This paper analyzes the problem of simultaneous fault detection and control of the six-rotor unmanned aerial vehicle control system, considering external disturbance, measurement disturbance, and actuator fault. The integral event trigger mechanism is introduced in the control side and sensor side of the system. Based on Lyapunov stability and H∞ control theory, the sufficient conditions to make the fault system asymptotically stable and have certain performance indexes are given by means of linear matrix inequalities; at the same time, the design criteria of event trigger parameters are also given. The linear matrix inequality is decoupled, and the calculation method of gain matrix of simultaneous fault detection and control module is given. The effectiveness of the proposed method is verified by simulation experiments.
{"title":"Simultaneous attitude fault detection and control of the six-rotor UAV based on event trigger mechanism","authors":"Qingnan Huang, Enze Zhang, Xisheng Dai, Jingru Qi, Qiqi Wu","doi":"10.1177/01423312231196640","DOIUrl":"https://doi.org/10.1177/01423312231196640","url":null,"abstract":"This paper analyzes the problem of simultaneous fault detection and control of the six-rotor unmanned aerial vehicle control system, considering external disturbance, measurement disturbance, and actuator fault. The integral event trigger mechanism is introduced in the control side and sensor side of the system. Based on Lyapunov stability and H∞ control theory, the sufficient conditions to make the fault system asymptotically stable and have certain performance indexes are given by means of linear matrix inequalities; at the same time, the design criteria of event trigger parameters are also given. The linear matrix inequality is decoupled, and the calculation method of gain matrix of simultaneous fault detection and control module is given. The effectiveness of the proposed method is verified by simulation experiments.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"10 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380656","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-06DOI: 10.1177/01423312231200514
Lili Zhou, Huiying Zhang, Fei Tan, Kaiyue Liu
This paper mainly studies the synchronization problem of memristor-based bidirectional associative memory neural networks (MBAMNNs) via finite-time technology. Different from the existing neural network dynamic models, the given model in this paper is focused on the impact of parameter perturbation and strong mismatch, where strong mismatch includes parameter mismatch and time-varying delay mismatch. These characteristics can make the model be closer to the actual situation. A delay-independent feedback control scheme, which can stabilize the error system within finite-time regardless of whether the past state is known or not, is designed. It is worth noting that the constant is replaced by a function with the exponential term in the delay-independent controller, which can save the control cost to a certain extent. Based on the integral inequality technique, some sufficient conditions for MBAMNNs to converge to the equilibrium point within finite-time are provided. The validity and correctness of the theoretical results are finally confirmed by numerical simulation.
{"title":"Delay-independent control for synchronization of memristor-based BAM neural networks with parameter perturbation and strong mismatch via finite-time technology","authors":"Lili Zhou, Huiying Zhang, Fei Tan, Kaiyue Liu","doi":"10.1177/01423312231200514","DOIUrl":"https://doi.org/10.1177/01423312231200514","url":null,"abstract":"This paper mainly studies the synchronization problem of memristor-based bidirectional associative memory neural networks (MBAMNNs) via finite-time technology. Different from the existing neural network dynamic models, the given model in this paper is focused on the impact of parameter perturbation and strong mismatch, where strong mismatch includes parameter mismatch and time-varying delay mismatch. These characteristics can make the model be closer to the actual situation. A delay-independent feedback control scheme, which can stabilize the error system within finite-time regardless of whether the past state is known or not, is designed. It is worth noting that the constant is replaced by a function with the exponential term in the delay-independent controller, which can save the control cost to a certain extent. Based on the integral inequality technique, some sufficient conditions for MBAMNNs to converge to the equilibrium point within finite-time are provided. The validity and correctness of the theoretical results are finally confirmed by numerical simulation.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"8 5","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380630","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-06DOI: 10.1177/01423312231198922
Wenlong Yao, Chunbo Pei, R. Chi, Wei Shao, Boyang Li
The paper studies a presynchronization control of grid connection for large merchant marine microgrid inverters. We present a virtual synchronous generator (VSG) algorithm with model-free adaptive control (MFAC) to optimize the stable grid connection of ship microgrid and shore-to-ship power. To solve poor precision of presynchronization control under nonideal ship microgrid condition, an MFAC controller and its presynchronization method are developed for grid connection of ship-distributed generation inverters. The proposed presynchronization control method effectively avoids a high transient overcurrent and achieves a seamless grid connection to different types of shore power. The simulation results verify the effectiveness of the proposed control method.
{"title":"Presynchronization control for ship microgrid of merchant marine inverters based on VSG algorithm with MFAC","authors":"Wenlong Yao, Chunbo Pei, R. Chi, Wei Shao, Boyang Li","doi":"10.1177/01423312231198922","DOIUrl":"https://doi.org/10.1177/01423312231198922","url":null,"abstract":"The paper studies a presynchronization control of grid connection for large merchant marine microgrid inverters. We present a virtual synchronous generator (VSG) algorithm with model-free adaptive control (MFAC) to optimize the stable grid connection of ship microgrid and shore-to-ship power. To solve poor precision of presynchronization control under nonideal ship microgrid condition, an MFAC controller and its presynchronization method are developed for grid connection of ship-distributed generation inverters. The proposed presynchronization control method effectively avoids a high transient overcurrent and achieves a seamless grid connection to different types of shore power. The simulation results verify the effectiveness of the proposed control method.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"9 12","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380444","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2024-01-06DOI: 10.1177/01423312231200054
Dong Guo, Peng Jiang, Jun Liu, Jianping Cai, Igor Bychkov, A. Hmelnov
Unknown actuator failures are inevitable in practical systems. At the same time, time delay exists in many physical actuators, and the system performance will be affected by such actuator delay and faults. However, the results of studies that attempt to compensate for unknown failures of actuators with time delay are still very limited. In this paper, such a problem is studied, and an adaptive control scheme is proposed based on backstepping approaches. First, the input delay of actuator faults and output disturbances are transformed into unknown effects on the output signal. In the backstepping recursive design, these unknown effects will accumulate to the last step of the controller design. Then, a new Lyapunov function is constructed by introducing auxiliary signals to prove the stability of the system. It is shown that the proposed control scheme can compensate for the effects caused by unknown actuator failures and input delays. The stability of the closed-loop system can be guaranteed by this adaptive controller. Finally, simulation studies are used to verify the effectiveness of the proposed scheme.
{"title":"Adaptive backstepping control for a class of uncertain systems with actuator delay and faults","authors":"Dong Guo, Peng Jiang, Jun Liu, Jianping Cai, Igor Bychkov, A. Hmelnov","doi":"10.1177/01423312231200054","DOIUrl":"https://doi.org/10.1177/01423312231200054","url":null,"abstract":"Unknown actuator failures are inevitable in practical systems. At the same time, time delay exists in many physical actuators, and the system performance will be affected by such actuator delay and faults. However, the results of studies that attempt to compensate for unknown failures of actuators with time delay are still very limited. In this paper, such a problem is studied, and an adaptive control scheme is proposed based on backstepping approaches. First, the input delay of actuator faults and output disturbances are transformed into unknown effects on the output signal. In the backstepping recursive design, these unknown effects will accumulate to the last step of the controller design. Then, a new Lyapunov function is constructed by introducing auxiliary signals to prove the stability of the system. It is shown that the proposed control scheme can compensate for the effects caused by unknown actuator failures and input delays. The stability of the closed-loop system can be guaranteed by this adaptive controller. Finally, simulation studies are used to verify the effectiveness of the proposed scheme.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"5 9","pages":""},"PeriodicalIF":1.8,"publicationDate":"2024-01-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139380533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-21DOI: 10.1177/01423312231214832
Ali Mounir Halitim, M. Bouhedda, Sofiane Tchoketch-Kebir, S. Rebouh
Low-cost inertial measurement units (IMUs) are commonly used to determine the orientation of objects, such as unmanned aerial vehicles (UAVs) and smartphones. They calculate yaw by measuring Earth’s magnetic field’s horizontal components. However, in the presence of tilt (pitch or roll), a tilt-compensation operation is necessary. This is usually done by projecting measurements onto a horizontal plane. This method has limitations, particularly for large tilt angles and when the IMU is pointing toward the east or west directions. In this paper, we expose the shortcomings of this conventional approach and propose a novel machine learning–based solution employing an artificial neural network (ANN). This method eliminates the need to determine tilt angles and uses accelerometer and magnetometer measurements as its inputs. The dataset for training and testing the ANN was collected based on a 3D nonmagnetic scaled platform, using a low-cost IMU and a Raspberry Pi platform. On one hand, our method outperforms the conventional tilt-compensation technique and other complementary filters (Madgwick and Mahony) in terms of accuracy, as evidenced by the root mean square error (RMSE = 1.95°). However, this superiority comes at the expense of a more complex system that consumes more processing time.
{"title":"Artificial neural network for tilt compensation in yaw estimation","authors":"Ali Mounir Halitim, M. Bouhedda, Sofiane Tchoketch-Kebir, S. Rebouh","doi":"10.1177/01423312231214832","DOIUrl":"https://doi.org/10.1177/01423312231214832","url":null,"abstract":"Low-cost inertial measurement units (IMUs) are commonly used to determine the orientation of objects, such as unmanned aerial vehicles (UAVs) and smartphones. They calculate yaw by measuring Earth’s magnetic field’s horizontal components. However, in the presence of tilt (pitch or roll), a tilt-compensation operation is necessary. This is usually done by projecting measurements onto a horizontal plane. This method has limitations, particularly for large tilt angles and when the IMU is pointing toward the east or west directions. In this paper, we expose the shortcomings of this conventional approach and propose a novel machine learning–based solution employing an artificial neural network (ANN). This method eliminates the need to determine tilt angles and uses accelerometer and magnetometer measurements as its inputs. The dataset for training and testing the ANN was collected based on a 3D nonmagnetic scaled platform, using a low-cost IMU and a Raspberry Pi platform. On one hand, our method outperforms the conventional tilt-compensation technique and other complementary filters (Madgwick and Mahony) in terms of accuracy, as evidenced by the root mean square error (RMSE = 1.95°). However, this superiority comes at the expense of a more complex system that consumes more processing time.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"52 50","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-12-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138949394","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-15DOI: 10.1177/01423312231213125
Sok Li Lim, W. C. Yeong, Z. L. Chong, Chew Peng Gan, M. Khoo
A major challenge for control charts monitoring the coefficient of variation is to quickly detect shifts in this parameter, so that assignable cause(s) can be quickly removed and the process can operate in an in-control state with a stable coefficient of variation. This is especially so when there are constraints in the sample size. One proposed strategy is to vary the sample size according to the most recent information. However, a side-sensitive synthetic chart monitoring the coefficient of variation with variable sample size is not available. This paper contributes to the literature by developing a variable sample size side-sensitive synthetic chart for the coefficient of variation. The main contributions are in terms of illustrating the operations of the chart, deriving the formulae to evaluate its performance and developing the algorithms to optimize its performance. Comparisons with current charts show that the proposed chart outperforms all existing synthetic-type charts monitoring the coefficient of variation. The proposed chart also outperforms the variable sample size coefficient of variation chart for all shift sizes. In addition, it outperforms the variable sample size run sum and variable sample size Exponentially Weighted Moving Average charts monitoring the coefficient of variation for moderate and large shift sizes.
{"title":"A variable sample size side-sensitive synthetic coefficient of variation chart","authors":"Sok Li Lim, W. C. Yeong, Z. L. Chong, Chew Peng Gan, M. Khoo","doi":"10.1177/01423312231213125","DOIUrl":"https://doi.org/10.1177/01423312231213125","url":null,"abstract":"A major challenge for control charts monitoring the coefficient of variation is to quickly detect shifts in this parameter, so that assignable cause(s) can be quickly removed and the process can operate in an in-control state with a stable coefficient of variation. This is especially so when there are constraints in the sample size. One proposed strategy is to vary the sample size according to the most recent information. However, a side-sensitive synthetic chart monitoring the coefficient of variation with variable sample size is not available. This paper contributes to the literature by developing a variable sample size side-sensitive synthetic chart for the coefficient of variation. The main contributions are in terms of illustrating the operations of the chart, deriving the formulae to evaluate its performance and developing the algorithms to optimize its performance. Comparisons with current charts show that the proposed chart outperforms all existing synthetic-type charts monitoring the coefficient of variation. The proposed chart also outperforms the variable sample size coefficient of variation chart for all shift sizes. In addition, it outperforms the variable sample size run sum and variable sample size Exponentially Weighted Moving Average charts monitoring the coefficient of variation for moderate and large shift sizes.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"37 10","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138997601","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-14DOI: 10.1177/01423312231210054
Oussama Esfouna, M. Ouahi, E. Tissir
In this paper, a new fuzzy Functional observer is developed for nonlinear neutral systems. Also, the existence conditions for it are studied. The delay-dependent stability of this observer is guaranteed by the combination of the solution of the Sylvester equation and the Lyapunov–Krasovskii stability approach. The parameters of the studied observer are obtained by solving linear matrix inequalities (LMIs). The performance of the approach developed in this paper is demonstrated at the end of the paper by numerical examples.
{"title":"Functional observer design for T-S fuzzy neutral systems","authors":"Oussama Esfouna, M. Ouahi, E. Tissir","doi":"10.1177/01423312231210054","DOIUrl":"https://doi.org/10.1177/01423312231210054","url":null,"abstract":"In this paper, a new fuzzy Functional observer is developed for nonlinear neutral systems. Also, the existence conditions for it are studied. The delay-dependent stability of this observer is guaranteed by the combination of the solution of the Sylvester equation and the Lyapunov–Krasovskii stability approach. The parameters of the studied observer are obtained by solving linear matrix inequalities (LMIs). The performance of the approach developed in this paper is demonstrated at the end of the paper by numerical examples.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"412 3","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-12-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138974095","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-12-06DOI: 10.1177/01423312231213677
Ali Ihsan Tas, Mehmet Iscan, Berkay Gurkan, Cuneyt Yilmaz
The continuous telemetry transmission between unmanned aerial vehicles (UAVs) and ground control stations is important particularly in scenarios lacking global positioning system (GPS) data. This paper proposes an adaptive novel elliptic trajectory formula-based tracking algorithm for received signal strength indicator (ANETF-RSSI) which dynamically optimizes model parameters based on energy-associated RSSI measurement errors. ANETF-RSSI generates a variable two-dimensional (2D) RSSI map to identify optimal paths, even under challenging conditions like circular flight paths, varying operating ranges, and accelerated maneuvering, which causes uncertainty into RSSI measurements during flight. In contrast to previous methods, the proposed approach eliminates the reliance on telemetry data such as GPS or complex multiantenna configurations, ensuring robust UAV communication continuity across routes ranging from 100 m to 100 km, even as the UAV rotates around the antenna. This method offers substantial contributions, including enhanced monitoring precision, simplified hardware configurations, continuous tracking with superior accuracy, and adaptability to diverse range routes without the need for preflight parameter tuning. Performance evaluations demonstrate that the proposed ANETF-RSSI method consistently outperforms existing technique, improving nominal performance by 32.02% in the most challenging operational scenarios and achieving a remarkable 48.76% improvement in minimum RSSI values. Consequently, this research provides a versatile and adaptive tracking solution for unexpected UAV flight trajectories.
{"title":"Adaptive elliptic trajectory-based received signal strength indicator antenna tracking algorithm","authors":"Ali Ihsan Tas, Mehmet Iscan, Berkay Gurkan, Cuneyt Yilmaz","doi":"10.1177/01423312231213677","DOIUrl":"https://doi.org/10.1177/01423312231213677","url":null,"abstract":"The continuous telemetry transmission between unmanned aerial vehicles (UAVs) and ground control stations is important particularly in scenarios lacking global positioning system (GPS) data. This paper proposes an adaptive novel elliptic trajectory formula-based tracking algorithm for received signal strength indicator (ANETF-RSSI) which dynamically optimizes model parameters based on energy-associated RSSI measurement errors. ANETF-RSSI generates a variable two-dimensional (2D) RSSI map to identify optimal paths, even under challenging conditions like circular flight paths, varying operating ranges, and accelerated maneuvering, which causes uncertainty into RSSI measurements during flight. In contrast to previous methods, the proposed approach eliminates the reliance on telemetry data such as GPS or complex multiantenna configurations, ensuring robust UAV communication continuity across routes ranging from 100 m to 100 km, even as the UAV rotates around the antenna. This method offers substantial contributions, including enhanced monitoring precision, simplified hardware configurations, continuous tracking with superior accuracy, and adaptability to diverse range routes without the need for preflight parameter tuning. Performance evaluations demonstrate that the proposed ANETF-RSSI method consistently outperforms existing technique, improving nominal performance by 32.02% in the most challenging operational scenarios and achieving a remarkable 48.76% improvement in minimum RSSI values. Consequently, this research provides a versatile and adaptive tracking solution for unexpected UAV flight trajectories.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"17 4","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"138595464","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.1177/01423312231201234
Hakan Kızmaz
A current challenge with adaptive controllers is to define efficient tuning methods of the controller parameters. Unlike linear systems, nonlinear systems may need parameters that are continuously tuned at different operating points to provide stability and desired behaviours. This study aims to develop a solution for tuning proportional–integral–derivative (PID) controller parameters as opposed to changing the operating points of a nonlinear system. Most tuning methods calculate parameters according to the system’s step or frequency response. However, adaptive controllers have self-tuneable parameters or control rules. The proposed algorithm in this paper contains a controller, an estimator, and a reference model, and uses the system model. Unlike the model reference adaptive control method, the proposed controller has tuneable controller parameters estimated by the extended Kalman–Bucy filter. The filter estimates the controller parameters to make the system perform like the auxiliary ideal reference model to ensure minimum-time consumption. Hence, this study aims to develop an algorithm that will automatically calculate controller parameters for each operating point of the controlled chaotic or nonlinear system to minimize settling time at each operating point. The proposed algorithm is implemented in a unified chaotic system in which the estimator and controller of the system run together. Simulation results confirm the performance of the proposed algorithm. In addition, the simulation results provide strong evidence that the proposed algorithm can be an effective tool for controlling nonlinear or chaotic systems.
{"title":"Control & synchronization of a unified chaotic system using an adaptive controller with an extended Kalman–Bucy-filter based Auto-Tuner","authors":"Hakan Kızmaz","doi":"10.1177/01423312231201234","DOIUrl":"https://doi.org/10.1177/01423312231201234","url":null,"abstract":"A current challenge with adaptive controllers is to define efficient tuning methods of the controller parameters. Unlike linear systems, nonlinear systems may need parameters that are continuously tuned at different operating points to provide stability and desired behaviours. This study aims to develop a solution for tuning proportional–integral–derivative (PID) controller parameters as opposed to changing the operating points of a nonlinear system. Most tuning methods calculate parameters according to the system’s step or frequency response. However, adaptive controllers have self-tuneable parameters or control rules. The proposed algorithm in this paper contains a controller, an estimator, and a reference model, and uses the system model. Unlike the model reference adaptive control method, the proposed controller has tuneable controller parameters estimated by the extended Kalman–Bucy filter. The filter estimates the controller parameters to make the system perform like the auxiliary ideal reference model to ensure minimum-time consumption. Hence, this study aims to develop an algorithm that will automatically calculate controller parameters for each operating point of the controlled chaotic or nonlinear system to minimize settling time at each operating point. The proposed algorithm is implemented in a unified chaotic system in which the estimator and controller of the system run together. Simulation results confirm the performance of the proposed algorithm. In addition, the simulation results provide strong evidence that the proposed algorithm can be an effective tool for controlling nonlinear or chaotic systems.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"36 S159","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135341921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-11-08DOI: 10.1177/01423312231203030
Jan Michael Spoor, Jens Weber, Jivka Ovtcharova
Anomalies in dynamical systems mostly occur as deviations between measurement and prediction. Current anomaly detection methods in multivariate time series often require prior clustering, training data, or cannot distinguish local and global anomalies. Furthermore, no generalized metric exists to evaluate and compare different prediction functions regarding their amount of anomalous behavior. We propose a novel methodology to detect local and global anomalies in time series data of dynamical systems. For this purpose, a theoretical density distribution is derived assuming that only noise conceals the time series. If the theoretical and the empirical density distribution yield significantly different entropies, an anomaly is assumed. For a local anomaly detection, the Mahalanobis distance using the theoretical noise distribution’s covariance is applied to evaluate sequences of predictions and measurements. In addition, the Wasserstein metric enables a comparison of predictions using the distance between the noise and empirical distribution as a measure for selecting the best prediction function. The proposed method performs well on nonlinear time series such as logistic growth and enables a useful selection of a prediction model for satellite orbits. Thus, the proposed method improves anomaly detection in time series and model selection for nonlinear systems.
{"title":"Anomaly detection and prediction evaluation for discrete nonlinear dynamical systems","authors":"Jan Michael Spoor, Jens Weber, Jivka Ovtcharova","doi":"10.1177/01423312231203030","DOIUrl":"https://doi.org/10.1177/01423312231203030","url":null,"abstract":"Anomalies in dynamical systems mostly occur as deviations between measurement and prediction. Current anomaly detection methods in multivariate time series often require prior clustering, training data, or cannot distinguish local and global anomalies. Furthermore, no generalized metric exists to evaluate and compare different prediction functions regarding their amount of anomalous behavior. We propose a novel methodology to detect local and global anomalies in time series data of dynamical systems. For this purpose, a theoretical density distribution is derived assuming that only noise conceals the time series. If the theoretical and the empirical density distribution yield significantly different entropies, an anomaly is assumed. For a local anomaly detection, the Mahalanobis distance using the theoretical noise distribution’s covariance is applied to evaluate sequences of predictions and measurements. In addition, the Wasserstein metric enables a comparison of predictions using the distance between the noise and empirical distribution as a measure for selecting the best prediction function. The proposed method performs well on nonlinear time series such as logistic growth and enables a useful selection of a prediction model for satellite orbits. Thus, the proposed method improves anomaly detection in time series and model selection for nonlinear systems.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"151 4‐5","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135392874","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","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：