Index","authors":"Manli Zhang, Min Wu, Shengnan Tian, Jinhua She","doi":"10.1109/DDCLS52934.2021.9455512","DOIUrl":"https://doi.org/10.1109/DDCLS52934.2021.9455512","url":null,"abstract":"This paper concerns the design and optimisation of two-dimensional (2D) repetitive control of nonlinear systems based on the Takagi-Sugeno (T-S) fuzzy model. First, a continuous-discrete 2D model of nonlinear repetitive-control systems based on T-S fuzzy model is constructed by utilizing the 2D characteristics of continuous control and discrete learning actions in the repetitive-control process. Next, a fuzzy Lyapunov-Krasovskii functional derives the linear-matrix-inequality-based stability condition with a low conservatism. Two positive and two nonzero parameters in the fuzzy Lyapunov-Krasovskii functional tune the control and learning actions. Then the particle swarm optimisation algorithm based on a 2D performance index searches for the best parameter combination, resulting in the optimal 2D controller gains. A numerical example is given to demonstrate the effectiveness of the method.","PeriodicalId":325897,"journal":{"name":"2021 IEEE 10th Data Driven Control and Learning Systems Conference (DDCLS)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2021-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125731615","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：