Pub Date : 2023-08-10DOI: 10.1177/01423312231185383
Yuling Liang, Jun Zhang, Hui Zhao, Hanguang Su, Xiaohong Cui
This paper develops a novel guaranteed cost control (GCC) approach under the event-triggered mechanism for completely unknown systems using integral reinforcement learning (IRL) algorithm. First, based on the adaptive dynamic programming (ADP) method, the GCC problem is addressed by transforming it into the optimal control problem. Second, without using the accurate information of system dynamics, a model-free data-based GCC approach is designed via IRL algorithm. Moreover, for the purpose of reducing the waste of communication resources, a GCC algorithm is presented under the event-triggered mechanism for completely unknown system by utilizing the explorized IRL algorithm. The critic–actor–disturbance neural networks (NNs) are applied to approximate near optimal solution. In addition, the weight estimations of NNs are tuned synchronously according to the designed novel triggering condition. Furthermore, the stability analysis of the controlled system is given by utilizing the Lyapunov principle. Finally, the simulation results are presented to verify the feasibility of the designed approach.
{"title":"A learning-based approach to event-triggered guaranteed cost control for completely unknown nonlinear systems","authors":"Yuling Liang, Jun Zhang, Hui Zhao, Hanguang Su, Xiaohong Cui","doi":"10.1177/01423312231185383","DOIUrl":"https://doi.org/10.1177/01423312231185383","url":null,"abstract":"This paper develops a novel guaranteed cost control (GCC) approach under the event-triggered mechanism for completely unknown systems using integral reinforcement learning (IRL) algorithm. First, based on the adaptive dynamic programming (ADP) method, the GCC problem is addressed by transforming it into the optimal control problem. Second, without using the accurate information of system dynamics, a model-free data-based GCC approach is designed via IRL algorithm. Moreover, for the purpose of reducing the waste of communication resources, a GCC algorithm is presented under the event-triggered mechanism for completely unknown system by utilizing the explorized IRL algorithm. The critic–actor–disturbance neural networks (NNs) are applied to approximate near optimal solution. In addition, the weight estimations of NNs are tuned synchronously according to the designed novel triggering condition. Furthermore, the stability analysis of the controlled system is given by utilizing the Lyapunov principle. Finally, the simulation results are presented to verify the feasibility of the designed approach.","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":"46912238","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: 10.1177/01423312231183761
Kunfeng Lu, Zhaolei Wang, Chunmei Yu, Na Yao, Wuyi Luo
The fault detection problem of a class of full-envelope flight vehicles with time delays and packet losses is investigated. Their model is established as locally overlapped switched systems to reduce conservatism. The delays and the packet losses are transformed into the parameters of polytopic systems. The switched parameter-dependent fault detection filter (FDF) is then designed. The fault detection system stability and its [Formula: see text] performance under asynchronous switching with average dwell time are analyzed. Moreover, a parity-space–based optimization approach is presented to guarantee that the modified residual signal is sensitive to fault but robust to disturbance. An example of applying this method to the highly maneuverable technology vehicle is given to verify the method’s effectiveness.
{"title":"Asynchronously switched fault detection filter design for full-envelope flight vehicle","authors":"Kunfeng Lu, Zhaolei Wang, Chunmei Yu, Na Yao, Wuyi Luo","doi":"10.1177/01423312231183761","DOIUrl":"https://doi.org/10.1177/01423312231183761","url":null,"abstract":"The fault detection problem of a class of full-envelope flight vehicles with time delays and packet losses is investigated. Their model is established as locally overlapped switched systems to reduce conservatism. The delays and the packet losses are transformed into the parameters of polytopic systems. The switched parameter-dependent fault detection filter (FDF) is then designed. The fault detection system stability and its [Formula: see text] performance under asynchronous switching with average dwell time are analyzed. Moreover, a parity-space–based optimization approach is presented to guarantee that the modified residual signal is sensitive to fault but robust to disturbance. An example of applying this method to the highly maneuverable technology vehicle is given to verify the method’s effectiveness.","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":"42076460","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: 10.1177/01423312231189770
Qian-Kun Liang, Yan Cai, Jin-chun Song, Bin Wang
This paper is focused on asymptotic tracking control of electro-hydraulic actuator (EHA) systems subject to matched and mismatched time-varying disturbances. To counteract the matched disturbance, a novel extended state observer (ESO) is proposed to achieve asymptotic convergence of the estimation error, by incorporating the strictly positive real (SPR) Lyapunov design method and a Nussbaum function. To further suppress the mismatched disturbance, an adaptive robust integral of the sign of the error (RISE) controller is formulated in the backstepping framework based on the proposed ESO. Asymptotic tracking performance is theoretically achieved via closed-loop system stability analysis. The efficacy of the proposed control scheme is verified through comparative experiments executed on an EHA test rig. In this study, a priori bounds of the disturbances and their higher-order derivatives are no longer needed, and only one auxiliary error signal is introduced. This approach loosens the restrictions on the disturbances and reduces the design conservativeness, thus making it promising in practice.
{"title":"A novel ESO-based adaptive RISE control for asymptotic position tracking of electro-hydraulic actuator systems","authors":"Qian-Kun Liang, Yan Cai, Jin-chun Song, Bin Wang","doi":"10.1177/01423312231189770","DOIUrl":"https://doi.org/10.1177/01423312231189770","url":null,"abstract":"This paper is focused on asymptotic tracking control of electro-hydraulic actuator (EHA) systems subject to matched and mismatched time-varying disturbances. To counteract the matched disturbance, a novel extended state observer (ESO) is proposed to achieve asymptotic convergence of the estimation error, by incorporating the strictly positive real (SPR) Lyapunov design method and a Nussbaum function. To further suppress the mismatched disturbance, an adaptive robust integral of the sign of the error (RISE) controller is formulated in the backstepping framework based on the proposed ESO. Asymptotic tracking performance is theoretically achieved via closed-loop system stability analysis. The efficacy of the proposed control scheme is verified through comparative experiments executed on an EHA test rig. In this study, a priori bounds of the disturbances and their higher-order derivatives are no longer needed, and only one auxiliary error signal is introduced. This approach loosens the restrictions on the disturbances and reduces the design conservativeness, thus making it promising in practice.","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":"44669643","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: 10.1177/01423312231187019
Nain de la Cruz, M. Basin
This paper presents the predefined-time convergent robust controller design for a brushed direct current (DC) motor system affected by matched and unmatched deterministic disturbances and stochastic noises, considering both fully measurable and incompletely measurable states. The control algorithm allows the control designer to set the convergence time a priori. The convergence time is independent of initial conditions and disturbances and noises affecting the system. Numerical simulations are conducted to demonstrate efficiency of the designed control algorithm. The obtained results show that the control algorithm counteracts the matched and unmatched disturbances, and noises in case of fully measurable states and mitigates their influence in case of incompletely measurable ones.
{"title":"Predefined-time stabilization of brushed direct current motor system affected by matched and unmatched disturbances and stochastic noises","authors":"Nain de la Cruz, M. Basin","doi":"10.1177/01423312231187019","DOIUrl":"https://doi.org/10.1177/01423312231187019","url":null,"abstract":"This paper presents the predefined-time convergent robust controller design for a brushed direct current (DC) motor system affected by matched and unmatched deterministic disturbances and stochastic noises, considering both fully measurable and incompletely measurable states. The control algorithm allows the control designer to set the convergence time a priori. The convergence time is independent of initial conditions and disturbances and noises affecting the system. Numerical simulations are conducted to demonstrate efficiency of the designed control algorithm. The obtained results show that the control algorithm counteracts the matched and unmatched disturbances, and noises in case of fully measurable states and mitigates their influence in case of incompletely measurable ones.","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":"49227928","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: 10.1177/01423312231189107
Tu Zhang, Guobao Zhang, Yongming Huang
This paper studies a secure iterative interval estimation approach for cyber-physical systems subject to stealthy deception attacks. Under the hypothesis that the system is accessed by a stealthy attack, an iteration scheme integrating the T-N-L observer framework is employed to reconstruct the system state. With the help of a structure separation method, a sufficient condition in terms of linear matrix inequality is provided to obtain convergent observation errors under deception attacks. Resorting to the reachability analysis, a secure state interval is built by means of the analyzed attack bounds and the observation error interval. Simulation studies verify the effectiveness of the proposed method for attack and attack-free cases.
{"title":"Secure iterative interval estimation method for cyber-physical systems subject to stealthy deception attacks","authors":"Tu Zhang, Guobao Zhang, Yongming Huang","doi":"10.1177/01423312231189107","DOIUrl":"https://doi.org/10.1177/01423312231189107","url":null,"abstract":"This paper studies a secure iterative interval estimation approach for cyber-physical systems subject to stealthy deception attacks. Under the hypothesis that the system is accessed by a stealthy attack, an iteration scheme integrating the T-N-L observer framework is employed to reconstruct the system state. With the help of a structure separation method, a sufficient condition in terms of linear matrix inequality is provided to obtain convergent observation errors under deception attacks. Resorting to the reachability analysis, a secure state interval is built by means of the analyzed attack bounds and the observation error interval. Simulation studies verify the effectiveness of the proposed method for attack and attack-free cases.","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":"47315109","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 : 2023-08-09DOI: 10.1177/01423312231185377
He Li, Chenglin Liu, Ya Zhang, Yangyang Chen
This paper tries to solve the quantized practical fixed-time consensus tracking problem for networked Euler–Lagrange systems under the predetermined workspace. To realize the information interaction under the limited bandwidth, a set of encoder, decoder, and average quantizers are constructed to process the interaction data. On this basis, a fixed-time observer is proposed so that each follower can estimate the leader’s information within the quantized communication environment. Afterward, the local tracking control algorithm is designed by using backstepping strategy and adaptive technology, and the state constraint function is introduced to cope with the asymmetric time-varying constraint problem. With the Lyapunov stability criterion, all error signals are guaranteed to remain in the compact sets near the origin within the fixed time. Ultimately, a numerical example is carried out to testify the validity of the proposed scheme.
{"title":"Quantized practical fixed-time consensus tracking for networked Euler–Lagrange systems under the predetermined workspace","authors":"He Li, Chenglin Liu, Ya Zhang, Yangyang Chen","doi":"10.1177/01423312231185377","DOIUrl":"https://doi.org/10.1177/01423312231185377","url":null,"abstract":"This paper tries to solve the quantized practical fixed-time consensus tracking problem for networked Euler–Lagrange systems under the predetermined workspace. To realize the information interaction under the limited bandwidth, a set of encoder, decoder, and average quantizers are constructed to process the interaction data. On this basis, a fixed-time observer is proposed so that each follower can estimate the leader’s information within the quantized communication environment. Afterward, the local tracking control algorithm is designed by using backstepping strategy and adaptive technology, and the state constraint function is introduced to cope with the asymmetric time-varying constraint problem. With the Lyapunov stability criterion, all error signals are guaranteed to remain in the compact sets near the origin within the fixed time. Ultimately, a numerical example is carried out to testify the validity of the proposed scheme.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42341536","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 : 2023-08-09DOI: 10.1177/01423312231190169
Rui-Dong Xi, Tie-Nan Ma, Xiao Xiao, Zhi-Xin Yang
Robot manipulators as an indispensable part of automatic operation are becoming increasingly important in intelligent manufacturing systems, such as grinding and assembly. Although control methods of robot manipulators have been extensively studied, high-precision robots still face new challenges from uncertainties caused by changes in the environment and enhancement of interference. As a consequence, the neural network-based observer is utilized to reduce the influence of uncertainties and external disturbances. In this work, a new kind of nonlinear disturbance observer is designed which could well function with observed states. To improve the control efficiency and response characteristic, a kind of new integral sliding manifold is devised and the control input is generated via backstepping techniques. The stability is proved with Lyapunov theory, and the experimental results are given to demonstrate the effectiveness of the proposed controller.
{"title":"Design and implementation of an adaptive neural network observer–based backstepping sliding mode controller for robot manipulators","authors":"Rui-Dong Xi, Tie-Nan Ma, Xiao Xiao, Zhi-Xin Yang","doi":"10.1177/01423312231190169","DOIUrl":"https://doi.org/10.1177/01423312231190169","url":null,"abstract":"Robot manipulators as an indispensable part of automatic operation are becoming increasingly important in intelligent manufacturing systems, such as grinding and assembly. Although control methods of robot manipulators have been extensively studied, high-precision robots still face new challenges from uncertainties caused by changes in the environment and enhancement of interference. As a consequence, the neural network-based observer is utilized to reduce the influence of uncertainties and external disturbances. In this work, a new kind of nonlinear disturbance observer is designed which could well function with observed states. To improve the control efficiency and response characteristic, a kind of new integral sliding manifold is devised and the control input is generated via backstepping techniques. The stability is proved with Lyapunov theory, and the experimental results are given to demonstrate the effectiveness of the proposed controller.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135696696","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 : 2023-08-09DOI: 10.1177/01423312231190446
Rui Shan, P. Sun, Shuoyu Wang, Hongbin Chang
An each step time-limited iterative learning control model was developed for a cushion robot with velocity constraints. A predictive modeling method was proposed to solve the velocity mutation problem by employing a kinematic model to constrain the velocity inputs, which can then constrain the robot’s actual velocity. Furthermore, a tracking error system was established that used constrained motion velocity and a dynamic model. A new iterative controller with each step time-limited learning was built to reduce the transient adjustment time. Simulation results and comparative analyses revealed that the proposed control method quickly stabilizes the system and ensures that the human–robot system operates at a safe velocity.
{"title":"Each step time-limited iterative learning control for a cushion robot with motion velocity constraints","authors":"Rui Shan, P. Sun, Shuoyu Wang, Hongbin Chang","doi":"10.1177/01423312231190446","DOIUrl":"https://doi.org/10.1177/01423312231190446","url":null,"abstract":"An each step time-limited iterative learning control model was developed for a cushion robot with velocity constraints. A predictive modeling method was proposed to solve the velocity mutation problem by employing a kinematic model to constrain the velocity inputs, which can then constrain the robot’s actual velocity. Furthermore, a tracking error system was established that used constrained motion velocity and a dynamic model. A new iterative controller with each step time-limited learning was built to reduce the transient adjustment time. Simulation results and comparative analyses revealed that the proposed control method quickly stabilizes the system and ensures that the human–robot system operates at a safe velocity.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46981461","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 : 2023-08-07DOI: 10.1177/01423312231190435
Baokun Han, Bo Li, Huadong Du, Jinrui Wang, Shuo Xing, Lijin Song, Junqing Ma, Haozhou Ma
In recent years, transfer learning has been widely used in mechanical fault diagnosis with some achievements. However, most transfer learning methods do not perform well in diagnosis when the speed and load change simultaneously. Inspired by the adversarial learning mechanism, a transfer learning method named attention mechanism-guided domain adversarial network (AMDAN) is proposed in this paper. AMDAN regards the convolutional neural networks (CNNs) as the generator of the domain adversarial network to learn mutually invariant features and the domain classifier as the discriminator of the domain adversarial network. Attention mechanism is introduced to take into account the interchannel and intraspace feature fusion to improve the training efficiency. Then, multi-kernel maximum mean discrepancy (MK-MMD) is used to measure the distance of different feature spaces to achieve domain alignment. Finally, the superiority of AMDAN is verified by two sets of gear fault diagnosis experiments. The experimental results show that AMDAN has the highest classification accuracy and the strongest generalization ability compared with other methods.
{"title":"An attention mechanism-guided domain adversarial network for gearbox fault diagnosis under different operating conditions","authors":"Baokun Han, Bo Li, Huadong Du, Jinrui Wang, Shuo Xing, Lijin Song, Junqing Ma, Haozhou Ma","doi":"10.1177/01423312231190435","DOIUrl":"https://doi.org/10.1177/01423312231190435","url":null,"abstract":"In recent years, transfer learning has been widely used in mechanical fault diagnosis with some achievements. However, most transfer learning methods do not perform well in diagnosis when the speed and load change simultaneously. Inspired by the adversarial learning mechanism, a transfer learning method named attention mechanism-guided domain adversarial network (AMDAN) is proposed in this paper. AMDAN regards the convolutional neural networks (CNNs) as the generator of the domain adversarial network to learn mutually invariant features and the domain classifier as the discriminator of the domain adversarial network. Attention mechanism is introduced to take into account the interchannel and intraspace feature fusion to improve the training efficiency. Then, multi-kernel maximum mean discrepancy (MK-MMD) is used to measure the distance of different feature spaces to achieve domain alignment. Finally, the superiority of AMDAN is verified by two sets of gear fault diagnosis experiments. The experimental results show that AMDAN has the highest classification accuracy and the strongest generalization ability compared with other methods.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44842146","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 : 2023-08-07DOI: 10.1177/01423312231189809
Wenhan Zhang, Wei Cui, X. Li, Mingzhi Xu, Chen-Shan Wang
In an indoor environment where global positioning system (GPS) signals are severely attenuated, ultra-wideband (UWB) and 2D lidar are widely used in the autonomous positioning of mobile platforms. However, the presence of nonline-of-sight (NLOS) environments can lead to large errors in UWB positioning, and 2D lidar will increase the cumulative error due to the loss of accuracy in sparsely textured scenes. In order to reduce the positioning error, a UWB and 2D lidar fusion positioning algorithm based on the assistance of a few landmarks is proposed in this paper. Considering the colored noise of lidar location data, a Kalman filter algorithm based on cumulative error analysis is proposed. First, the lidar error curve is fitted by the least-square method, and then the relationship between the noise covariance matrix and the lidar cumulative error function is established by introducing the scale factor, which is substituted into the Kalman prediction equation. Experimental results show that the proposed multi-sensor fusion localization algorithm is feasible, and compared with the single localization method, the proposed fusion algorithm can significantly improve the localization accuracy; matching landmarks can achieve a positioning accuracy of 0.15 m, which is about 24.4% lower than the root mean square error of traditional Kalman filter.
{"title":"2D lidar and ultra-wideband fusion location algorithm based on landmark assistance","authors":"Wenhan Zhang, Wei Cui, X. Li, Mingzhi Xu, Chen-Shan Wang","doi":"10.1177/01423312231189809","DOIUrl":"https://doi.org/10.1177/01423312231189809","url":null,"abstract":"In an indoor environment where global positioning system (GPS) signals are severely attenuated, ultra-wideband (UWB) and 2D lidar are widely used in the autonomous positioning of mobile platforms. However, the presence of nonline-of-sight (NLOS) environments can lead to large errors in UWB positioning, and 2D lidar will increase the cumulative error due to the loss of accuracy in sparsely textured scenes. In order to reduce the positioning error, a UWB and 2D lidar fusion positioning algorithm based on the assistance of a few landmarks is proposed in this paper. Considering the colored noise of lidar location data, a Kalman filter algorithm based on cumulative error analysis is proposed. First, the lidar error curve is fitted by the least-square method, and then the relationship between the noise covariance matrix and the lidar cumulative error function is established by introducing the scale factor, which is substituted into the Kalman prediction equation. Experimental results show that the proposed multi-sensor fusion localization algorithm is feasible, and compared with the single localization method, the proposed fusion algorithm can significantly improve the localization accuracy; matching landmarks can achieve a positioning accuracy of 0.15 m, which is about 24.4% lower than the root mean square error of traditional Kalman filter.","PeriodicalId":49426,"journal":{"name":"Transactions of the Institute of Measurement and Control","volume":" ","pages":""},"PeriodicalIF":1.8,"publicationDate":"2023-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47629938","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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