Pub Date : 2024-07-30DOI: 10.1109/TCST.2024.3430708
Shuang Feng;Ricardo de Castro;Iman Ebrahimi
This article proposes a control barrier function (CBF) approach for fast charging and discharging of batteries under temperature, state of charge (SoC), and terminal voltage constraints. To improve numerical efficiency, we derive a cascade CBF formulation, which divides this safety problem into multiple layers that are easier to formulate and implement. The proposed algorithm exhibits a computational speed that is seven times faster than the model predictive control (MPC) and 3.6 times faster than the traditional single-layer (central) CBF. In the charging scenario, experimental results indicate that the proposed algorithm reduces charging time by 20% in comparison to traditional constant current, constant voltage (CC-CV) methods without violating electro-thermal safety constraints. The discharging experiment illustrates that the cascade CBF effectively limits the battery’s performance to ensure compliance with safety constraints.
{"title":"Safe Battery Control Using Cascade-Control-Barrier Functions","authors":"Shuang Feng;Ricardo de Castro;Iman Ebrahimi","doi":"10.1109/TCST.2024.3430708","DOIUrl":"10.1109/TCST.2024.3430708","url":null,"abstract":"This article proposes a control barrier function (CBF) approach for fast charging and discharging of batteries under temperature, state of charge (SoC), and terminal voltage constraints. To improve numerical efficiency, we derive a cascade CBF formulation, which divides this safety problem into multiple layers that are easier to formulate and implement. The proposed algorithm exhibits a computational speed that is seven times faster than the model predictive control (MPC) and 3.6 times faster than the traditional single-layer (central) CBF. In the charging scenario, experimental results indicate that the proposed algorithm reduces charging time by 20% in comparison to traditional constant current, constant voltage (CC-CV) methods without violating electro-thermal safety constraints. The discharging experiment illustrates that the cascade CBF effectively limits the battery’s performance to ensure compliance with safety constraints.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2344-2358"},"PeriodicalIF":4.9,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866698","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 : 2024-07-30DOI: 10.1109/TCST.2024.3429908
Jianping Lin;Gray C. Thomas;Nikhil V. Divekar;Vamsi Peddinti;Robert D. Gregg
Various backdrivable lower limb exoskeletons have demonstrated the electromechanical capability to assist volitional motions of able-bodied users and people with mild to moderate gait disorders, but there does not exist a control framework that can be deployed on any joint(s) to assist any activity of daily life in a provably stable manner. This article presents the modular, multitask optimal energy shaping (M-TOES) framework, which uses a convex, data-driven optimization to train an analytical control model to instantaneously determine assistive joint torques across activities for any lower limb exoskeleton joint configuration. The presented modular energy basis is sufficiently descriptive to fit normative human joint torques (given normative feedback from signals available to a given joint configuration) across sit-stand transitions, stair ascent/descent, ramp ascent/descent, and level walking at different speeds. We evaluated controllers for four joint configurations (unilateral/bilateral and hip/knee) of the modular backdrivable lower limb unloading exoskeleton (M-BLUE) exoskeleton on eight able-bodied users navigating a multiactivity circuit. The two unilateral conditions significantly lowered overall muscle activation across all tasks and subjects (p $mathbf {lt }$ 0.001). In contrast, bilateral configurations had a minimal impact, possibly attributable to device weight and physical constraints.
{"title":"A Modular Framework for Task-Agnostic, Energy Shaping Control of Lower Limb Exoskeletons","authors":"Jianping Lin;Gray C. Thomas;Nikhil V. Divekar;Vamsi Peddinti;Robert D. Gregg","doi":"10.1109/TCST.2024.3429908","DOIUrl":"10.1109/TCST.2024.3429908","url":null,"abstract":"Various backdrivable lower limb exoskeletons have demonstrated the electromechanical capability to assist volitional motions of able-bodied users and people with mild to moderate gait disorders, but there does not exist a control framework that can be deployed on any joint(s) to assist any activity of daily life in a provably stable manner. This article presents the modular, multitask optimal energy shaping (M-TOES) framework, which uses a convex, data-driven optimization to train an analytical control model to instantaneously determine assistive joint torques across activities for any lower limb exoskeleton joint configuration. The presented modular energy basis is sufficiently descriptive to fit normative human joint torques (given normative feedback from signals available to a given joint configuration) across sit-stand transitions, stair ascent/descent, ramp ascent/descent, and level walking at different speeds. We evaluated controllers for four joint configurations (unilateral/bilateral and hip/knee) of the modular backdrivable lower limb unloading exoskeleton (M-BLUE) exoskeleton on eight able-bodied users navigating a multiactivity circuit. The two unilateral conditions significantly lowered overall muscle activation across all tasks and subjects (p\u0000<inline-formula> <tex-math>$mathbf {lt }$ </tex-math></inline-formula>\u00000.001). In contrast, bilateral configurations had a minimal impact, possibly attributable to device weight and physical constraints.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2359-2375"},"PeriodicalIF":4.9,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866700","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 : 2024-07-30DOI: 10.1109/TCST.2024.3430128
Gian Carlo Maffettone;Lorenzo Liguori;Eduardo Palermo;Mario Di Bernardo;Maurizio Porfiri
Many new methodologies for the control of large-scale multiagent systems are based on macroscopic representations of the system dynamics, in the form of continuum approximations of large ensembles. These techniques, developed in the limit case of an infinite number of agents, are usually validated only through numerical simulations. Here, we introduce a mixed reality setup for testing swarm robotics techniques, focusing on the macroscopic collective motion of robotic swarms. This hybrid apparatus combines real differential drive robots and virtual agents to create a heterogeneous swarm of tunable size. We also extend continuification-based control methods for swarms to higher dimensions and experimentally assess their validity in the new platform. Our study demonstrates the effectiveness of the platform for conducting large-scale swarm robotics experiments, and it contributes new theoretical insights into control algorithms exploiting continuification approaches.
{"title":"Mixed Reality Environment and High-Dimensional Continuification Control for Swarm Robotics","authors":"Gian Carlo Maffettone;Lorenzo Liguori;Eduardo Palermo;Mario Di Bernardo;Maurizio Porfiri","doi":"10.1109/TCST.2024.3430128","DOIUrl":"10.1109/TCST.2024.3430128","url":null,"abstract":"Many new methodologies for the control of large-scale multiagent systems are based on macroscopic representations of the system dynamics, in the form of continuum approximations of large ensembles. These techniques, developed in the limit case of an infinite number of agents, are usually validated only through numerical simulations. Here, we introduce a mixed reality setup for testing swarm robotics techniques, focusing on the macroscopic collective motion of robotic swarms. This hybrid apparatus combines real differential drive robots and virtual agents to create a heterogeneous swarm of tunable size. We also extend continuification-based control methods for swarms to higher dimensions and experimentally assess their validity in the new platform. Our study demonstrates the effectiveness of the platform for conducting large-scale swarm robotics experiments, and it contributes new theoretical insights into control algorithms exploiting continuification approaches.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2484-2491"},"PeriodicalIF":4.9,"publicationDate":"2024-07-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10614946","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141866699","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 : 2024-07-26DOI: 10.1109/TCST.2024.3430130
Zeyu Guo;Jun Yang;Shihua Li;Zuo Wang
This article presents a position-based visual servo approach to allow a quadrotor to visually land on a moving platform, addressing perception delay and disturbances using only sampled-data output feedback. Without the platform’s model prior, the relative position of the quadrotor and the platform is determined by capturing the AprilTag on the platform by an onboard camera. The limitation in the camera’s sampling frequency yields only discrete output with time delay, emphasizing the requirement for a sampled-data method, since continuous system theory is not applicable in this scenario. In addition, disturbances arising from the unknown platform motion, wind resistance, and attitude tracking errors are also unavoidable. To mitigate these issues, a sampled-data time-delay extended state observer (TDESO)-based predictor is developed, capable of actively predicting the current states and disturbances. Using these predictions, a composite sampled-data controller is devised that incorporates disturbance feedforward compensation, thus enhancing the system’s robustness against disturbances. Rigorous Lyapunov analysis is provided, offering a guarantee that the states of the sampled-data control system converge asymptotically to a bounded region, even in the presence of perception delay and disturbances. The effectiveness and practicality of the proposed algorithm are supported by simulations and experimental results.
{"title":"Robust Visual Landing Control of Quadrotor on a Moving Platform: A Sampled-Data Approach With Delayed Output and Disturbances","authors":"Zeyu Guo;Jun Yang;Shihua Li;Zuo Wang","doi":"10.1109/TCST.2024.3430130","DOIUrl":"10.1109/TCST.2024.3430130","url":null,"abstract":"This article presents a position-based visual servo approach to allow a quadrotor to visually land on a moving platform, addressing perception delay and disturbances using only sampled-data output feedback. Without the platform’s model prior, the relative position of the quadrotor and the platform is determined by capturing the AprilTag on the platform by an onboard camera. The limitation in the camera’s sampling frequency yields only discrete output with time delay, emphasizing the requirement for a sampled-data method, since continuous system theory is not applicable in this scenario. In addition, disturbances arising from the unknown platform motion, wind resistance, and attitude tracking errors are also unavoidable. To mitigate these issues, a sampled-data time-delay extended state observer (TDESO)-based predictor is developed, capable of actively predicting the current states and disturbances. Using these predictions, a composite sampled-data controller is devised that incorporates disturbance feedforward compensation, thus enhancing the system’s robustness against disturbances. Rigorous Lyapunov analysis is provided, offering a guarantee that the states of the sampled-data control system converge asymptotically to a bounded region, even in the presence of perception delay and disturbances. The effectiveness and practicality of the proposed algorithm are supported by simulations and experimental results.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2283-2297"},"PeriodicalIF":4.9,"publicationDate":"2024-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141783415","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 : 2024-07-18DOI: 10.1109/TCST.2024.3425211
Ahmed M. Elsergany;Mamoun F. Abdel-Hafez;Mohammad A. Jaradat
This article presents a novel direct filtering approach for loosely coupled global positioning system (GPS) and inertial navigation system (INS) integration. The proposed model is established based on utilizing the full nonlinear INS state equations in a direct configuration while including vehicle orientation through a unit-quaternion representation. A novel augmented quaternion unscented Kalman filter (AQUKF) is developed and proposed to address the direct nonlinear estimation of vehicle states for outdoor vehicle localization while preserving the non-Euclidean geometry of unit-quaternions. The proposed filter is experimentally validated under full GPS coverage as well as prolonged GPS outages. Results obtained in this article show that the proposed filter outperforms other existing solutions in various experimental testing scenarios.
本文针对松散耦合的全球定位系统（GPS）和惯性导航系统（INS）集成提出了一种新颖的直接滤波方法。所提议的模型是在直接配置中利用完整的非线性 INS 状态方程的基础上建立的，同时通过单位四元数表示法将车辆方位包括在内。开发并提出了一种新颖的增强四元数无特征卡尔曼滤波器（AQUKF），用于解决室外车辆定位的车辆状态直接非线性估计问题，同时保留了单位四元数的非欧几里得几何特性。实验验证了所提出的滤波器在 GPS 全面覆盖以及 GPS 长期中断的情况下的有效性。本文获得的结果表明，在各种实验测试场景中，所提出的滤波器优于其他现有解决方案。
{"title":"Novel Augmented Quaternion UKF for Enhanced Loosely Coupled GPS/INS Integration","authors":"Ahmed M. Elsergany;Mamoun F. Abdel-Hafez;Mohammad A. Jaradat","doi":"10.1109/TCST.2024.3425211","DOIUrl":"10.1109/TCST.2024.3425211","url":null,"abstract":"This article presents a novel direct filtering approach for loosely coupled global positioning system (GPS) and inertial navigation system (INS) integration. The proposed model is established based on utilizing the full nonlinear INS state equations in a direct configuration while including vehicle orientation through a unit-quaternion representation. A novel augmented quaternion unscented Kalman filter (AQUKF) is developed and proposed to address the direct nonlinear estimation of vehicle states for outdoor vehicle localization while preserving the non-Euclidean geometry of unit-quaternions. The proposed filter is experimentally validated under full GPS coverage as well as prolonged GPS outages. Results obtained in this article show that the proposed filter outperforms other existing solutions in various experimental testing scenarios.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2321-2331"},"PeriodicalIF":4.9,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10602523","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739633","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 : 2024-07-18DOI: 10.1109/TCST.2024.3425210
Mojtaba Kaheni;Alessandro V. Papadopoulos;Elio Usai;Mauro Franceschelli
This manuscript presents a novel distributed greedy framework applicable to a network of thermostatically controlled loads (TCLs) to desynchronize the network’s aggregated power consumption. Compared to the existing literature, our proposed framework offers two distinct novelties. First, our proposed algorithm relaxes the restrictive assumptions associated with the communication graph among TCLs. To elaborate, our algorithm only requires a connected graph to execute control, a condition less demanding than its counterpart algorithms that mandate a star architecture, K-regular graphs, or undirected connected graphs. Second, a significant novel feature is the relaxation of the obligation to share private information, such as each unit’s local power consumption and appliance temperatures, either with a central coordinator or neighboring TCLs. The findings presented in this brief are validated through simulations conducted over a network comprising 1000 TCLs.
{"title":"A Privacy-Preserving Distributed Greedy Framework to Desynchronize Power Consumption in a Network of Thermostatically Controlled Loads","authors":"Mojtaba Kaheni;Alessandro V. Papadopoulos;Elio Usai;Mauro Franceschelli","doi":"10.1109/TCST.2024.3425210","DOIUrl":"10.1109/TCST.2024.3425210","url":null,"abstract":"This manuscript presents a novel distributed greedy framework applicable to a network of thermostatically controlled loads (TCLs) to desynchronize the network’s aggregated power consumption. Compared to the existing literature, our proposed framework offers two distinct novelties. First, our proposed algorithm relaxes the restrictive assumptions associated with the communication graph among TCLs. To elaborate, our algorithm only requires a connected graph to execute control, a condition less demanding than its counterpart algorithms that mandate a star architecture, K-regular graphs, or undirected connected graphs. Second, a significant novel feature is the relaxation of the obligation to share private information, such as each unit’s local power consumption and appliance temperatures, either with a central coordinator or neighboring TCLs. The findings presented in this brief are validated through simulations conducted over a network comprising 1000 TCLs.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2476-2483"},"PeriodicalIF":4.9,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10604709","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739634","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}
{"title":"Active Exploration in Iterative Gaussian Process Regression for Uncertainty Modeling in Autonomous Racing","authors":"Tommaso Benciolini, Chen Tang, Marion Leibold, Catherine Weaver, Masayoshi Tomizuka, Wei Zhan","doi":"10.1109/tcst.2024.3423630","DOIUrl":"https://doi.org/10.1109/tcst.2024.3423630","url":null,"abstract":"","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"82 1","pages":""},"PeriodicalIF":4.8,"publicationDate":"2024-07-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739569","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 : 2024-07-17DOI: 10.1109/TCST.2024.3422048
Mahmoud Hussein;Youmin Zhang;Zhaoheng Liu
This brief addresses the problem of fault-tolerant cooperative control (FTCC) for a group of car-like vehicles experiencing actuator faults. The main feature of this study is the transmission of vehicle’s state information via fading channels. It is challenging to compensate for actuator faults and maintain vehicle’s stability in the presence of unreliable communication links. To cope with such fault conditions, this work introduces an integral terminal sliding mode control developed by means of received faded neighborhood state information. The fading channel’s effect and the nonlinearity of vehicle dynamics are carefully analyzed by providing rigorous proofs with the Lyapunov stability theorem. In this study, the settling time function relies on design parameters rather than the initial states, which is essential for real applications. The effectiveness of the proposed controller is validated in a real system using the latest Quanser self-driving car (QCar) platform.
{"title":"Fault-Tolerant Cooperative Control Design for Car-Like Vehicles Subject to Actuator Faults and Fading Channels","authors":"Mahmoud Hussein;Youmin Zhang;Zhaoheng Liu","doi":"10.1109/TCST.2024.3422048","DOIUrl":"10.1109/TCST.2024.3422048","url":null,"abstract":"This brief addresses the problem of fault-tolerant cooperative control (FTCC) for a group of car-like vehicles experiencing actuator faults. The main feature of this study is the transmission of vehicle’s state information via fading channels. It is challenging to compensate for actuator faults and maintain vehicle’s stability in the presence of unreliable communication links. To cope with such fault conditions, this work introduces an integral terminal sliding mode control developed by means of received faded neighborhood state information. The fading channel’s effect and the nonlinearity of vehicle dynamics are carefully analyzed by providing rigorous proofs with the Lyapunov stability theorem. In this study, the settling time function relies on design parameters rather than the initial states, which is essential for real applications. The effectiveness of the proposed controller is validated in a real system using the latest Quanser self-driving car (QCar) platform.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2452-2459"},"PeriodicalIF":4.9,"publicationDate":"2024-07-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141739635","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 : 2024-07-11DOI: 10.1109/TCST.2024.3422372
Cary L. Butler;Reid D. Smith;Andrew G. Alleyne
As electrified aircraft are becoming more prominent, new energy management strategies are needed to fully leverage their capabilities to perform more complex missions and to do so safely. Nonconvex constraints, multitimescale dynamics, and uncertainty introduce challenges in the way of guaranteeing safe powertrain operation using existing methods. This work seeks to address these challenges using a novel application of sampling-based planning methods to plan the operation of a hybrid unmanned aerial vehicle (UAV) powertrain. Known for their computational efficiency, these sampling-based methods can rapidly react to changing mission information. A two-stage method is introduced, which manages multiple time scales using rapidly exploring random tree (RRT)-based algorithms for long-term planning and robust model predictive control (RMPC) for short-term execution of mission plans with guaranteed tracking error bounds. An experimentally validated case study demonstrates the implementation of the two-stage method using RRT-based algorithms. Rapid planning times ( $gt 100times $ faster than real time) enable replanning online to react to changing mission specifications. Robust tracking control guarantees that the UAV powertrain is safely operated in the presence of complex, uncertain constraints.
{"title":"Sampling-Based Planning for Guaranteed Safe Energy Management of Hybrid UAV Powertrain Under Complex, Uncertain Constraints","authors":"Cary L. Butler;Reid D. Smith;Andrew G. Alleyne","doi":"10.1109/TCST.2024.3422372","DOIUrl":"10.1109/TCST.2024.3422372","url":null,"abstract":"As electrified aircraft are becoming more prominent, new energy management strategies are needed to fully leverage their capabilities to perform more complex missions and to do so safely. Nonconvex constraints, multitimescale dynamics, and uncertainty introduce challenges in the way of guaranteeing safe powertrain operation using existing methods. This work seeks to address these challenges using a novel application of sampling-based planning methods to plan the operation of a hybrid unmanned aerial vehicle (UAV) powertrain. Known for their computational efficiency, these sampling-based methods can rapidly react to changing mission information. A two-stage method is introduced, which manages multiple time scales using rapidly exploring random tree (RRT)-based algorithms for long-term planning and robust model predictive control (RMPC) for short-term execution of mission plans with guaranteed tracking error bounds. An experimentally validated case study demonstrates the implementation of the two-stage method using RRT-based algorithms. Rapid planning times (\u0000<inline-formula> <tex-math>$gt 100times $ </tex-math></inline-formula>\u0000 faster than real time) enable replanning online to react to changing mission specifications. Robust tracking control guarantees that the UAV powertrain is safely operated in the presence of complex, uncertain constraints.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2267-2282"},"PeriodicalIF":4.9,"publicationDate":"2024-07-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141613521","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 : 2024-07-09DOI: 10.1109/TCST.2024.3423548
Ruiqing Zhang;Jingkang Xia;Junjie Ma;Deqing Huang;Xin Zhang;Yanan Li
To achieve rapid and flexible deployment of robots in the finishing process of small batch workpieces, this article proposes a framework for human-robot interactive (HRI) skill learning and correction based on improved dynamic time warping iterative learning control (DTW-ILC). First, we incorporate Gaussian mixture model (GMM) with DTW-ILC approach to enable the robot to learn polishing skills from human demonstration and interaction. Second, to ensure accurate force tracking under the condition of varying polishing feed speed, we propose an iterative force tracking method based on DTW-ILC and impedance control. Notably, we propose to iteratively estimate the polishing stiffness and incorporate it into the path updating law, resulting in simplified parameter settings and faster error convergence compared with traditional iterative learning control (ILC) methods with fixed parameters. A polishing experiment is carried out to prove the effectiveness of the proposed framework and method.
{"title":"Human-Robot Interactive Skill Learning and Correction for Polishing Based on Dynamic Time Warping Iterative Learning Control","authors":"Ruiqing Zhang;Jingkang Xia;Junjie Ma;Deqing Huang;Xin Zhang;Yanan Li","doi":"10.1109/TCST.2024.3423548","DOIUrl":"10.1109/TCST.2024.3423548","url":null,"abstract":"To achieve rapid and flexible deployment of robots in the finishing process of small batch workpieces, this article proposes a framework for human-robot interactive (HRI) skill learning and correction based on improved dynamic time warping iterative learning control (DTW-ILC). First, we incorporate Gaussian mixture model (GMM) with DTW-ILC approach to enable the robot to learn polishing skills from human demonstration and interaction. Second, to ensure accurate force tracking under the condition of varying polishing feed speed, we propose an iterative force tracking method based on DTW-ILC and impedance control. Notably, we propose to iteratively estimate the polishing stiffness and incorporate it into the path updating law, resulting in simplified parameter settings and faster error convergence compared with traditional iterative learning control (ILC) methods with fixed parameters. A polishing experiment is carried out to prove the effectiveness of the proposed framework and method.","PeriodicalId":13103,"journal":{"name":"IEEE Transactions on Control Systems Technology","volume":"32 6","pages":"2310-2320"},"PeriodicalIF":4.9,"publicationDate":"2024-07-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141568392","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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