S. Khoroshylov, S. Martyniuk, O. Sushko, V. Vasyliev, E. Medzmariashvili, W. Woods
Abstract This work tackles the problem of attitude control of a space-based synthetic aperture radar with a deployable reflector antenna, representing a lightly damped uncertain vibratory system with highly nonlinear dynamics. A control strategy based on two identifiable in-orbit vector parameters is proposed to make the robust controller less conservative. The first parameter is used in the feedforward loop to achieve a trade-off between the energy efficiency of maneuvers and the amplitudes of the oscillatory response. The feedback loop utilizes the second parameter to accurately handle the controller-structure interactions by adaptive notch filters. The notch filters are included in the augmented plant at the design stage to guarantee closed-loop robustness against disturbances, unmodeled dynamics, and parametric uncertainty. The system’s robustness and specified requirements are confirmed by formal criteria and numerical simulations using a realistic model of the flexible spacecraft.
{"title":"Dynamics and attitude control of space-based synthetic aperture radar","authors":"S. Khoroshylov, S. Martyniuk, O. Sushko, V. Vasyliev, E. Medzmariashvili, W. Woods","doi":"10.1515/nleng-2022-0277","DOIUrl":"https://doi.org/10.1515/nleng-2022-0277","url":null,"abstract":"Abstract This work tackles the problem of attitude control of a space-based synthetic aperture radar with a deployable reflector antenna, representing a lightly damped uncertain vibratory system with highly nonlinear dynamics. A control strategy based on two identifiable in-orbit vector parameters is proposed to make the robust controller less conservative. The first parameter is used in the feedforward loop to achieve a trade-off between the energy efficiency of maneuvers and the amplitudes of the oscillatory response. The feedback loop utilizes the second parameter to accurately handle the controller-structure interactions by adaptive notch filters. The notch filters are included in the augmented plant at the design stage to guarantee closed-loop robustness against disturbances, unmodeled dynamics, and parametric uncertainty. The system’s robustness and specified requirements are confirmed by formal criteria and numerical simulations using a realistic model of the flexible spacecraft.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88670656","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}
Abstract To explore the extraction of computer image scene and target information, a nonlinear method based on big data technology is proposed. The method can decompose the computer image into a plurality of components when the SAR computer image is processed such as target extraction and computer image compression, which represent different captured image features, respectively. Selecting the most suitable processing method according to the characteristics of different components can greatly improve the performance. Using nonlinear diffusion method, the computer image is decomposed into structural components representing large-scale structural information and texture components representing small-scale detailed information, and the automatic threshold estimation in the diffusion process is studied. The LAIDA criterion is introduced into the automatic threshold solution of nonlinear diffusion-based computer image decomposition to test and evaluate the diffusion process of various diffusion parameter forms. The results show that the experimental outcome of the diffusion decomposition based on automatic threshold estimation is very close on each index, which shows that using automatic threshold estimation, no matter what diffusion index is used, very close results can be obtained. Specifically, for each algorithm, the parameter estimation threshold l for outliers plays an obvious role. The third is the degree of initiative of the estimation process. The larger the L, the larger the outlier, which will lead to a greater extent of the diffusion process, resulting in a continuous decrease in the structural similarity index and compositional correlation. It is proved that the algorithm has strong global search ability, can effectively avoid premature convergence, has fast convergence speed, and good long stability. It can be widely used for optimization of various multimodal functions.
{"title":"Nonlinear computer image scene and target information extraction based on big data technology","authors":"Jiaqi Wang","doi":"10.1515/nleng-2022-0245","DOIUrl":"https://doi.org/10.1515/nleng-2022-0245","url":null,"abstract":"Abstract To explore the extraction of computer image scene and target information, a nonlinear method based on big data technology is proposed. The method can decompose the computer image into a plurality of components when the SAR computer image is processed such as target extraction and computer image compression, which represent different captured image features, respectively. Selecting the most suitable processing method according to the characteristics of different components can greatly improve the performance. Using nonlinear diffusion method, the computer image is decomposed into structural components representing large-scale structural information and texture components representing small-scale detailed information, and the automatic threshold estimation in the diffusion process is studied. The LAIDA criterion is introduced into the automatic threshold solution of nonlinear diffusion-based computer image decomposition to test and evaluate the diffusion process of various diffusion parameter forms. The results show that the experimental outcome of the diffusion decomposition based on automatic threshold estimation is very close on each index, which shows that using automatic threshold estimation, no matter what diffusion index is used, very close results can be obtained. Specifically, for each algorithm, the parameter estimation threshold l for outliers plays an obvious role. The third is the degree of initiative of the estimation process. The larger the L, the larger the outlier, which will lead to a greater extent of the diffusion process, resulting in a continuous decrease in the structural similarity index and compositional correlation. It is proved that the algorithm has strong global search ability, can effectively avoid premature convergence, has fast convergence speed, and good long stability. It can be widely used for optimization of various multimodal functions.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90797455","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}
Abstract The typical power transformer diagnosis approach is imprecise and unstable. A support vector machine classification algorithm is proposed, by designing an algorithm program that can improve the accuracy and speed of energy transformer diagnosis, the vibration signals of the surface twisting in different states are extracted by wavelet packet energy spectrum signal processing method, it is verified that the curve similarity between the vibration simulation model and the measured data is greater than 0.98, proving the simulation model’s validity. The calculation technique of online short circuit inductance is developed from the equivalent transformer model, and the variation error of simulation results is less than 0.05% when compared to the real transformer characteristics. The suggested state diagnostic technique successfully compensates for the drawbacks of the reactance method, which is incapable of detecting and judging the slightly loose or faulty winding. The method’s accuracy and superiority, as well as the practicability of the state diagnosis system, are demonstrated.
{"title":"Experimental design and data analysis and optimization of mechanical condition diagnosis for transformer sets","authors":"Bingshuang Chang, Jian Xin, Miaomiao Fu, Vishal Jagota, Mukesh Soni, Samrat Ray","doi":"10.1515/nleng-2022-0215","DOIUrl":"https://doi.org/10.1515/nleng-2022-0215","url":null,"abstract":"Abstract The typical power transformer diagnosis approach is imprecise and unstable. A support vector machine classification algorithm is proposed, by designing an algorithm program that can improve the accuracy and speed of energy transformer diagnosis, the vibration signals of the surface twisting in different states are extracted by wavelet packet energy spectrum signal processing method, it is verified that the curve similarity between the vibration simulation model and the measured data is greater than 0.98, proving the simulation model’s validity. The calculation technique of online short circuit inductance is developed from the equivalent transformer model, and the variation error of simulation results is less than 0.05% when compared to the real transformer characteristics. The suggested state diagnostic technique successfully compensates for the drawbacks of the reactance method, which is incapable of detecting and judging the slightly loose or faulty winding. The method’s accuracy and superiority, as well as the practicability of the state diagnosis system, are demonstrated.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77692929","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}
Abstract Since the beginning of the digital music era, the number of available digital music resources has skyrocketed. The genre of music is a significant classification to use when elaborating music; the role of music tags in locating and categorizing electronic music services is essential. To categorize such a large music archive manually would be prohibitively expensive and time-consuming, rendering it obsolete. This study’s main contributions to knowledge are the following: This article will break down the music into many MIDI (music played on a digital musical instrument) movements, playing way close by analysis movement, character extraction from passages, and character sequencing from movement so that you may get a clearer picture of what you are hearing. The procedure includes the following steps: extracting the note character matrix, extracting the subject and segmentation grouping based on the note character matrix, researching and extracting beneficial characteristics based on the theme of the segments, and composing the feature sequence. It is challenging for the sorter to acquire spatial and contextual knowledge about music using traditional classification techniques due to its shallow structure. This study uses the unique pattern of input MIDI segments, which are used to probe the relationship between recurrent neural networks and attention. The approach for music classification is verified when paired with the testing precision of the same-length segment categorization; thus, gathering MIDI tracks 1920 along with genre tags from the network to construct statistics sets and perform music classification analysis.
{"title":"A deep learning-based mathematical modeling strategy for classifying musical genres in musical industry","authors":"Xiaoquan He, Fang Dong","doi":"10.1515/nleng-2022-0302","DOIUrl":"https://doi.org/10.1515/nleng-2022-0302","url":null,"abstract":"Abstract Since the beginning of the digital music era, the number of available digital music resources has skyrocketed. The genre of music is a significant classification to use when elaborating music; the role of music tags in locating and categorizing electronic music services is essential. To categorize such a large music archive manually would be prohibitively expensive and time-consuming, rendering it obsolete. This study’s main contributions to knowledge are the following: This article will break down the music into many MIDI (music played on a digital musical instrument) movements, playing way close by analysis movement, character extraction from passages, and character sequencing from movement so that you may get a clearer picture of what you are hearing. The procedure includes the following steps: extracting the note character matrix, extracting the subject and segmentation grouping based on the note character matrix, researching and extracting beneficial characteristics based on the theme of the segments, and composing the feature sequence. It is challenging for the sorter to acquire spatial and contextual knowledge about music using traditional classification techniques due to its shallow structure. This study uses the unique pattern of input MIDI segments, which are used to probe the relationship between recurrent neural networks and attention. The approach for music classification is verified when paired with the testing precision of the same-length segment categorization; thus, gathering MIDI tracks 1920 along with genre tags from the network to construct statistics sets and perform music classification analysis.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81461323","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}
Lili Zhang, Chuan-Jie Zhang, Peng Wang, Mohammad Shabaz, Skanda M. G., Vijayalakshmi C., K. Kishore
Abstract A three-dimensional simulation model of the electromechanical control system was built using the fuzzy control proportional–integral–derivative (PID) adjustment algorithm after an automatic electromechanical control system based on programmable logic controller (PLC) technology was optimized to achieve the practical use of electromechanical program control. First, the hardware of the electromechanical control system is discussed and designed. The findings demonstrate the viability of the mechanical and electrical integration PLC program optimization solution based on three-dimensional (3D) model. The system has a higher control and management efficiency, which is 30% greater than that of the conventional system. The mechatronic manufacturing system’s continuous operation efficiency enhancement can significantly lower the investment costs and boost the financial gains of industrial organizations. Traditional systems have a control and management efficiency of around 30%, but automatic electromechanical control systems based on PLC technology and created using 3D models have a control and management efficiency between 60 and 70%.
{"title":"Realization of optimization design of electromechanical integration PLC program system based on 3D model","authors":"Lili Zhang, Chuan-Jie Zhang, Peng Wang, Mohammad Shabaz, Skanda M. G., Vijayalakshmi C., K. Kishore","doi":"10.1515/nleng-2022-0252","DOIUrl":"https://doi.org/10.1515/nleng-2022-0252","url":null,"abstract":"Abstract A three-dimensional simulation model of the electromechanical control system was built using the fuzzy control proportional–integral–derivative (PID) adjustment algorithm after an automatic electromechanical control system based on programmable logic controller (PLC) technology was optimized to achieve the practical use of electromechanical program control. First, the hardware of the electromechanical control system is discussed and designed. The findings demonstrate the viability of the mechanical and electrical integration PLC program optimization solution based on three-dimensional (3D) model. The system has a higher control and management efficiency, which is 30% greater than that of the conventional system. The mechatronic manufacturing system’s continuous operation efficiency enhancement can significantly lower the investment costs and boost the financial gains of industrial organizations. Traditional systems have a control and management efficiency of around 30%, but automatic electromechanical control systems based on PLC technology and created using 3D models have a control and management efficiency between 60 and 70%.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81484803","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}
Abstract To improve data mining and data clustering performance to improve the efficiency of the cloud computing platform, the author proposes a bionic optimized clustering data extraction algorithm based on cloud computing platform. According to the Gaussian distribution function graph, the degree of aggregation of the categories and the distribution of data points of the same category can be judged more intuitively. The cloud computing platform has the characteristics of large amount of data and high dimension. In the process of solving the distance between all sample points and the center point, after each center point update, the optimization function needs to be re-executed, the author mainly uses clustering evaluation methods such as PBM-index and DB-index. The simulation data object is the Iris dataset in UCI, and N = 500 samples are selected for simulation. The experiment result shows that when P is not greater than 15, the PBM value changes very little, and when P = 20, the PBM performance of all the four clustering algorithms decreased significantly. When the sample size is increased from 50,000 to 100,000, the DB performance of this algorithm does not change much, and the DB value tends to be stable. In terms of clustering operation time, the K-means algorithm has obvious advantages, the DBSCAN algorithm is the most time-consuming, and the operation time of wolf pack clustering and Mean-shift is in the middle. In the actual application process, the number of samples for each training can be dynamically adjusted according to the actual needs, in order to improve the applicability of the wolf pack clustering algorithm in specific application scenarios. Flattening in cloud computing for data clusters, this algorithm is compared with the common clustering algorithm in PBM. DB also shows better performance.
{"title":"Application of nonlinear clustering optimization algorithm in web data mining of cloud computing","authors":"Yan Zhang","doi":"10.1515/nleng-2022-0239","DOIUrl":"https://doi.org/10.1515/nleng-2022-0239","url":null,"abstract":"Abstract To improve data mining and data clustering performance to improve the efficiency of the cloud computing platform, the author proposes a bionic optimized clustering data extraction algorithm based on cloud computing platform. According to the Gaussian distribution function graph, the degree of aggregation of the categories and the distribution of data points of the same category can be judged more intuitively. The cloud computing platform has the characteristics of large amount of data and high dimension. In the process of solving the distance between all sample points and the center point, after each center point update, the optimization function needs to be re-executed, the author mainly uses clustering evaluation methods such as PBM-index and DB-index. The simulation data object is the Iris dataset in UCI, and N = 500 samples are selected for simulation. The experiment result shows that when P is not greater than 15, the PBM value changes very little, and when P = 20, the PBM performance of all the four clustering algorithms decreased significantly. When the sample size is increased from 50,000 to 100,000, the DB performance of this algorithm does not change much, and the DB value tends to be stable. In terms of clustering operation time, the K-means algorithm has obvious advantages, the DBSCAN algorithm is the most time-consuming, and the operation time of wolf pack clustering and Mean-shift is in the middle. In the actual application process, the number of samples for each training can be dynamically adjusted according to the actual needs, in order to improve the applicability of the wolf pack clustering algorithm in specific application scenarios. Flattening in cloud computing for data clusters, this algorithm is compared with the common clustering algorithm in PBM. DB also shows better performance.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75011480","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}
Ravi Shanker, Prateek Aggrawal, Aman Singh, Mohammed Wasim Bhatt
Abstract In every network, traffic anomaly detection system is an essential field of study. In the communication system, there are various protocols and intrusions. It is still a testing area to find high precision to boost the correct distribution ratio. Many authors have worked on various algorithms such as simple classification, K-Means, Genetic Algorithm, and Support Vector Machine approaches, and they presented the efficiency and accuracy of these algorithms. In this article, we have proposed a feature extraction technique known as “k-means clustering,” which has its roots in signal processing and is employed to divide a set of n observations into k clusters, each of which has its origin from the observation with the closest mean. K-Means method is applied in this study to investigate the stream and its implementation and applications using Python and the dataset on the KDDcup99. The effectiveness of the outcome indicates the planned work’s efficiency in relation to other widely available alternatives. Apart from the applied method, a web-based framework is designed, which can inspect an actual network traffic packet for identifying network attacks. Instead of using a static file for testing the network attack, a web page-based solution uses database to collect and test the information. Real-time packet inspection is provided in the proposed work for identifying new attacks.
{"title":"Framework for identifying network attacks through packet inspection using machine learning","authors":"Ravi Shanker, Prateek Aggrawal, Aman Singh, Mohammed Wasim Bhatt","doi":"10.1515/nleng-2022-0297","DOIUrl":"https://doi.org/10.1515/nleng-2022-0297","url":null,"abstract":"Abstract In every network, traffic anomaly detection system is an essential field of study. In the communication system, there are various protocols and intrusions. It is still a testing area to find high precision to boost the correct distribution ratio. Many authors have worked on various algorithms such as simple classification, K-Means, Genetic Algorithm, and Support Vector Machine approaches, and they presented the efficiency and accuracy of these algorithms. In this article, we have proposed a feature extraction technique known as “k-means clustering,” which has its roots in signal processing and is employed to divide a set of n observations into k clusters, each of which has its origin from the observation with the closest mean. K-Means method is applied in this study to investigate the stream and its implementation and applications using Python and the dataset on the KDDcup99. The effectiveness of the outcome indicates the planned work’s efficiency in relation to other widely available alternatives. Apart from the applied method, a web-based framework is designed, which can inspect an actual network traffic packet for identifying network attacks. Instead of using a static file for testing the network attack, a web page-based solution uses database to collect and test the information. Real-time packet inspection is provided in the proposed work for identifying new attacks.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89468235","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}
Abstract Damages on railway sleepers due to heavy impact loads induced by the movement of trains can be reduced by improving their impact resistance. Fibre-reinforced/pre-treated crumb rubber concrete sleepers (RCSs) have the potential to display significant impact resistance to withstand a high-magnitude impact load. The ideal proportions of pre-treated crumb rubber, steel fibres, and polypropylene fibres (PFs) can be identified based on the minimum cost-to-impact energy ratio after conducting a drop weight impact test on prisms. The numerical model developed to assess the behaviour of ballasted tracks has been validated using both simulation results and field measurements. Numerical studies have been conducted on ballasted rail tracks with steel and PF-reinforced/pre-treated RCSs using LS-DYNA software. Dynamic strain rate-dependent material parameters are introduced in the numerical simulations. The nonlinear effect of higher train speeds on dynamic track responses has been highlighted in this article. Although the static load-carrying capacity and modulus of elasticity of rubber concrete are low, their dynamic performance controls the track displacements from exceeding permissible limits. The outcome of this study will provide new insights into the effects of railway concrete sleepers incorporated with reinforced fibres and pre-treated crumb rubber on railway track performance in order to ensure safety and reliability before it is put into services.
{"title":"Nonlinear dynamic responses of ballasted railway tracks using concrete sleepers incorporated with reinforced fibres and pre-treated crumb rubber","authors":"Anand Raj, Chayut Ngamkhanong, Lapyote Prasittisopin, Sakdirat Kaewunruen","doi":"10.1515/nleng-2022-0320","DOIUrl":"https://doi.org/10.1515/nleng-2022-0320","url":null,"abstract":"Abstract Damages on railway sleepers due to heavy impact loads induced by the movement of trains can be reduced by improving their impact resistance. Fibre-reinforced/pre-treated crumb rubber concrete sleepers (RCSs) have the potential to display significant impact resistance to withstand a high-magnitude impact load. The ideal proportions of pre-treated crumb rubber, steel fibres, and polypropylene fibres (PFs) can be identified based on the minimum cost-to-impact energy ratio after conducting a drop weight impact test on prisms. The numerical model developed to assess the behaviour of ballasted tracks has been validated using both simulation results and field measurements. Numerical studies have been conducted on ballasted rail tracks with steel and PF-reinforced/pre-treated RCSs using LS-DYNA software. Dynamic strain rate-dependent material parameters are introduced in the numerical simulations. The nonlinear effect of higher train speeds on dynamic track responses has been highlighted in this article. Although the static load-carrying capacity and modulus of elasticity of rubber concrete are low, their dynamic performance controls the track displacements from exceeding permissible limits. The outcome of this study will provide new insights into the effects of railway concrete sleepers incorporated with reinforced fibres and pre-treated crumb rubber on railway track performance in order to ensure safety and reliability before it is put into services.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135360360","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}
Abstract This article discusses the bifurcation analysis and control of a valve-controlled hydraulic cylinder system. The dynamic system of the valve-controlled hydraulic cylinder is established. Normal form theory and Hopf bifurcation theory are used to analyse the bifurcation characteristic at equilibria of the system. Then, a dynamic-state feedback control method is proposed. A nonlinear controller is set for the system to control the bifurcation with the method. By adjusting the control parameters, the delay of model bifurcation and the stability of the system can be changed. Numerical analysis verifies the correctness of bifurcation control.
{"title":"Bifurcation analysis and control of the valve-controlled hydraulic cylinder system","authors":"Qin Han, Liang Zhang","doi":"10.1515/nleng-2022-0311","DOIUrl":"https://doi.org/10.1515/nleng-2022-0311","url":null,"abstract":"Abstract This article discusses the bifurcation analysis and control of a valve-controlled hydraulic cylinder system. The dynamic system of the valve-controlled hydraulic cylinder is established. Normal form theory and Hopf bifurcation theory are used to analyse the bifurcation characteristic at equilibria of the system. Then, a dynamic-state feedback control method is proposed. A nonlinear controller is set for the system to control the bifurcation with the method. By adjusting the control parameters, the delay of model bifurcation and the stability of the system can be changed. Numerical analysis verifies the correctness of bifurcation control.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135649649","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}
A. Buscarino, Carlo Famoso, Luigi Fortuna, Giuseppe La Spina
Abstract On September 22, 2022, a spacecraft, designed by the Double Asteroid Redirection Test (DART) team, successfully attempted to deflect the orbit of the asteroid Dimorphos, which together with Didymos, constitutes a binary system of near-Earth asteroids orbiting around the Sun. The effect of the impact of the spacecraft was to shorten the orbit of Dimorphos of about 33 min with respect to the original one. In this communication, a simple nonlinear circuit emulator based on a mathematical model allowing the emulation of the DART mission behavior is presented. The modeling is approached referring to the Kepler problem that leads to a highly nonlinear dynamical model. The problem is approached numerically, by using appropriate integration algorithms for both the two-body and three-body formulations of the problem, and experimentally, by means of an analog/digital electronic circuit emulator of the system that allows us to realize faster and qualitative more efficient experiments.
{"title":"NASA DART mission: A preliminary mathematical dynamical model and its nonlinear circuit emulation","authors":"A. Buscarino, Carlo Famoso, Luigi Fortuna, Giuseppe La Spina","doi":"10.1515/nleng-2022-0314","DOIUrl":"https://doi.org/10.1515/nleng-2022-0314","url":null,"abstract":"Abstract On September 22, 2022, a spacecraft, designed by the Double Asteroid Redirection Test (DART) team, successfully attempted to deflect the orbit of the asteroid Dimorphos, which together with Didymos, constitutes a binary system of near-Earth asteroids orbiting around the Sun. The effect of the impact of the spacecraft was to shorten the orbit of Dimorphos of about 33 min with respect to the original one. In this communication, a simple nonlinear circuit emulator based on a mathematical model allowing the emulation of the DART mission behavior is presented. The modeling is approached referring to the Kepler problem that leads to a highly nonlinear dynamical model. The problem is approached numerically, by using appropriate integration algorithms for both the two-body and three-body formulations of the problem, and experimentally, by means of an analog/digital electronic circuit emulator of the system that allows us to realize faster and qualitative more efficient experiments.","PeriodicalId":37863,"journal":{"name":"Nonlinear Engineering - Modeling and Application","volume":null,"pages":null},"PeriodicalIF":8.3,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75515876","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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