Pub Date : 2023-09-08DOI: 10.1177/01423312231189810
Ruicheng Zhang, Pengfei Li, Weizheng Liang
In order to address the problem that the main drive system of rolling mill is easily affected by the impact of biting steel, and considering the nonlinear friction damping and the external perturbations of the main drive system of rolling mill during the rolling process, a fault model of the main drive system of rolling mill is established, and a fault diagnosis and fault tolerance control method of the main drive system of rolling mill based on the nonlinear sliding-mode observer is proposed. In order to suppress the influence of external perturbations on fault diagnosis, a nonlinear sliding-mode observer is constructed for fault diagnosis and fault reconfiguration of the system, and the robustness of the observer to fault reconfiguration is improved by using the sliding-mode control rate [Formula: see text], and the stability of the designed nonlinear sliding-mode observer is proved using Lyapunov’s stability theorem. In order to ensure that the system can operate normally even after a fault occurs, a reference model is designed, and a new controller is redesigned for fault-tolerant control of the system by adding a fault compensation term to the original control scheme using fault estimation information. Through the simulation study of the main drive system of stand F4 of 2030 mm cold rolling mill, it is verified that the observer can accurately track the system state with an angular velocity error of 2.45% and detect and estimate the main drive system failure of rolling mill with an estimation error of no more than 0.04% after a fault occurs; the fault-tolerant control of the main drive system of rolling mill is carried out by using the fault information to restore the system to its normal state, and the angular velocity error is 1.89%.
{"title":"Sliding-mode observer-based fault diagnosis and fault-tolerant control of the main drive system of rolling mill","authors":"Ruicheng Zhang, Pengfei Li, Weizheng Liang","doi":"10.1177/01423312231189810","DOIUrl":"https://doi.org/10.1177/01423312231189810","url":null,"abstract":"In order to address the problem that the main drive system of rolling mill is easily affected by the impact of biting steel, and considering the nonlinear friction damping and the external perturbations of the main drive system of rolling mill during the rolling process, a fault model of the main drive system of rolling mill is established, and a fault diagnosis and fault tolerance control method of the main drive system of rolling mill based on the nonlinear sliding-mode observer is proposed. In order to suppress the influence of external perturbations on fault diagnosis, a nonlinear sliding-mode observer is constructed for fault diagnosis and fault reconfiguration of the system, and the robustness of the observer to fault reconfiguration is improved by using the sliding-mode control rate [Formula: see text], and the stability of the designed nonlinear sliding-mode observer is proved using Lyapunov’s stability theorem. In order to ensure that the system can operate normally even after a fault occurs, a reference model is designed, and a new controller is redesigned for fault-tolerant control of the system by adding a fault compensation term to the original control scheme using fault estimation information. Through the simulation study of the main drive system of stand F4 of 2030 mm cold rolling mill, it is verified that the observer can accurately track the system state with an angular velocity error of 2.45% and detect and estimate the main drive system failure of rolling mill with an estimation error of no more than 0.04% after a fault occurs; the fault-tolerant control of the main drive system of rolling mill is carried out by using the fault information to restore the system to its normal state, and the angular velocity error is 1.89%.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-09-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45766531","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 : 2023-09-07DOI: 10.1177/01423312231183610
Liyao Hu, Guangren Duan
This paper considers the adaptive guaranteed cost tracking (AGCT) control problems for two classes of high-order nonlinear systems with unknown parameters. A new local smooth nonlinear function (LSNF) is introduced first, which provides an important mathematical tool for our controller design. Then, based on the LSNF and the high-order fully actuated (HOFA) system approaches, the AGCT controller is designed for HOFA system with unknown parameter, which guarantees that all of the states of the closed-loop HOFA system are globally bounded, and the tracking error is asymptotically convergent. Moreover, the upper bound of cost function (UBCF) characterizing the tracking performance can be arbitrarily preseted, and is completely independent of the system initial value and the unknown parameter, which significantly improves the tracking performance, and is difficult to achieve by using existing guaranteed cost control (GCC). Furthermore, an extra result, the AGCT controller for a class of strict-feedback systems with high-order form and unknown parameters, is obtained in this paper, which also guarantees that the system tracking error is globally asymptotically convergent with the arbitrarily preseted UBCF characterizing the tracking performance. Three simulation examples, including an inverted pendulum, are presented to show the effect and the superiority of the proposed method.
{"title":"Adaptive guaranteed cost tracking control for high-order nonlinear systems based on fully actuated system approaches","authors":"Liyao Hu, Guangren Duan","doi":"10.1177/01423312231183610","DOIUrl":"https://doi.org/10.1177/01423312231183610","url":null,"abstract":"This paper considers the adaptive guaranteed cost tracking (AGCT) control problems for two classes of high-order nonlinear systems with unknown parameters. A new local smooth nonlinear function (LSNF) is introduced first, which provides an important mathematical tool for our controller design. Then, based on the LSNF and the high-order fully actuated (HOFA) system approaches, the AGCT controller is designed for HOFA system with unknown parameter, which guarantees that all of the states of the closed-loop HOFA system are globally bounded, and the tracking error is asymptotically convergent. Moreover, the upper bound of cost function (UBCF) characterizing the tracking performance can be arbitrarily preseted, and is completely independent of the system initial value and the unknown parameter, which significantly improves the tracking performance, and is difficult to achieve by using existing guaranteed cost control (GCC). Furthermore, an extra result, the AGCT controller for a class of strict-feedback systems with high-order form and unknown parameters, is obtained in this paper, which also guarantees that the system tracking error is globally asymptotically convergent with the arbitrarily preseted UBCF characterizing the tracking performance. Three simulation examples, including an inverted pendulum, are presented to show the effect and the superiority of the proposed method.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-09-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44604025","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 : 2023-08-22DOI: 10.1177/01423312231157120
Zhen-tao Hu, Liuyang Tian, Wei Hou, Linlin Yang
To improve the accuracy of multiple target tracking in the clutter environment, a new joint probabilistic data association (JPDA) algorithm based on variational Bayesian adaptive moment estimation is proposed. First, considering the existence of measurements, the posterior distribution of the target state in JPDA is composed of two parts of probability weighting, that is, the posterior distribution of the target state that the real measurement exists in the association gate and the posterior distribution of the target state that the real measurement does not exist in the association gate. By combining the conjugate properties of the prior and posterior distributions, the prior distributions of the target state in the two cases are classified to provide more accurate a priori information to filter, so as to improve the accuracy of data association. Second, considering the coupling effect between state estimation and data association process, combined with variational Bayesian inference, the problem of minimizing Kullback–Leibler divergence is transformed into the problem of maximizing the evidence lower bound, thereby effectively measuring the distance between the posterior distribution of target state estimation and the real posterior distribution, so as to improve the accuracy of data association again from the perspective of optimizing nonlinear filter. Finally, the adaptive momentum estimation strategy is introduced to iteratively solve the variable distribution that meets the maximization of the evidence lower bound, and the optimization of the posterior distribution of the target state is completed. Theoretical derivation and simulation experiments are conducted to verify the feasibility and effectiveness of the algorithm.
{"title":"New joint probabilistic data association algorithm based on variational Bayesian adaptive moment estimation","authors":"Zhen-tao Hu, Liuyang Tian, Wei Hou, Linlin Yang","doi":"10.1177/01423312231157120","DOIUrl":"https://doi.org/10.1177/01423312231157120","url":null,"abstract":"To improve the accuracy of multiple target tracking in the clutter environment, a new joint probabilistic data association (JPDA) algorithm based on variational Bayesian adaptive moment estimation is proposed. First, considering the existence of measurements, the posterior distribution of the target state in JPDA is composed of two parts of probability weighting, that is, the posterior distribution of the target state that the real measurement exists in the association gate and the posterior distribution of the target state that the real measurement does not exist in the association gate. By combining the conjugate properties of the prior and posterior distributions, the prior distributions of the target state in the two cases are classified to provide more accurate a priori information to filter, so as to improve the accuracy of data association. Second, considering the coupling effect between state estimation and data association process, combined with variational Bayesian inference, the problem of minimizing Kullback–Leibler divergence is transformed into the problem of maximizing the evidence lower bound, thereby effectively measuring the distance between the posterior distribution of target state estimation and the real posterior distribution, so as to improve the accuracy of data association again from the perspective of optimizing nonlinear filter. Finally, the adaptive momentum estimation strategy is introduced to iteratively solve the variable distribution that meets the maximization of the evidence lower bound, and the optimization of the posterior distribution of the target state is completed. Theoretical derivation and simulation experiments are conducted to verify the feasibility and effectiveness of the algorithm.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44873643","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 : 2023-08-21DOI: 10.1177/01423312231191332
Zhilin Liu, Zhongxin Wang, Shouzheng Yuan, Linhe Zheng, Guosheng Li
This paper considers the state estimation problem for discrete-time linear systems suffering from dense measurement anomalies. Conventional moving horizon estimation algorithms can be used to solve the case containing sparse measurement anomalies, but their performance degrades dramatically as the number of outliers increases. To address this problem, we propose two outliers exclusion-moving horizon estimation strategies. That is, at each sampling instant, solving a set of least-squares cost functions aims to exclude all possible outliers. The state estimates corresponding to the optimal cost are retained and propagated to the next instant, and the procedure is repeated when new information arrives. The stability of the estimation error of the estimators is proved under moderate conditions, namely the observability of the noise-free state equation and the choice of the tuning parameters in the cost function. The simulation results demonstrate the robustness of the proposed approaches in the presence of dense outliers.
{"title":"Design and stability of moving horizon estimator for discrete-time linear systems subject to multiple measurement outliers","authors":"Zhilin Liu, Zhongxin Wang, Shouzheng Yuan, Linhe Zheng, Guosheng Li","doi":"10.1177/01423312231191332","DOIUrl":"https://doi.org/10.1177/01423312231191332","url":null,"abstract":"This paper considers the state estimation problem for discrete-time linear systems suffering from dense measurement anomalies. Conventional moving horizon estimation algorithms can be used to solve the case containing sparse measurement anomalies, but their performance degrades dramatically as the number of outliers increases. To address this problem, we propose two outliers exclusion-moving horizon estimation strategies. That is, at each sampling instant, solving a set of least-squares cost functions aims to exclude all possible outliers. The state estimates corresponding to the optimal cost are retained and propagated to the next instant, and the procedure is repeated when new information arrives. The stability of the estimation error of the estimators is proved under moderate conditions, namely the observability of the noise-free state equation and the choice of the tuning parameters in the cost function. The simulation results demonstrate the robustness of the proposed approaches in the presence of dense outliers.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44505403","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 : 2023-08-19DOI: 10.1177/01423312231190734
Monesha S, S. S
This paper presents a novel control approach for integrated converters using Exact Tracking Error Dynamics Passive Output Feedback control and Exact Static Error Dynamics Passive Output Feedback control. By continuously injecting active distributed power systems (DPS) power sources into the utility grid and loads, the approach reduces harmonic current distortion and maintains unity for the grid’s power factor. The paper compares existing control methods, such as P, PI, proportional–integral–derivative (PID), energy structuring and damping infusion and interconnection and damping assignment—passivity-based control and considers the impacts of instantaneous fluctuations in reference current elements on the AC side and oscillations in DC voltage generated by the DC-link voltage. Relevant switching state functions are designed, and if the maximum power can be fed exceeds the required power from grid-connected loads, the true, reactive, and harmonic current elements of loads are adjusted dynamically, resulting in in-phase sinewave grid currents. The performance analysis is performed using MATLAB/Simulink, and a smaller research prototype is built and discussed.
{"title":"Performance analysis of distributed power systems using error dynamics passive output feedback control","authors":"Monesha S, S. S","doi":"10.1177/01423312231190734","DOIUrl":"https://doi.org/10.1177/01423312231190734","url":null,"abstract":"This paper presents a novel control approach for integrated converters using Exact Tracking Error Dynamics Passive Output Feedback control and Exact Static Error Dynamics Passive Output Feedback control. By continuously injecting active distributed power systems (DPS) power sources into the utility grid and loads, the approach reduces harmonic current distortion and maintains unity for the grid’s power factor. The paper compares existing control methods, such as P, PI, proportional–integral–derivative (PID), energy structuring and damping infusion and interconnection and damping assignment—passivity-based control and considers the impacts of instantaneous fluctuations in reference current elements on the AC side and oscillations in DC voltage generated by the DC-link voltage. Relevant switching state functions are designed, and if the maximum power can be fed exceeds the required power from grid-connected loads, the true, reactive, and harmonic current elements of loads are adjusted dynamically, resulting in in-phase sinewave grid currents. The performance analysis is performed using MATLAB/Simulink, and a smaller research prototype is built and discussed.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45451633","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 : 2023-08-18DOI: 10.1177/01423312231188174
Chunfu Zhang, Yanyan Sun, Wenyong Duan
The robust synchronization of uncertain master–slave Lur’e systems based on time-delayed feedback control is further investigated. A less conservative synchronization stability criterion and a less conservative robust synchronization stability criterion than some recent published references are proposed via Lyapunov stability theory. First, an augmented delay-dependent Lyapunov–Krasovskii functional (LKF) is constructed, where some single integral terms are augmented to the integrand component of a single-integral subfunction. This not only increases some coupling information on some system variables but also increases the coupling information on some necessary variables contained in the inequality lemmas, which can make full use of the inequality lemmas and reduce the conservatism of the synchronization stability criterion. Second, to overcome the nonlinear phenomena in the synchronization criterion, the novel negative definite inequality equivalent transformation lemma is used to transform the nonlinear inequalities to the linear matrix inequalities (LMIs) equivalently, which can be easily solved by the MATLAB LMI-Toolbox. Finally, some common numerical examples are presented to show the effectiveness of the proposed approach.
{"title":"Improvement master–slave robustly synchronous criteria of uncertain chaotic Lur’e systems via an augmented Lyapunov–Krasovskii functional","authors":"Chunfu Zhang, Yanyan Sun, Wenyong Duan","doi":"10.1177/01423312231188174","DOIUrl":"https://doi.org/10.1177/01423312231188174","url":null,"abstract":"The robust synchronization of uncertain master–slave Lur’e systems based on time-delayed feedback control is further investigated. A less conservative synchronization stability criterion and a less conservative robust synchronization stability criterion than some recent published references are proposed via Lyapunov stability theory. First, an augmented delay-dependent Lyapunov–Krasovskii functional (LKF) is constructed, where some single integral terms are augmented to the integrand component of a single-integral subfunction. This not only increases some coupling information on some system variables but also increases the coupling information on some necessary variables contained in the inequality lemmas, which can make full use of the inequality lemmas and reduce the conservatism of the synchronization stability criterion. Second, to overcome the nonlinear phenomena in the synchronization criterion, the novel negative definite inequality equivalent transformation lemma is used to transform the nonlinear inequalities to the linear matrix inequalities (LMIs) equivalently, which can be easily solved by the MATLAB LMI-Toolbox. Finally, some common numerical examples are presented to show the effectiveness of the proposed approach.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48068512","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 : 2023-08-18DOI: 10.1177/01423312231190194
Shiqi Wang, Hui Li, Hua Li, Hui-yuan Shi, Qiubai Sun, P. Li
A robust dynamic output feedback predictive control approach is developed for a discrete system with time-varying delays, unknown external disturbances, and unmeasurable states. First, the discrete system is transformed into an incremental state deviation model. Based on this model, a novel tracking deviation feedback model is established by extending the output tracking error. Then, a robust predictive control law, possessing more degrees of freedom, is designed. The closed-loop model is further given in conjunction with the feedback model. Second, by using the linear matrix inequality (LMI) method, relaxation technique, and variable transformation method, a less conservative stability condition is given in LMI form, which allows the controller to tolerate a greater range of time-varying delays. The gains of the control law are acquired by solving the stability condition, and the control performance can be significantly enhanced. Finally, by utilizing the TTS20 water tank as a simulation case, the viability and effectiveness of the proposed method are demonstrated.
{"title":"Robust dynamic output feedback predictive control for discrete uncertain systems with time-varying delays","authors":"Shiqi Wang, Hui Li, Hua Li, Hui-yuan Shi, Qiubai Sun, P. Li","doi":"10.1177/01423312231190194","DOIUrl":"https://doi.org/10.1177/01423312231190194","url":null,"abstract":"A robust dynamic output feedback predictive control approach is developed for a discrete system with time-varying delays, unknown external disturbances, and unmeasurable states. First, the discrete system is transformed into an incremental state deviation model. Based on this model, a novel tracking deviation feedback model is established by extending the output tracking error. Then, a robust predictive control law, possessing more degrees of freedom, is designed. The closed-loop model is further given in conjunction with the feedback model. Second, by using the linear matrix inequality (LMI) method, relaxation technique, and variable transformation method, a less conservative stability condition is given in LMI form, which allows the controller to tolerate a greater range of time-varying delays. The gains of the control law are acquired by solving the stability condition, and the control performance can be significantly enhanced. Finally, by utilizing the TTS20 water tank as a simulation case, the viability and effectiveness of the proposed method are demonstrated.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46940414","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 : 2023-08-12DOI: 10.1177/01423312231187008
Xiangfei Meng, Gui-chen Zhang, Qiang Zhang
This paper deals with the improvement for the tracking performance of underactuated surface vessels (USVs) under input saturation and actuator faults. The neural networks (NNs) are used to reconstruct the dynamic uncertainty of the ship, and an adaptive law is designed to compensate the adverse effects of external unknown disturbances and bias faults on the system. To improve the tracking performance of the system, a nonlinear link is added in the design process of the control scheme to adjust the system error feedback, and the finite-time control (FTC) technology is used to further improve the steady-state performance and transient performance of the system. In addition, to solve the problem of communication resource limitation, an event-triggered mechanism for switching thresholds is introduced, which reduces the update frequency of controller signals. Based on the above techniques, a trajectory tracking control scheme with a performance improvement mechanism is designed. A rigorous stability analysis is provided for the control scheme using Lyapunov stability theory. Finally, the effectiveness of the control scheme is verified by two sets of simulations.
{"title":"Event-triggered trajectory tracking control of underactuated surface vessels with performance-improving mechanisms under input saturation and actuator faults","authors":"Xiangfei Meng, Gui-chen Zhang, Qiang Zhang","doi":"10.1177/01423312231187008","DOIUrl":"https://doi.org/10.1177/01423312231187008","url":null,"abstract":"This paper deals with the improvement for the tracking performance of underactuated surface vessels (USVs) under input saturation and actuator faults. The neural networks (NNs) are used to reconstruct the dynamic uncertainty of the ship, and an adaptive law is designed to compensate the adverse effects of external unknown disturbances and bias faults on the system. To improve the tracking performance of the system, a nonlinear link is added in the design process of the control scheme to adjust the system error feedback, and the finite-time control (FTC) technology is used to further improve the steady-state performance and transient performance of the system. In addition, to solve the problem of communication resource limitation, an event-triggered mechanism for switching thresholds is introduced, which reduces the update frequency of controller signals. Based on the above techniques, a trajectory tracking control scheme with a performance improvement mechanism is designed. A rigorous stability analysis is provided for the control scheme using Lyapunov stability theory. Finally, the effectiveness of the control scheme is verified by two sets of simulations.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41839957","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 : 2023-08-10DOI: 10.1177/01423312231180916
Fuqiang Di, Linxiao Li, Aijun Li, Yong Guo, Changqing Wang
This paper provides an event-triggered finite-time adaptive bounded controller for attitude tracking of spacecraft formation flying under external disturbances and limited communication. To facilitate the realization of bounded control, a novel full-order terminal sliding mode surface is established according to the hyperbolic tangent function. To reduce the communication frequency among formation members, an event-triggered control strategy that can converge to zero in finite time is investigated based on the full-order sliding mode surface. Under the proposed control strategy, the spacecraft only send their information to neighboring spacecraft when the trigger error exceeds the defined threshold. Rigorous theoretical analysis provides that finite-time convergence and Zeno-free are achieved under the proposed controller. Finally, numerical simulations are exhibited to illustrate the effectiveness of the proposed control law.
{"title":"Adaptive full-order sliding mode bounded attitude control for spacecraft formation flying with event-triggered communication","authors":"Fuqiang Di, Linxiao Li, Aijun Li, Yong Guo, Changqing Wang","doi":"10.1177/01423312231180916","DOIUrl":"https://doi.org/10.1177/01423312231180916","url":null,"abstract":"This paper provides an event-triggered finite-time adaptive bounded controller for attitude tracking of spacecraft formation flying under external disturbances and limited communication. To facilitate the realization of bounded control, a novel full-order terminal sliding mode surface is established according to the hyperbolic tangent function. To reduce the communication frequency among formation members, an event-triggered control strategy that can converge to zero in finite time is investigated based on the full-order sliding mode surface. Under the proposed control strategy, the spacecraft only send their information to neighboring spacecraft when the trigger error exceeds the defined threshold. Rigorous theoretical analysis provides that finite-time convergence and Zeno-free are achieved under the proposed controller. Finally, numerical simulations are exhibited to illustrate the effectiveness of the proposed control law.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48851624","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 : 2023-08-10DOI: 10.1177/01423312231181379
Xiaoying Tan, Wei Guo, Ran Liu, Tianhong Pan
Functional principal component analysis (FPCA) and functional partial least squares (FPLS) are two mainstream functional data analysis (FDA) methods, which have been commonly used to extract deep information hidden in the original data space. However, the process data always contain random noise, which affects the performance of FDA models. To overcome this issue, two functional probabilistic latent variable models (FPLVMs), including functional probabilistic principal component analysis (FPPCA) and functional probabilistic partial least squares (FPPLS) are proposed in this work. First, the process data are converted into functional data using the FDA. Subsequently, a log-likelihood function considering the noise factor and functional latent variables is designed. Finally, the regression model parameters are estimated using an expectation–maximisation algorithm. In contrast to FPPCA, FPPLS decomposes the process data and the key variable with constrained latent variables, which is similar to the partial least squares (PLS) and the principal component analysis (PCA). Moreover, the degeneration mechanism from FPLVMs into probabilistic latent variable models and latent variable models is discussed. An adaptive strategy with functional covariance is used to satisfy the online predictive capabilities of the model. Finally, the proposed approach is validated using a numerical case, the Tennessee Eastman process and an industrial o-xylene distillation column for evaluation.
{"title":"A data-driven soft-sensing approach using probabilistic latent variable model with functional data framework","authors":"Xiaoying Tan, Wei Guo, Ran Liu, Tianhong Pan","doi":"10.1177/01423312231181379","DOIUrl":"https://doi.org/10.1177/01423312231181379","url":null,"abstract":"Functional principal component analysis (FPCA) and functional partial least squares (FPLS) are two mainstream functional data analysis (FDA) methods, which have been commonly used to extract deep information hidden in the original data space. However, the process data always contain random noise, which affects the performance of FDA models. To overcome this issue, two functional probabilistic latent variable models (FPLVMs), including functional probabilistic principal component analysis (FPPCA) and functional probabilistic partial least squares (FPPLS) are proposed in this work. First, the process data are converted into functional data using the FDA. Subsequently, a log-likelihood function considering the noise factor and functional latent variables is designed. Finally, the regression model parameters are estimated using an expectation–maximisation algorithm. In contrast to FPPCA, FPPLS decomposes the process data and the key variable with constrained latent variables, which is similar to the partial least squares (PLS) and the principal component analysis (PCA). Moreover, the degeneration mechanism from FPLVMs into probabilistic latent variable models and latent variable models is discussed. An adaptive strategy with functional covariance is used to satisfy the online predictive capabilities of the model. Finally, the proposed approach is validated using a numerical case, the Tennessee Eastman process and an industrial o-xylene distillation column for evaluation.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46886174","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}
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