Pub Date : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995951
He Ran Wang, Shunjie Han, Huan Yang
Aiming at the problem that the degree of icing of transmission lines in cold regions is difficult to predict, a method for predicting icing galloping of overhead transmission lines based on multi-information fusion is proposed. Through the mechanical structure model of the transmission tower established using Design Modeler, and the stress analysis performed using ANSYS Workbench, calculate the displacement of the characteristic point and the change of the inclination angle when the transmission line tower is covered with ice and gallops, and then classify and predict according to the information above. When the line is running, the real-time meteorological data during icing is collected through the sensor information of the tower body, and a nonlinear four-class SVM is constructed to predict and classify the icing situation. The verification results show that the prediction accuracy of this method is high, which is convenient for promotion.
{"title":"Prediction Method of Icing Galloping of Overhead Transmission Line Based on Multi-Information Fusion","authors":"He Ran Wang, Shunjie Han, Huan Yang","doi":"10.1109/RCAE56054.2022.9995951","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995951","url":null,"abstract":"Aiming at the problem that the degree of icing of transmission lines in cold regions is difficult to predict, a method for predicting icing galloping of overhead transmission lines based on multi-information fusion is proposed. Through the mechanical structure model of the transmission tower established using Design Modeler, and the stress analysis performed using ANSYS Workbench, calculate the displacement of the characteristic point and the change of the inclination angle when the transmission line tower is covered with ice and gallops, and then classify and predict according to the information above. When the line is running, the real-time meteorological data during icing is collected through the sensor information of the tower body, and a nonlinear four-class SVM is constructed to predict and classify the icing situation. The verification results show that the prediction accuracy of this method is high, which is convenient for promotion.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"222 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114688523","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995870
Jian Wang, Jing Xu, Yakun Li
Traditional fault detection methods based on AutoEncoder (AE) usually complete fault detection by comparing reconstruction errors, and ignore a lot of useful information about the distribution of latent variables. In this paper, we propose a novel unsupervised fault detection method named One Dimension Convolutional Adversarial AutoEncoder (1DAAE), which introduce two new ideas: 1D convolution layers for autoencoder to get better features and the adversarial thought to impose the latent variables z to cluster into a prior distribution. Then two anomaly scores are proposed to detect fault samples, one is based on reconstruction errors, the other is based on latent variables distribution. Finally, it is shown by experiments that the proposed method outperforms traditional AE-based, Adversarial AutoEncoder (AAE)-based, One Dimension Convolutional AutoEncoder (1DAE)-based, and 1DAAE-based algorithms on Tennessee Eastman Process.
{"title":"A Novel Fault Detection Method Based on Reconstruction Error and Clustering of Latent Variables","authors":"Jian Wang, Jing Xu, Yakun Li","doi":"10.1109/RCAE56054.2022.9995870","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995870","url":null,"abstract":"Traditional fault detection methods based on AutoEncoder (AE) usually complete fault detection by comparing reconstruction errors, and ignore a lot of useful information about the distribution of latent variables. In this paper, we propose a novel unsupervised fault detection method named One Dimension Convolutional Adversarial AutoEncoder (1DAAE), which introduce two new ideas: 1D convolution layers for autoencoder to get better features and the adversarial thought to impose the latent variables z to cluster into a prior distribution. Then two anomaly scores are proposed to detect fault samples, one is based on reconstruction errors, the other is based on latent variables distribution. Finally, it is shown by experiments that the proposed method outperforms traditional AE-based, Adversarial AutoEncoder (AAE)-based, One Dimension Convolutional AutoEncoder (1DAE)-based, and 1DAAE-based algorithms on Tennessee Eastman Process.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114119264","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995954
Kelin Zhu, Huadong Dai, Hao Gao, Xing Zhou
Many robotic exploration and surveillance applications can be modeled as a single-robot Euclidean traveling salesman problem (TSP). However, the robot in the real-world is usually limited by turning radius or curvature; Moreover, multiple robots can accelerate the completion of the applications. This paper thus studies the Dubins multiple traveling salesman problem (DMTSP) with a min-max objective where the robots are with limited turning radius. Compared to the single robot, multiple robots also need a high corporation to min-max the completion time of the application, and the cooperation makes the problem more difficult. As no mathematical programming work for DMTSP yet has been found in the literature, we propose two approximate (discretization-based) mixed integer linear program-ming (MILP) formulations for the studied problem in this paper. These formulations were compared to the existing Euclidean multiple TSP (MTSP) method and the genetic algorithms for Dubins TSP (DTSP). The results show the effectiveness of our methods on mild-large instances and high accuracy results towards genetic algorithms. The results also are with a fairly small 5% gap to the Euclidean MTSP results which ignores the curvature limits.
{"title":"High Accuracy Discretization-based Integer Programming for the Dubins Multiple Traveling Salesman Problem with Min-max Objective","authors":"Kelin Zhu, Huadong Dai, Hao Gao, Xing Zhou","doi":"10.1109/RCAE56054.2022.9995954","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995954","url":null,"abstract":"Many robotic exploration and surveillance applications can be modeled as a single-robot Euclidean traveling salesman problem (TSP). However, the robot in the real-world is usually limited by turning radius or curvature; Moreover, multiple robots can accelerate the completion of the applications. This paper thus studies the Dubins multiple traveling salesman problem (DMTSP) with a min-max objective where the robots are with limited turning radius. Compared to the single robot, multiple robots also need a high corporation to min-max the completion time of the application, and the cooperation makes the problem more difficult. As no mathematical programming work for DMTSP yet has been found in the literature, we propose two approximate (discretization-based) mixed integer linear program-ming (MILP) formulations for the studied problem in this paper. These formulations were compared to the existing Euclidean multiple TSP (MTSP) method and the genetic algorithms for Dubins TSP (DTSP). The results show the effectiveness of our methods on mild-large instances and high accuracy results towards genetic algorithms. The results also are with a fairly small 5% gap to the Euclidean MTSP results which ignores the curvature limits.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116739712","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995787
Leĭbovich Li, Yao Zheng, Chao Liu, Hongyin Zhu
In order to obtain the information of exhaled gas marker concentration of acute kidney injury patients quickly and accurately, a quantitative VOCs detection system based on metal oxide gas sensors array and BP neural network model is proposed in this paper. Firstly, four kinds of metal oxide gas sensors are used to form a sensor array to convert the measured gas components and concentrations into electrical signal waveforms, and the feature matrix is obtained by feature extraction of the sensor array's signals. Then, a BP neural network model is used to predict the target gas concentrations, and the topology design and parameters of the neural network are optimized.
{"title":"Design of an Electronic Nose System for Exhaled Gas Markers of Acute Kidney Injury Patients","authors":"Leĭbovich Li, Yao Zheng, Chao Liu, Hongyin Zhu","doi":"10.1109/RCAE56054.2022.9995787","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995787","url":null,"abstract":"In order to obtain the information of exhaled gas marker concentration of acute kidney injury patients quickly and accurately, a quantitative VOCs detection system based on metal oxide gas sensors array and BP neural network model is proposed in this paper. Firstly, four kinds of metal oxide gas sensors are used to form a sensor array to convert the measured gas components and concentrations into electrical signal waveforms, and the feature matrix is obtained by feature extraction of the sensor array's signals. Then, a BP neural network model is used to predict the target gas concentrations, and the topology design and parameters of the neural network are optimized.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128290079","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995847
Keping Liu, Cheng Wei, Dawei Ni, Zengpeng Lu, Zhenguo Zhang, Yan Li
Aiming at the nonlinear problem of friction force when the robot is drag teaching, the stribeck model is used to describe the system friction, and a step-by-step identification method of friction coefficient based on parameter identification and genetic algorithm (GA) is proposed. First, the Newton-Euler method is used to establish the dynamic model, and the linear coulomb-viscous friction model is established. Then, the above-mentioned model parameters are identified by the high-speed dynamic parameter identification method, and the coulomb-viscous friction coefficient in the identification result is substituted into the stribeck friction. The model is used as a known quantity. Finally, the stribeck threshold and static friction coefficient are optimized by the GA, and the identification accuracy of the model is judged by the root mean square (RMS) of the theoretical value and the actual value of the friction torque. The experimental results show that, compared with the traditional coulomb-viscous friction model, the RMS value of the stribeck model decreases by 26% approximately at low speed. At the same time, compared with the RMS value of the GA to identify the full parameters of the stribeck model, the RMS value of the method proposed in this paper is reduced by 11%. This method not only improves the accuracy of the robot dynamics model but increases the flexibility of dragging during the drag teaching process, which fully demonstrates the effectiveness and feasibility of the method.
{"title":"Stribeck Friction Model Identification Based on Genetic Algorithm","authors":"Keping Liu, Cheng Wei, Dawei Ni, Zengpeng Lu, Zhenguo Zhang, Yan Li","doi":"10.1109/RCAE56054.2022.9995847","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995847","url":null,"abstract":"Aiming at the nonlinear problem of friction force when the robot is drag teaching, the stribeck model is used to describe the system friction, and a step-by-step identification method of friction coefficient based on parameter identification and genetic algorithm (GA) is proposed. First, the Newton-Euler method is used to establish the dynamic model, and the linear coulomb-viscous friction model is established. Then, the above-mentioned model parameters are identified by the high-speed dynamic parameter identification method, and the coulomb-viscous friction coefficient in the identification result is substituted into the stribeck friction. The model is used as a known quantity. Finally, the stribeck threshold and static friction coefficient are optimized by the GA, and the identification accuracy of the model is judged by the root mean square (RMS) of the theoretical value and the actual value of the friction torque. The experimental results show that, compared with the traditional coulomb-viscous friction model, the RMS value of the stribeck model decreases by 26% approximately at low speed. At the same time, compared with the RMS value of the GA to identify the full parameters of the stribeck model, the RMS value of the method proposed in this paper is reduced by 11%. This method not only improves the accuracy of the robot dynamics model but increases the flexibility of dragging during the drag teaching process, which fully demonstrates the effectiveness and feasibility of the method.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133917095","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}
In this paper, a data-driven method using least squares is proposed for finite training samples, with a focus on parameter identification and the corresponding performance evaluation. In the procedures of parameter identification, “probably approximately correct” (PAC) is used for determining the confidence of the obtained the modeling error that affects Fault Detection (FD) performance. The main contributions of this paper are: 1) The modeling error expressed by infinite norm norm can be reduced by increasing the size of training data; 2) the sub-Gaussian noise is taken into account; 3) the difference between system outputs and their predictions is used as the residual signal, based on which test statistics are defined to obtain FD results. Finally, the effectiveness of the proposed method is demonstrated through rigorous mathematical derivation and case studies.
本文针对有限训练样本，提出了一种基于最小二乘的数据驱动方法，重点研究了参数识别和相应的性能评估。在参数辨识过程中，采用“可能近似正确”(probably approximately correct, PAC)来确定得到的影响故障检测(Fault Detection, FD)性能的建模误差的置信度。本文的主要贡献有:1)通过增加训练数据的大小，可以减小无限范数模表示的建模误差;2)考虑了亚高斯噪声;3)将系统输出与预测值的差值作为残差信号，在残差信号的基础上定义检验统计量，得到FD结果。最后，通过严格的数学推导和实例分析验证了所提方法的有效性。
{"title":"Fault Detection Based on Least Squares with Limited Samples","authors":"Chao Cheng, Chao Ge, Zhaowang Fu, Yiqi Liu, Hongtian Chen","doi":"10.1109/RCAE56054.2022.9995765","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995765","url":null,"abstract":"In this paper, a data-driven method using least squares is proposed for finite training samples, with a focus on parameter identification and the corresponding performance evaluation. In the procedures of parameter identification, “probably approximately correct” (PAC) is used for determining the confidence of the obtained the modeling error that affects Fault Detection (FD) performance. The main contributions of this paper are: 1) The modeling error expressed by infinite norm norm can be reduced by increasing the size of training data; 2) the sub-Gaussian noise is taken into account; 3) the difference between system outputs and their predictions is used as the residual signal, based on which test statistics are defined to obtain FD results. Finally, the effectiveness of the proposed method is demonstrated through rigorous mathematical derivation and case studies.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131856558","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}
The engraving machine system is a typical multi-axis motion system, which has great application value in industrial production. The mechanism of input angular velocity and output position of a typical engraving machine system in speed control mode is analyzed. The engraving machine model is mainly composed of speed circuit, current circuit, motor and mechanical actuator. Some ideal assumptions and simplifications are made during the establishment of the mechanism model, which makes it difficult to estimate the parameters of the mechanism model accurately. The imprecise prediction model limits the application of model-based control algorithms and reduces the model control accuracy. Therefore, a model free adaptive control algorithm based on dynamic linearization of compact format is used to control the output position of the engraving machine. The stability of the proposed model-free adaptive control algorithm is analyzed and proved. The numerical simulation and practical experiment verify superiority and practicability of the proposed control algorithm for nonlinear time-varying system and engraving machine system.
{"title":"Model Free Adaptive Control for Industrial Engraving Machine System","authors":"Yuzhu Zhang, Jiawei Liu, Xingxing Zhou, Baojian Qin, Shi-Du Dong","doi":"10.1109/RCAE56054.2022.9995788","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995788","url":null,"abstract":"The engraving machine system is a typical multi-axis motion system, which has great application value in industrial production. The mechanism of input angular velocity and output position of a typical engraving machine system in speed control mode is analyzed. The engraving machine model is mainly composed of speed circuit, current circuit, motor and mechanical actuator. Some ideal assumptions and simplifications are made during the establishment of the mechanism model, which makes it difficult to estimate the parameters of the mechanism model accurately. The imprecise prediction model limits the application of model-based control algorithms and reduces the model control accuracy. Therefore, a model free adaptive control algorithm based on dynamic linearization of compact format is used to control the output position of the engraving machine. The stability of the proposed model-free adaptive control algorithm is analyzed and proved. The numerical simulation and practical experiment verify superiority and practicability of the proposed control algorithm for nonlinear time-varying system and engraving machine system.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129238091","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995988
Rubisnol Felix Julian Daga, Kevin Ricardo Vilchez Becerra, Jhon Stalin Figueroa Bados, Jesus Miguel Condor Fabian, Katy Fiorela Vilchez Becerra, Pablo José Hurtado Rengifo
The present research work includes the design and control of a plant for obtaining fuel through plastic waste in the city of Huancayo, it has a non-experimental quantitative method, using the German VDDI 2221 methodology and mathematical models of heat and mass transfer and selection of electronic components. The main objective is to design the fixed bed reactor and the ZSM-5 zeolite catalyst, in order to take advantage of solid waste such as polymers, to be able to transform them into fuel through the gasification produced in the reactor at an ideal temperature of 400 °C, continuing the condensation process through the heat exchanger that uses the refrigerant to obtain it in liquid form at a final temperature of 19 °C, considering that the automated control is programmed in a PLC S7 1200 and TIA Portal v15 for the reading of inputs and outputs, visualization and control is developed through the HMI since it is accessible for data control and visualization of the parameters of each process, this leads to the use of new technologies offered by industry 4.0. On the other hand, this modeling based on the calculated mathematical variables has optimal results in simulation and automated control.
{"title":"Design and Control of a Pyrolysis Reactor to Obtain Fuel with Plastic Waste in Huancayo-Peru","authors":"Rubisnol Felix Julian Daga, Kevin Ricardo Vilchez Becerra, Jhon Stalin Figueroa Bados, Jesus Miguel Condor Fabian, Katy Fiorela Vilchez Becerra, Pablo José Hurtado Rengifo","doi":"10.1109/RCAE56054.2022.9995988","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995988","url":null,"abstract":"The present research work includes the design and control of a plant for obtaining fuel through plastic waste in the city of Huancayo, it has a non-experimental quantitative method, using the German VDDI 2221 methodology and mathematical models of heat and mass transfer and selection of electronic components. The main objective is to design the fixed bed reactor and the ZSM-5 zeolite catalyst, in order to take advantage of solid waste such as polymers, to be able to transform them into fuel through the gasification produced in the reactor at an ideal temperature of 400 °C, continuing the condensation process through the heat exchanger that uses the refrigerant to obtain it in liquid form at a final temperature of 19 °C, considering that the automated control is programmed in a PLC S7 1200 and TIA Portal v15 for the reading of inputs and outputs, visualization and control is developed through the HMI since it is accessible for data control and visualization of the parameters of each process, this leads to the use of new technologies offered by industry 4.0. On the other hand, this modeling based on the calculated mathematical variables has optimal results in simulation and automated control.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121059388","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995880
Hucheng Jiang, Tianjiao An, B. Ma, Yuan-chun Li, B. Dong
In this article, a decentralized fuzzy optimal control method dependent on value iteration (VI) is proposed to settle the optimal trajectory tracking control problem of modular reconfigurable robots (MRRs) under the adaptive dynamic programming (ADP) algorithm. A fuzzy logic system (FLS) is designed to estimate cost function and unknown system dynamics of MRRs respectively. Through the use of ADP method, construct a local online VI algorithm and solving HJB equation with approximate cost function, then the decentralized FLS-based optimal control method is realized. On the basis of Lyapunov theorem the MRR system is proved to be asymptotically stable. At last, simulation results show the availability of the suggested method.
{"title":"Value Iteration-based Decentralized Fuzzy Optimal Control of Modular Reconfigurable Robots via Adaptive Dynamic Programming","authors":"Hucheng Jiang, Tianjiao An, B. Ma, Yuan-chun Li, B. Dong","doi":"10.1109/RCAE56054.2022.9995880","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995880","url":null,"abstract":"In this article, a decentralized fuzzy optimal control method dependent on value iteration (VI) is proposed to settle the optimal trajectory tracking control problem of modular reconfigurable robots (MRRs) under the adaptive dynamic programming (ADP) algorithm. A fuzzy logic system (FLS) is designed to estimate cost function and unknown system dynamics of MRRs respectively. Through the use of ADP method, construct a local online VI algorithm and solving HJB equation with approximate cost function, then the decentralized FLS-based optimal control method is realized. On the basis of Lyapunov theorem the MRR system is proved to be asymptotically stable. At last, simulation results show the availability of the suggested method.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131285846","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 : 2022-10-28DOI: 10.1109/RCAE56054.2022.9995749
Xiao Tang, Xiumei Zhang, Lei Sun, Mingming Zang
Aim of this study is to improve the accuracy of the method of estimating the state of charge(SOC) based on the fractional equivalent circuit model(FECM). Based on the fractional model, an adaptive fractional square root cubature Kalman filter(AFSCKF) is designed to estimate SOC. The experiments were compared with fractional cubature Kalman filter(FCKF) under four dynamic cycle conditions. Under the four dynamic cycle conditions, the maximum absolute error(MAE) of AFSCKF is not more than 0.014, the root mean square error(RMSE) is not more than 0.0064, and the MAE of FCKF is not more than 0.02, the RMSE is not more than 0.01. AFSCKF adds a noise estimator based on FCKF, and the transmission of error information is changed from the error covariance matrix to its square root factor. Experimental results show that AFSCKF has better accuracy and robustness, and provides an accurate and reliable method for estimating SOC based on a fractional model.
{"title":"Lithium Battery SOC Estimation Method Based on AFSCKF Algorithm","authors":"Xiao Tang, Xiumei Zhang, Lei Sun, Mingming Zang","doi":"10.1109/RCAE56054.2022.9995749","DOIUrl":"https://doi.org/10.1109/RCAE56054.2022.9995749","url":null,"abstract":"Aim of this study is to improve the accuracy of the method of estimating the state of charge(SOC) based on the fractional equivalent circuit model(FECM). Based on the fractional model, an adaptive fractional square root cubature Kalman filter(AFSCKF) is designed to estimate SOC. The experiments were compared with fractional cubature Kalman filter(FCKF) under four dynamic cycle conditions. Under the four dynamic cycle conditions, the maximum absolute error(MAE) of AFSCKF is not more than 0.014, the root mean square error(RMSE) is not more than 0.0064, and the MAE of FCKF is not more than 0.02, the RMSE is not more than 0.01. AFSCKF adds a noise estimator based on FCKF, and the transmission of error information is changed from the error covariance matrix to its square root factor. Experimental results show that AFSCKF has better accuracy and robustness, and provides an accurate and reliable method for estimating SOC based on a fractional model.","PeriodicalId":165439,"journal":{"name":"2022 5th International Conference on Robotics, Control and Automation Engineering (RCAE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2022-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130158810","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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