Pub Date : 2025-02-21DOI: 10.1016/j.conengprac.2025.106281
Xu Deng , Dapeng Tian
Admittance control is a widely used approach for ensuring compliant robot behavior in physical human–robot interaction (pHRI) tasks. The selection of admittance parameters is crucial, as it directly affects interaction stability. However, this process becomes challenging when the robot’s interaction with objects involves not only the human hand but also the task environment. This is because the task environment is often unknown and hard to predict while the models of the human hand have been extensively studied in previous work. To address this issue, this paper proposes an admittance adaptive algorithm that ensures stability in human–robot-environment interaction tasks. This algorithm can adjust damping online without prior information about environments. Specifically, we consider the coupling between the robot, human hand, and task environment, treating them as a whole to analyze interaction stability and construct an energy function. Then, based on the energy function, a passive observer is designed to monitor unstable behaviors during the interaction process. Finally, the algorithm adjusts the damping online based on the observed values. The algorithm was experimentally validated using a custom admittance force feedback device. Experimental results indicate that the algorithm can ensure interaction stability without prior information about environments. In the experiment of writing letters, compared to a constant-parameter admittance controller, the algorithm reduces operator effort while maintaining stability.
{"title":"An admittance adaptive force feedback device and its interaction stability involving coupling with humans and uncertain environments","authors":"Xu Deng , Dapeng Tian","doi":"10.1016/j.conengprac.2025.106281","DOIUrl":"10.1016/j.conengprac.2025.106281","url":null,"abstract":"<div><div>Admittance control is a widely used approach for ensuring compliant robot behavior in physical human–robot interaction (pHRI) tasks. The selection of admittance parameters is crucial, as it directly affects interaction stability. However, this process becomes challenging when the robot’s interaction with objects involves not only the human hand but also the task environment. This is because the task environment is often unknown and hard to predict while the models of the human hand have been extensively studied in previous work. To address this issue, this paper proposes an admittance adaptive algorithm that ensures stability in human–robot-environment interaction tasks. This algorithm can adjust damping online without prior information about environments. Specifically, we consider the coupling between the robot, human hand, and task environment, treating them as a whole to analyze interaction stability and construct an energy function. Then, based on the energy function, a passive observer is designed to monitor unstable behaviors during the interaction process. Finally, the algorithm adjusts the damping online based on the observed values. The algorithm was experimentally validated using a custom admittance force feedback device. Experimental results indicate that the algorithm can ensure interaction stability without prior information about environments. In the experiment of writing letters, compared to a constant-parameter admittance controller, the algorithm reduces operator effort while maintaining stability.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106281"},"PeriodicalIF":5.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143464450","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-20DOI: 10.1016/j.conengprac.2025.106285
Yong Ruan , Tao Tang
This paper addresses the control problem of a time-delay compensation method with multirate control in Youla–Kucera parametrization to reject disturbance. Such design methodologies not only enhance the disturbance rejection performance within the control bandwidth, but can also even break through the bandwidth to reject disturbance up to the Nyquist frequency. First, the time-delay function can be simplified to the real number at the disturbance characteristic frequency by tuning the additional time-delay factor for compensation, resulting in alleviating the detrimental effects of time delays. Next, a multirate control mode is proposed to implement the fractional compensation condition for solving the time-delay alignment problem. Moreover, this paper presents a parallel design approach for Q filters, significantly attenuating beam jitter resulting from complex multi-frequency disturbances. Finally, to assess the proposed method for beam jitter attenuation, experiments were conducted on a line-of-sight stabilization testbed. The results demonstrate that the proposed method can effectively enhance the disturbance rejection performance in time-delay control systems.
{"title":"An optimized Youla–Kucera parametrization with time-delay compensation in multirate parallel control for disturbance rejection up to Nyquist frequency","authors":"Yong Ruan , Tao Tang","doi":"10.1016/j.conengprac.2025.106285","DOIUrl":"10.1016/j.conengprac.2025.106285","url":null,"abstract":"<div><div>This paper addresses the control problem of a time-delay compensation method with multirate control in Youla–Kucera parametrization to reject disturbance. Such design methodologies not only enhance the disturbance rejection performance within the control bandwidth, but can also even break through the bandwidth to reject disturbance up to the Nyquist frequency. First, the time-delay function can be simplified to the real number <span><math><mrow><mo>±</mo><mn>1</mn></mrow></math></span> at the disturbance characteristic frequency by tuning the additional time-delay factor for compensation, resulting in alleviating the detrimental effects of time delays. Next, a multirate control mode is proposed to implement the fractional compensation condition for solving the time-delay alignment problem. Moreover, this paper presents a parallel design approach for Q filters, significantly attenuating beam jitter resulting from complex multi-frequency disturbances. Finally, to assess the proposed method for beam jitter attenuation, experiments were conducted on a line-of-sight stabilization testbed. The results demonstrate that the proposed method can effectively enhance the disturbance rejection performance in time-delay control systems.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106285"},"PeriodicalIF":5.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143445358","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-19DOI: 10.1016/j.conengprac.2025.106286
Lin Qi, Jin Zhang, Xiaohong Jiao
This paper investigates the connected cruise control issue for the connected autonomous vehicle (CAV) in a mixed platoon consisting of a CAV, consecutive human-driven vehicles (HDVs), and a connected HDV considering mixed traffic of human-autonomous vehicles from the low penetration of autonomous vehicles. To deal with the uncertainty of traffic flow and vehicle platooning when the uncertain number of HDVs enter or leave the mixed platoon, a CAV predictive cruise control strategy based on the prediction of the preceding vehicle’s speed is designed for the CAV with the help of the information of connected vehicles ahead and Signal Phase and Timing (SPaT) information through vehicle-to-everything (V2X) communication. A stochastic speed prediction method combining a conditional linear Gaussian speed prediction model and a backpropagation neural network is proposed, which improves the prediction accuracy of the future speed of the predecessor vehicle. The CAV’s target speed is planned based on the network information so that the CAV can pass the intersection without stopping. The fuel efficiency driving problem is transformed into the target speed tracking problem, and the optimal solution is carried out in the model predictive control (MPC) framework, which improves fuel economy while ensuring safety. Compared with existing other schemes verify the effectiveness and advantage of the designed strategy.
{"title":"Predecessor speed prediction-based predictive cruise control of connected autonomous vehicle in platoon with multiple-human-driven-vehicles","authors":"Lin Qi, Jin Zhang, Xiaohong Jiao","doi":"10.1016/j.conengprac.2025.106286","DOIUrl":"10.1016/j.conengprac.2025.106286","url":null,"abstract":"<div><div>This paper investigates the connected cruise control issue for the connected autonomous vehicle (CAV) in a mixed platoon consisting of a CAV, consecutive human-driven vehicles (HDVs), and a connected HDV considering mixed traffic of human-autonomous vehicles from the low penetration of autonomous vehicles. To deal with the uncertainty of traffic flow and vehicle platooning when the uncertain number of HDVs enter or leave the mixed platoon, a CAV predictive cruise control strategy based on the prediction of the preceding vehicle’s speed is designed for the CAV with the help of the information of connected vehicles ahead and Signal Phase and Timing (SPaT) information through vehicle-to-everything (V2X) communication. A stochastic speed prediction method combining a conditional linear Gaussian speed prediction model and a backpropagation neural network is proposed, which improves the prediction accuracy of the future speed of the predecessor vehicle. The CAV’s target speed is planned based on the network information so that the CAV can pass the intersection without stopping. The fuel efficiency driving problem is transformed into the target speed tracking problem, and the optimal solution is carried out in the model predictive control (MPC) framework, which improves fuel economy while ensuring safety. Compared with existing other schemes verify the effectiveness and advantage of the designed strategy.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106286"},"PeriodicalIF":5.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437318","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-19DOI: 10.1016/j.conengprac.2025.106280
Ze Wang, Zhongyang Han, Jun Zhao, Wei Wang
The state prediction of by-product gas system in steel industry plays a pivotal role in its safety assessment, so as to maintain stable operation and production. The fluctuation caused by some units in a time window will then affect others by spatially distributed pipeline network, which may lead to potential safety threats, such as shortage supply, unstable transmission, etc. As such, a multi-node state prediction model considering spatial and temporal characteristics for by-product gas system is proposed in this paper. Considering that the distribution of the key nodes including generation, transmission, storage and consumption presents a non-Euclidean spatial structure, the byproduct gas network is intuitively addressed as a graph model according to the state features in this study, which not only innovatively defines both nodes and edges with regard to their practical consideration, but also establishes physics-related constraints to efficiently and accurately capture the correlation. Then, an interactive extraction mechanism of the node–edge features is designed to achieve dynamic updating of the graph neural network, so that the transient characteristic of gas transportation process can be fully reflected. Finally, the Gated Recurrent Unit (GRU) is introduced to capture the temporal-dependent relationship. Based on the actual data of an iron and steel enterprise in China, the experimental results verified that the proposed method exhibits an advanced accuracy for multi-node prediction. In addition, the prediction interval is constructed to quantify reliability based on the numeric prediction results, which is then verified to be effective for supporting the safety assessment.
{"title":"A spatiotemporal characteristics based multi-nodes state prediction method for byproduct gas system and its application on safety assessment","authors":"Ze Wang, Zhongyang Han, Jun Zhao, Wei Wang","doi":"10.1016/j.conengprac.2025.106280","DOIUrl":"10.1016/j.conengprac.2025.106280","url":null,"abstract":"<div><div>The state prediction of by-product gas system in steel industry plays a pivotal role in its safety assessment, so as to maintain stable operation and production. The fluctuation caused by some units in a time window will then affect others by spatially distributed pipeline network, which may lead to potential safety threats, such as shortage supply, unstable transmission, etc. As such, a multi-node state prediction model considering spatial and temporal characteristics for by-product gas system is proposed in this paper. Considering that the distribution of the key nodes including generation, transmission, storage and consumption presents a non-Euclidean spatial structure, the byproduct gas network is intuitively addressed as a graph model according to the state features in this study, which not only innovatively defines both nodes and edges with regard to their practical consideration, but also establishes physics-related constraints to efficiently and accurately capture the correlation. Then, an interactive extraction mechanism of the node–edge features is designed to achieve dynamic updating of the graph neural network, so that the transient characteristic of gas transportation process can be fully reflected. Finally, the Gated Recurrent Unit (GRU) is introduced to capture the temporal-dependent relationship. Based on the actual data of an iron and steel enterprise in China, the experimental results verified that the proposed method exhibits an advanced accuracy for multi-node prediction. In addition, the prediction interval is constructed to quantify reliability based on the numeric prediction results, which is then verified to be effective for supporting the safety assessment.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106280"},"PeriodicalIF":5.4,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143437319","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-18DOI: 10.1016/j.conengprac.2025.106282
Kaixin Cui , Wenjing Wu , Jun Shang , Dawei Shi
Alarm systems are essential for the safety maintenance and health management of industrial systems. In this work, a dynamic alarm monitoring approach with data-driven ellipsoidal threshold learning is proposed, and an unknown system is directly learned using noisy data without model identification. An ellipsoid-based normal operating zone of the system variable is iteratively predicted based on system dynamics, and is updated as an external approximation of the intersection of a predicted ellipsoid and a measurement-based ellipsoid with an event-triggering condition. Then, the dynamic alarm limits are calculated for each dimension of the output by an ellipsoid-based quadratic equation, and a projection strategy from output points to the predicted ellipsoids is designed to have two different solutions to the equation. The effectiveness of the proposed dynamic alarm monitoring approach is illustrated by experimental results on the sensor fault and actuator fault detection of an ultrasonic motor with and without an event-triggering condition, respectively.
{"title":"Dynamic alarm monitoring with data-driven ellipsoidal threshold learning","authors":"Kaixin Cui , Wenjing Wu , Jun Shang , Dawei Shi","doi":"10.1016/j.conengprac.2025.106282","DOIUrl":"10.1016/j.conengprac.2025.106282","url":null,"abstract":"<div><div>Alarm systems are essential for the safety maintenance and health management of industrial systems. In this work, a dynamic alarm monitoring approach with data-driven ellipsoidal threshold learning is proposed, and an unknown system is directly learned using noisy data without model identification. An ellipsoid-based normal operating zone of the system variable is iteratively predicted based on system dynamics, and is updated as an external approximation of the intersection of a predicted ellipsoid and a measurement-based ellipsoid with an event-triggering condition. Then, the dynamic alarm limits are calculated for each dimension of the output by an ellipsoid-based quadratic equation, and a projection strategy from output points to the predicted ellipsoids is designed to have two different solutions to the equation. The effectiveness of the proposed dynamic alarm monitoring approach is illustrated by experimental results on the sensor fault and actuator fault detection of an ultrasonic motor with and without an event-triggering condition, respectively.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106282"},"PeriodicalIF":5.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-17DOI: 10.1016/j.conengprac.2025.106270
Zariff M. Gomes , Hassan Moussa , Yann Le Gall , Edemar O. Prado , Gilney Damm , José Renes Pinheiro , Christophe Ripoll
This paper introduces a nonlinear state-space model for a Dynamic Wireless Power Transfer System (DWPT). DWPT enables the continuous delivery of power to an electric vehicle while it moves along the road, allowing long-haul vehicles to operate with a relatively small battery. The system comprises primary side coils, which are supplied by DC/AC converters. These coils transmit power through induction to an electric vehicle. Within the vehicle (secondary side), a power receiver coil is connected to a full bridge diode rectifier, followed by the standard electric vehicle system. In the second step, the paper presents the design of a control system that ensures the seamless transfer of power to the vehicle as it moves along the road. The chosen controller is an Extremum Seeking algorithm, capable of implementation in high-speed systems compatible with real-time control for fast-moving vehicles. The following step involves conducting test-bed experiments using the designed controller to verify the alignment of the proposed mathematical model with the real system. Furthermore, the controller achieves maximum power transfer and maintains power and voltage across the load during transient states. The proposed model effectively captures the relevant dynamics and is well-suited for control design. Additionally, it offers faster simulation times compared to the full electrical model. Due to its good fit with experimental results, the model can be utilized for sizing, design, and tuning of both the system and control algorithms. This is especially valuable before conducting more detailed simulations on the electrical model and, eventually, test-bed experiments and real-life deployment.
{"title":"A nonlinear state-space model and control algorithm for a dynamic wireless power transfer system electric vehicle charger application","authors":"Zariff M. Gomes , Hassan Moussa , Yann Le Gall , Edemar O. Prado , Gilney Damm , José Renes Pinheiro , Christophe Ripoll","doi":"10.1016/j.conengprac.2025.106270","DOIUrl":"10.1016/j.conengprac.2025.106270","url":null,"abstract":"<div><div>This paper introduces a nonlinear state-space model for a Dynamic Wireless Power Transfer System (DWPT). DWPT enables the continuous delivery of power to an electric vehicle while it moves along the road, allowing long-haul vehicles to operate with a relatively small battery. The system comprises primary side coils, which are supplied by DC/AC converters. These coils transmit power through induction to an electric vehicle. Within the vehicle (secondary side), a power receiver coil is connected to a full bridge diode rectifier, followed by the standard electric vehicle system. In the second step, the paper presents the design of a control system that ensures the seamless transfer of power to the vehicle as it moves along the road. The chosen controller is an Extremum Seeking algorithm, capable of implementation in high-speed systems compatible with real-time control for fast-moving vehicles. The following step involves conducting test-bed experiments using the designed controller to verify the alignment of the proposed mathematical model with the real system. Furthermore, the controller achieves maximum power transfer and maintains power and voltage across the load during transient states. The proposed model effectively captures the relevant dynamics and is well-suited for control design. Additionally, it offers faster simulation times compared to the full electrical model. Due to its good fit with experimental results, the model can be utilized for sizing, design, and tuning of both the system and control algorithms. This is especially valuable before conducting more detailed simulations on the electrical model and, eventually, test-bed experiments and real-life deployment.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106270"},"PeriodicalIF":5.4,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429977","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this article, we present and experimentally validate a safe docking control strategy designed for an experimental planar floating platform, called the Slider. Three degrees-of-freedom (DOF) platforms like the Slider are used extensively in space industry and academia to emulate micro-gravity conditions on Earth, for validating in-plane Guidance, Navigation and Control (GNC) algorithms. The Slider uses an air cushion (induced by air bearings) to levitate on a smooth flat table, thus emulating the in-plane zero-gravity motion of a spacecraft in orbit. The proposed docking control strategy is applicable in the in-plane approach and docking phases of space docking missions, and is based on the Control Barrier Functions (CBF) approach, where a safe set (a Cardioid), capturing the clearance and direction-of-approach constraints, is rendered positively forward invariant. To enable precise and safe docking in the presence of unmodeled dynamics, disturbances induced by the tether and drifts induced by the non-flat floating surface, we present a switching strategy among the zero and positive level sets of a Cardioid function. In the approach phase, the positive contour of the Cardioid function smoothly steers the Slider platform into the neighborhood of a deadlock point, which is designed to be at a safe distance from the docking port. In the neighborhood of the deadlock point, Slider corrects its proximity and heading until its configuration is well-suited to enter the docking phase. The docking maneuver is initiated by the CBF switching mechanism (positive to zero contour), which expands the safe zone to include the final docking configuration. We present an analysis of the Quadratic program defining the CBF filter, and identify two deadlock points (an asymptotically stable point in the vicinity of the docking port and an unstable point diametrically opposite on the CBF boundary). Both the approach and docking phases are validated through experimentation on the Slider platform, in the presence of tether-induced disturbances and drifts induced by the non-ideal floating surface. In the docking phase, the CBF switching condition effectively handles experimental non-idealities and recovers the slider platform from unsafe configurations. The proposed docking strategy caters to the in-plane (3DOF) approach and docking phases of real space docking missions and is scalable to three-dimensional 6DOF operations, in conjunction with controllers that stabilize the attitude and the out-of-plane degree-of-freedom. Link to the video of experimental demonstration: https://youtu.be/eBiWvnKtG7U?si=QFPD-vm11wydyZSd.
{"title":"Switched control barrier functions-based safe docking control strategy for a planar floating platform","authors":"Akshit Saradagi, Viswa Narayanan Sankaranarayanan, Avijit Banerjee, Sumeet Satpute, George Nikolakopoulos","doi":"10.1016/j.conengprac.2025.106274","DOIUrl":"10.1016/j.conengprac.2025.106274","url":null,"abstract":"<div><div>In this article, we present and experimentally validate a safe docking control strategy designed for an experimental planar floating platform, called the Slider. Three degrees-of-freedom (DOF) platforms like the Slider are used extensively in space industry and academia to emulate micro-gravity conditions on Earth, for validating in-plane Guidance, Navigation and Control (GNC) algorithms. The Slider uses an air cushion (induced by air bearings) to levitate on a smooth flat table, thus emulating the in-plane zero-gravity motion of a spacecraft in orbit. The proposed docking control strategy is applicable in the in-plane approach and docking phases of space docking missions, and is based on the Control Barrier Functions (CBF) approach, where a safe set (a Cardioid), capturing the clearance and direction-of-approach constraints, is rendered positively forward invariant. To enable precise and safe docking in the presence of unmodeled dynamics, disturbances induced by the tether and drifts induced by the non-flat floating surface, we present a switching strategy among the zero and positive level sets of a Cardioid function. In the approach phase, the positive contour of the Cardioid function smoothly steers the Slider platform into the neighborhood of a deadlock point, which is designed to be at a safe distance from the docking port. In the neighborhood of the deadlock point, Slider corrects its proximity and heading until its configuration is well-suited to enter the docking phase. The docking maneuver is initiated by the CBF switching mechanism (positive to zero contour), which expands the safe zone to include the final docking configuration. We present an analysis of the Quadratic program defining the CBF filter, and identify two deadlock points (an asymptotically stable point in the vicinity of the docking port and an unstable point diametrically opposite on the CBF boundary). Both the approach and docking phases are validated through experimentation on the Slider platform, in the presence of tether-induced disturbances and drifts induced by the non-ideal floating surface. In the docking phase, the CBF switching condition effectively handles experimental non-idealities and recovers the slider platform from unsafe configurations. The proposed docking strategy caters to the in-plane (3DOF) approach and docking phases of real space docking missions and is scalable to three-dimensional 6DOF operations, in conjunction with controllers that stabilize the attitude and the out-of-plane degree-of-freedom. Link to the video of experimental demonstration: <span><span>https://youtu.be/eBiWvnKtG7U?si=QFPD-vm11wydyZSd</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106274"},"PeriodicalIF":5.4,"publicationDate":"2025-02-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-16DOI: 10.1016/j.conengprac.2025.106279
Fanliang Meng , Hao Yan , Christian Haas , Katharina Schmitz
The Electro-Hydraulic Load Simulator (EHLS) is crucial for testing the performance of aircraft hydraulic actuators. However, challenges such as the actuator’s motion disturbance, unmodeled dynamics, and uncertainty disturbances impact the loading performance. This paper proposes a dual-loop control strategy for the EHLS, combining an open-loop velocity synchronization controller and a robust force backstepping controller, working together in parallel.The open-loop velocity synchronization controller is designed to eliminate the primary disturbances caused by the aircraft’s hydraulic actuator movement. Meanwhile, the robust force backstepping controller addresses the residual disturbances from the synchronized motion, as well as both the matched and mismatched disturbances originating from the EHLS. To enhance synchronization within the EHLS, lag compensation is incorporated for both velocity computation and servo valve spool response. An observer is concurrently implemented to estimate unmeasurable system states and manage both matched and mismatched disturbances. Nonlinear tracking differentiators are then integrated into the backstepping controller design to facilitate the computation of derivatives for the virtual control laws, effectively addressing the ‘explosion of complexity’ issue. Stability of the control system is ensured through Lyapunov’s theory, which accounts for both observation and differentiation errors. Experimental results underscore the effectiveness of the proposed control strategy.
{"title":"Robust backstepping control via tracking differentiator for electro-hydraulic load simulator based on velocity synchronization","authors":"Fanliang Meng , Hao Yan , Christian Haas , Katharina Schmitz","doi":"10.1016/j.conengprac.2025.106279","DOIUrl":"10.1016/j.conengprac.2025.106279","url":null,"abstract":"<div><div>The Electro-Hydraulic Load Simulator (EHLS) is crucial for testing the performance of aircraft hydraulic actuators. However, challenges such as the actuator’s motion disturbance, unmodeled dynamics, and uncertainty disturbances impact the loading performance. This paper proposes a dual-loop control strategy for the EHLS, combining an open-loop velocity synchronization controller and a robust force backstepping controller, working together in parallel.The open-loop velocity synchronization controller is designed to eliminate the primary disturbances caused by the aircraft’s hydraulic actuator movement. Meanwhile, the robust force backstepping controller addresses the residual disturbances from the synchronized motion, as well as both the matched and mismatched disturbances originating from the EHLS. To enhance synchronization within the EHLS, lag compensation is incorporated for both velocity computation and servo valve spool response. An observer is concurrently implemented to estimate unmeasurable system states and manage both matched and mismatched disturbances. Nonlinear tracking differentiators are then integrated into the backstepping controller design to facilitate the computation of derivatives for the virtual control laws, effectively addressing the ‘explosion of complexity’ issue. Stability of the control system is ensured through Lyapunov’s theory, which accounts for both observation and differentiation errors. Experimental results underscore the effectiveness of the proposed control strategy.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106279"},"PeriodicalIF":5.4,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2025-02-15DOI: 10.1016/j.conengprac.2025.106278
Guoyu Zuo, Shuaifeng Dong, Jiyong Zhou, Shuangyue Yu, Min Zhao
Learning-based control strategies can significantly streamline the process of modeling robotic arms and adjusting control parameters, making them widely used in robotic arm motion control. However, the existing learning-based motion control strategies suffer from insufficient feature extraction, resulting in limited prediction accuracy. To address this problem, this paper proposes a robotic arm motion control strategy based on a cascaded feature-enhanced elastic-net broad learning system (CFE-EN-BLS), which improves the trajectory tracking accuracy of robotic arms. Firstly, a motion control strategy of the cascaded feature-enhanced broad learning system (CFE-BLS) is constructed to fully extract data features to improve joint position-tracking accuracy. Secondly, combined with elastic-net regression, a motion control strategy for the robotic arm based on CFE-EN-BLS is designed to reduce feature redundancy. Finally, the learning parameters of the proposed control strategy are constrained by incorporating Lyapunov theory to bolster the convergence of the control strategy. Simulation and experimental results show that the proposed control strategy can effectively extract data features and achieve high-precision trajectory tracking control of the robotic arm. The position tracking mean-squared-error (MSE) and root-mean-squared-error (RMSE) are 0.00174 and 0.04167, respectively, which represent reductions of 74.71% and 49.76% compared to the existing method.
{"title":"Motion control strategy for robotic arm using cascaded feature-enhancement ElasticNet broad learning system","authors":"Guoyu Zuo, Shuaifeng Dong, Jiyong Zhou, Shuangyue Yu, Min Zhao","doi":"10.1016/j.conengprac.2025.106278","DOIUrl":"10.1016/j.conengprac.2025.106278","url":null,"abstract":"<div><div>Learning-based control strategies can significantly streamline the process of modeling robotic arms and adjusting control parameters, making them widely used in robotic arm motion control. However, the existing learning-based motion control strategies suffer from insufficient feature extraction, resulting in limited prediction accuracy. To address this problem, this paper proposes a robotic arm motion control strategy based on a cascaded feature-enhanced elastic-net broad learning system (CFE-EN-BLS), which improves the trajectory tracking accuracy of robotic arms. Firstly, a motion control strategy of the cascaded feature-enhanced broad learning system (CFE-BLS) is constructed to fully extract data features to improve joint position-tracking accuracy. Secondly, combined with elastic-net regression, a motion control strategy for the robotic arm based on CFE-EN-BLS is designed to reduce feature redundancy. Finally, the learning parameters of the proposed control strategy are constrained by incorporating Lyapunov theory to bolster the convergence of the control strategy. Simulation and experimental results show that the proposed control strategy can effectively extract data features and achieve high-precision trajectory tracking control of the robotic arm. The position tracking mean-squared-error (MSE) and root-mean-squared-error (RMSE) are 0.00174<span><math><mrow><mi>r</mi><mi>a</mi><mi>d</mi></mrow></math></span> and 0.04167<span><math><mrow><mi>r</mi><mi>a</mi><mi>d</mi></mrow></math></span>, respectively, which represent reductions of 74.71% and 49.76% compared to the existing method.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106278"},"PeriodicalIF":5.4,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422536","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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 : 2025-02-15DOI: 10.1016/j.conengprac.2025.106277
Yanqi Lu, Weiran Yao
This paper investigates how to maintain control accuracy in cable-driven parallel robots (CDPRs) when faced with actuator faults and lumped uncertainties. An active fault-tolerant hybrid control (AFTHC) scheme integrated with deep reinforcement learning (DRL) is proposed to address the issue. The AFTHC scheme includes a tracking controller, a fixed-time sliding mode observer for fault detection, and a DRL-based fault compensation controller. The fault compensation controller is activated upon detecting an actuator fault to enhance the system stability and recover the control performance. Simulations and experiments are carried out to verify the effectiveness and superiority of the AFTHC scheme. The results indicate that the AFTHC scheme effectively enhances fault tolerance and rapidly recovers control accuracy.
{"title":"Active fault-tolerant hybrid control integrated with reinforcement learning application to cable-driven parallel robots","authors":"Yanqi Lu, Weiran Yao","doi":"10.1016/j.conengprac.2025.106277","DOIUrl":"10.1016/j.conengprac.2025.106277","url":null,"abstract":"<div><div>This paper investigates how to maintain control accuracy in cable-driven parallel robots (CDPRs) when faced with actuator faults and lumped uncertainties. An active fault-tolerant hybrid control (AFTHC) scheme integrated with deep reinforcement learning (DRL) is proposed to address the issue. The AFTHC scheme includes a tracking controller, a fixed-time sliding mode observer for fault detection, and a DRL-based fault compensation controller. The fault compensation controller is activated upon detecting an actuator fault to enhance the system stability and recover the control performance. Simulations and experiments are carried out to verify the effectiveness and superiority of the AFTHC scheme. The results indicate that the AFTHC scheme effectively enhances fault tolerance and rapidly recovers control accuracy.</div></div>","PeriodicalId":50615,"journal":{"name":"Control Engineering Practice","volume":"158 ","pages":"Article 106277"},"PeriodicalIF":5.4,"publicationDate":"2025-02-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143422553","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"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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