Pub Date : 2025-10-01Epub Date: 2025-06-07DOI: 10.1016/j.mechatronics.2025.103353
Michael Pumphrey , Almuatazbellah M. Boker , Mohammad Al Saaideh , Natheer Alatawneh , Yazan M. Al-Rawashdeh , Khaled Aljanaideh , Mohammad Al Janaideh
A novel approach for modeling the nonlinear dynamics of cable slabs using Koopman operator theory is presented. Cable slab dynamics are a critical challenge in precision motion systems, as the cables can induce undesired vibrations and disturbances on motion stages. To address this, a higher-dimensional state-space model with nonlinear observable functions is developed to approximate the cable slab dynamics. The proposed model achieves a prediction error within % over the specified motion range and demonstrates robustness in predicting untrained, randomized, acyclic cable slab motions. A systematic evaluation of various observable functions was conducted to minimize the modeling errors, leading to an optimized model with fractional-order exponents. When compared with a neural network-based state-space model (NN-SS), the Koopman approach demonstrated faster training and better performance. For force prediction, the Koopman approach achieved a reduction of three-quarters in maximum error when compared with the NN-SS method. This work offers a concise and experimentally validated analytical framework specifically for developing accurate predictive models of nonlinear cable slab dynamics.
{"title":"Modeling and prediction of nonlinear cable slab dynamics using Koopman operators","authors":"Michael Pumphrey , Almuatazbellah M. Boker , Mohammad Al Saaideh , Natheer Alatawneh , Yazan M. Al-Rawashdeh , Khaled Aljanaideh , Mohammad Al Janaideh","doi":"10.1016/j.mechatronics.2025.103353","DOIUrl":"10.1016/j.mechatronics.2025.103353","url":null,"abstract":"<div><div>A novel approach for modeling the nonlinear dynamics of cable slabs using Koopman operator theory is presented. Cable slab dynamics are a critical challenge in precision motion systems, as the cables can induce undesired vibrations and disturbances on motion stages. To address this, a higher-dimensional state-space model with nonlinear observable functions is developed to approximate the cable slab dynamics. The proposed model achieves a prediction error within <span><math><mrow><mo>∼</mo><mn>1</mn></mrow></math></span>% over the specified motion range and demonstrates robustness in predicting untrained, randomized, acyclic cable slab motions. A systematic evaluation of various observable functions was conducted to minimize the modeling errors, leading to an optimized model with fractional-order exponents. When compared with a neural network-based state-space model (NN-SS), the Koopman approach demonstrated faster training and better performance. For force prediction, the Koopman approach achieved a reduction of three-quarters in maximum error when compared with the NN-SS method. This work offers a concise and experimentally validated analytical framework specifically for developing accurate predictive models of nonlinear cable slab dynamics.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103353"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144230252","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-06-14DOI: 10.1016/j.mechatronics.2025.103358
Bruno S.S. Pereira , Tito L.M. Santos , Andre G.S. Conceicao
This paper proposes a new robust feedback-linearization MPC for a class of Unmanned Ground Vehicles. A robust MPC for trajectory tracking with an artificial target is combined with a suitable constraint mapping to ensure robust constraint satisfaction and recursive feasibility despite the effect of bounded disturbances. The artificial reference provides a potentially enlarged domain of attraction, and an analytical target modification is used to achieve the convergence of the tracking error to a minimal robust positively invariant set. The feedback-linearization trade-off concerning the transformed constraints is also analyzed. A case study demonstrating the control strategy’s performance is presented using the Clearpath Husky A200 UGV and the OptiTrack motion capture system.
{"title":"A robust feedback-linearization MPC with artificial target for UGVs","authors":"Bruno S.S. Pereira , Tito L.M. Santos , Andre G.S. Conceicao","doi":"10.1016/j.mechatronics.2025.103358","DOIUrl":"10.1016/j.mechatronics.2025.103358","url":null,"abstract":"<div><div>This paper proposes a new robust feedback-linearization MPC for a class of Unmanned Ground Vehicles. A robust MPC for trajectory tracking with an artificial target is combined with a suitable constraint mapping to ensure robust constraint satisfaction and recursive feasibility despite the effect of bounded disturbances. The artificial reference provides a potentially enlarged domain of attraction, and an analytical target modification is used to achieve the convergence of the tracking error to a minimal robust positively invariant set. The feedback-linearization trade-off concerning the transformed constraints is also analyzed. A case study demonstrating the control strategy’s performance is presented using the Clearpath Husky A200 UGV and the OptiTrack motion capture system.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103358"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144289012","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-07-16DOI: 10.1016/j.mechatronics.2025.103388
Gunwoo An, Jaeyoung Kang
Six-wheeled mobile robots (6-WMRs) equipped with rocker-bogie suspension systems are widely used for planetary exploration and search-and-rescue tasks due to their excellent terrain adaptability. However, conventional rocker-bogie-based systems present critical limitations, including tire slip caused by the absence of steering mechanisms, lack of camber control, and increased structural complexity from added components. To overcome these issues, this study introduces the GFRP Beam Spring Rocker-arm Suspension (GBSRS), which integrates a rocker-arm structure with a Glass Fiber Reinforced Polymer (GFRP) beam spring. An independent steering system based on Ackermann geometry is applied to minimize tire slip, while the torsional and vertical compliance of the GFRP beam enables passive camber variation and vibration damping without the use of additional actuators or complex linkages. A 7-degree-of-freedom (7-DOF) vibration model is developed to simulate dynamic behavior, and a bend-twist coupling analysis is conducted to calculate beam deformation and camber response. The design is further optimized by applying Derringer’s desirability function to key parameters such as beam thickness, damper position, and camber adjuster angle. Simulation and experimental results—including tests over single obstacles and rough terrain—demonstrate that the GBSRS reduces RMS acceleration by up to 16.3% and peak acceleration by up to 40.6% compared to conventional solid-arm systems. These results confirm that the GBSRS effectively improves vibration isolation and camber adaptability while maintaining structural simplicity, offering a practical suspension solution for 6-WMRs in challenging environments.
{"title":"Novel design of GFRP beam spring rocker-arm suspension for 6-wheeled mobile robots","authors":"Gunwoo An, Jaeyoung Kang","doi":"10.1016/j.mechatronics.2025.103388","DOIUrl":"10.1016/j.mechatronics.2025.103388","url":null,"abstract":"<div><div>Six-wheeled mobile robots (6-WMRs) equipped with rocker-bogie suspension systems are widely used for planetary exploration and search-and-rescue tasks due to their excellent terrain adaptability. However, conventional rocker-bogie-based systems present critical limitations, including tire slip caused by the absence of steering mechanisms, lack of camber control, and increased structural complexity from added components. To overcome these issues, this study introduces the GFRP Beam Spring Rocker-arm Suspension (GBSRS), which integrates a rocker-arm structure with a Glass Fiber Reinforced Polymer (GFRP) beam spring. An independent steering system based on Ackermann geometry is applied to minimize tire slip, while the torsional and vertical compliance of the GFRP beam enables passive camber variation and vibration damping without the use of additional actuators or complex linkages. A 7-degree-of-freedom (7-DOF) vibration model is developed to simulate dynamic behavior, and a bend-twist coupling analysis is conducted to calculate beam deformation and camber response. The design is further optimized by applying Derringer’s desirability function to key parameters such as beam thickness, damper position, and camber adjuster angle. Simulation and experimental results—including tests over single obstacles and rough terrain—demonstrate that the GBSRS reduces RMS acceleration by up to 16.3% and peak acceleration by up to 40.6% compared to conventional solid-arm systems. These results confirm that the GBSRS effectively improves vibration isolation and camber adaptability while maintaining structural simplicity, offering a practical suspension solution for 6-WMRs in challenging environments.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103388"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144634104","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To reduce residual vibration with accurate positioning for a flexible hydraulic manipulator, this paper proposes a dual-impulse vibration suppression method to implement concrete pumping tasks. Through sealing up the load-bearing chamber and allow fluid exchange in the non-bearing chamber by individual metering control (IMC), a valve-based volume control method without position sensors is proposed to replace direct positioning control of the end point. Besides, a dual-impulse valve controller is designed for making an online tradeoff between vibration suppression and accurate positioning under a specific pumping posture. Based on only pressure feedback, the amplitude and the time width of the two impulses are determined via system identification in advance and vibration prediction in real-time. Experimental tests are carried out using a 13m-length hydraulic manipulator under three different postures. The test results show that the vibration caused by disturbance can be effectively reduced using the proposed method, and more importantly the position of the end point can be maintained accurately.
{"title":"Residual vibration suppression of large-size flexible hydraulic manipulator under external disturbance with accurate positioning","authors":"Min Cheng , Xin Zhang , Ruqi Ding , Junhui Zhang , Bing Xu","doi":"10.1016/j.mechatronics.2025.103355","DOIUrl":"10.1016/j.mechatronics.2025.103355","url":null,"abstract":"<div><div>To reduce residual vibration with accurate positioning for a flexible hydraulic manipulator, this paper proposes a dual-impulse vibration suppression method to implement concrete pumping tasks. Through sealing up the load-bearing chamber and allow fluid exchange in the non-bearing chamber by individual metering control (IMC), a valve-based volume control method without position sensors is proposed to replace direct positioning control of the end point. Besides, a dual-impulse valve controller is designed for making an online tradeoff between vibration suppression and accurate positioning under a specific pumping posture. Based on only pressure feedback, the amplitude and the time width of the two impulses are determined via system identification in advance and vibration prediction in real-time. Experimental tests are carried out using a 13m-length hydraulic manipulator under three different postures. The test results show that the vibration caused by disturbance can be effectively reduced using the proposed method, and more importantly the position of the end point can be maintained accurately.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103355"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144213503","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-07-21DOI: 10.1016/j.mechatronics.2025.103386
Mario Rosenfelder , Hendrik Carius , Markus Herrmann-Wicklmayr , Peter Eberhard , Kathrin Flaßkamp , Henrik Ebel
In real-world applications of mobile robots, collision avoidance is of critical importance. Typically, global motion planning in constrained environments is addressed through high-level control schemes. However, additionally integrating local collision avoidance into robot motion control offers significant advantages. For instance, it reduces the reliance on heuristics, conservatism, and complexity from additional hyperparameters that can arise from a two-stage approach separating local collision avoidance and control. Moreover, using model predictive control (MPC), a robot’s full potential can be harnessed by considering jointly local collision avoidance, the robot’s dynamics including dynamic constraints (like nonholonomic constraints), and actuation constraints. In this context, the present paper focuses on local obstacle avoidance for wheeled mobile robots, where both the robot’s and obstacles’ occupied volumes are modeled as ellipsoids of arbitrary orientation. To this end, a computationally efficient overlap test, which works for arbitrary ellipsoids, is conducted and novelly integrated into the MPC framework. We propose a particularly efficient implementation tailored to robots moving in the plane. The functionality of the proposed obstacle-avoiding MPC is demonstrated for two exemplary types of kinematics by means of simulations. A hardware experiment using a real-world wheeled mobile robot shows transferability to reality and real-time applicability. Moreover, numerical experiments show that, due to the approach’s general nature, it can be directly applied to dynamic situations like moving obstacles. The general computational approach to ellipsoidal obstacle avoidance can also be applied to other robotic systems and vehicles as well as three-dimensional scenarios.
{"title":"Efficient avoidance of ellipsoidal obstacles with model predictive control for mobile robots and vehicles","authors":"Mario Rosenfelder , Hendrik Carius , Markus Herrmann-Wicklmayr , Peter Eberhard , Kathrin Flaßkamp , Henrik Ebel","doi":"10.1016/j.mechatronics.2025.103386","DOIUrl":"10.1016/j.mechatronics.2025.103386","url":null,"abstract":"<div><div>In real-world applications of mobile robots, collision avoidance is of critical importance. Typically, global motion planning in constrained environments is addressed through high-level control schemes. However, additionally integrating local collision avoidance into robot motion control offers significant advantages. For instance, it reduces the reliance on heuristics, conservatism, and complexity from additional hyperparameters that can arise from a two-stage approach separating local collision avoidance and control. Moreover, using model predictive control (MPC), a robot’s full potential can be harnessed by considering jointly local collision avoidance, the robot’s dynamics including dynamic constraints (like nonholonomic constraints), and actuation constraints. In this context, the present paper focuses on local obstacle avoidance for wheeled mobile robots, where both the robot’s and obstacles’ occupied volumes are modeled as ellipsoids of arbitrary orientation. To this end, a computationally efficient overlap test, which works for arbitrary ellipsoids, is conducted and novelly integrated into the MPC framework. We propose a particularly efficient implementation tailored to robots moving in the plane. The functionality of the proposed obstacle-avoiding MPC is demonstrated for two exemplary types of kinematics by means of simulations. A hardware experiment using a real-world wheeled mobile robot shows transferability to reality and real-time applicability. Moreover, numerical experiments show that, due to the approach’s general nature, it can be directly applied to dynamic situations like moving obstacles. The general computational approach to ellipsoidal obstacle avoidance can also be applied to other robotic systems and vehicles as well as three-dimensional scenarios.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103386"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144672214","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-07-31DOI: 10.1016/j.mechatronics.2025.103390
Yalun Wen, Prabhakar R. Pagilla
This paper develops a novel pose control framework for robot manipulators traversing a given spatial curve with constant speed. The key to this framework is the use of a Rotation Minimizing Frame (RMF) for path generation and control, enhancing motion stability for paths with significant curvature and inflection points, and reducing kinematic twist. Using the governing equations based on the RMF, we first develop the reference velocity and acceleration along the path that is consistent with the RMF. Employing tools from differential geometry, we derive a path following position control law by projecting the robot translation states onto the RMF. From an analytical description of the relative orientation error kinematics, we derive a stabilizing orientation controller by utilizing the Modified Rodrigues Parameters to avoid the unwinding problem. The proposed framework is applicable to both torque-controlled and velocity-controlled robots, and we provide results from real-time experiments on both types of robots to verify the effectiveness and advantages of the proposed approach.
{"title":"A novel pose control framework and its implementation for robot manipulators following constrained spatial paths","authors":"Yalun Wen, Prabhakar R. Pagilla","doi":"10.1016/j.mechatronics.2025.103390","DOIUrl":"10.1016/j.mechatronics.2025.103390","url":null,"abstract":"<div><div>This paper develops a novel pose control framework for robot manipulators traversing a given spatial curve with constant speed. The key to this framework is the use of a Rotation Minimizing Frame (RMF) for path generation and control, enhancing motion stability for paths with significant curvature and inflection points, and reducing kinematic twist. Using the governing equations based on the RMF, we first develop the reference velocity and acceleration along the path that is consistent with the RMF. Employing tools from differential geometry, we derive a path following position control law by projecting the robot translation states onto the RMF. From an analytical description of the relative orientation error kinematics, we derive a stabilizing orientation controller by utilizing the Modified Rodrigues Parameters to avoid the unwinding problem. The proposed framework is applicable to both torque-controlled and velocity-controlled robots, and we provide results from real-time experiments on both types of robots to verify the effectiveness and advantages of the proposed approach.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103390"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144739055","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-07-12DOI: 10.1016/j.mechatronics.2025.103381
Jiazhen Xu, Haoping Wang, Yang Tian
To address the challenges of diminished motivation and increased fatigue observed in participants during active rehabilitation training, this study proposes a digital human model-based adaptive assist-as-needed (DHM-AAAN) control for an upper limb exoskeleton. This control framework consists of two main sub-controller loops: an outer sub-controller loop that determines the necessary assistive force, and an inner sub-controller loop which enables the exoskeleton to accurately replicate target movements while applying the assistive force derived from the outer sub-controller loop. Within the outer sub-controller loop, a strategy known as the digital human model and task performance evaluation (DHM-TPE) is employed to evaluate participants’ mobility capabilities and overall condition. Based on the assessment results, parameters such as radius, frequency, and assistive force are dynamically adjusted for multi-period trajectory tracking tasks through the implementation of an adaptive frequency oscillator (AFO) algorithm integrated with a digital human model. In the inner sub-controller loop, a barrier Lyapunov function-based hybrid force/position control with shifting error constraints (BLF-HCS) controller is introduced. This controller utilizes radial basis function neural networks (RBFNN) and error offset functions initialized with random values. The BLF constrains the exoskeleton’s tracking error, considering potential deviations from the desired initial position during the early phases of movement. To validate the effectiveness of the proposed controller, this study presents joint simulation results of the rehabilitation training cycle for circular task trajectories, experimental results from individual participants, and the average results from 6 participants.
{"title":"Digital human model and training task planning-based adaptive assist-as-needed control for upper limb exoskeleton","authors":"Jiazhen Xu, Haoping Wang, Yang Tian","doi":"10.1016/j.mechatronics.2025.103381","DOIUrl":"10.1016/j.mechatronics.2025.103381","url":null,"abstract":"<div><div>To address the challenges of diminished motivation and increased fatigue observed in participants during active rehabilitation training, this study proposes a digital human model-based adaptive assist-as-needed (DHM-AAAN) control for an upper limb exoskeleton. This control framework consists of two main sub-controller loops: an outer sub-controller loop that determines the necessary assistive force, and an inner sub-controller loop which enables the exoskeleton to accurately replicate target movements while applying the assistive force derived from the outer sub-controller loop. Within the outer sub-controller loop, a strategy known as the digital human model and task performance evaluation (DHM-TPE) is employed to evaluate participants’ mobility capabilities and overall condition. Based on the assessment results, parameters such as radius, frequency, and assistive force are dynamically adjusted for multi-period trajectory tracking tasks through the implementation of an adaptive frequency oscillator (AFO) algorithm integrated with a digital human model. In the inner sub-controller loop, a barrier Lyapunov function-based hybrid force/position control with shifting error constraints (BLF-HCS) controller is introduced. This controller utilizes radial basis function neural networks (RBFNN) and error offset functions initialized with random values. The BLF constrains the exoskeleton’s tracking error, considering potential deviations from the desired initial position during the early phases of movement. To validate the effectiveness of the proposed controller, this study presents joint simulation results of the rehabilitation training cycle for circular task trajectories, experimental results from individual participants, and the average results from 6 participants.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103381"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144605502","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-06-11DOI: 10.1016/j.mechatronics.2025.103356
Joseph Nofech, Mir Behrad Khamesee
This study presents a novel methodology for achieving three-degree-of-freedom (3-DoF) control for an attractive-type magnetically-levitated (maglev) microrobot using machine learning. Contact micromanipulation methods face challenges associated with friction, backlash, and maintenance requirements; particularly in delicate applications such as cell injection. The frictionless and low-maintenance nature of attractive-type maglev makes it a viable alternative to traditional methods, but achieving precise 3-DoF control for such systems is not straightforward due to the complexity of their magnetic fields. This research addresses this problem by introducing a machine learning-based methodology that automates the learning of levitation dynamics across the workspace, effectively bypassing a major challenge associated with cross-disciplinary applications of attractive-type maglev.
Our presented approach introduces an automated system for generating training data with minimal human intervention, allowing a machine learning model to quantify the levitated microrobot’s physical response to system inputs while accounting for position-dependent variations in levitation dynamics across the workspace. This model is then used to establish 3-DoF position control of the levitated microrobot. In addition to simplifying the setup process for new and newly-modified attractive-type levitation platforms, this new data-driven methodology is demonstrated to improve performance over conventional methods; achieving up to a 20% reduction in root mean square error during trajectory tracking and up to a 36% reduction in step response settling times.
The results demonstrate the ability of our automated methodology to significantly reduce the accessibility barriers associated with establishing and modifying attractive-type maglev platforms; effectively replacing the usual methods of finite element simulation, precise magnetic field measurements, and/or analytical calculations while providing enhanced levitation control over traditional methods. This advancement contributes to the field of micromanipulation and microforce sensing by offering a more accessible and efficient approach to achieving precise control in attractive-type maglev systems.
{"title":"Machine learning for automation of 3-DoF control of magnetically-levitated microrobots","authors":"Joseph Nofech, Mir Behrad Khamesee","doi":"10.1016/j.mechatronics.2025.103356","DOIUrl":"10.1016/j.mechatronics.2025.103356","url":null,"abstract":"<div><div>This study presents a novel methodology for achieving three-degree-of-freedom (3-DoF) control for an attractive-type magnetically-levitated (maglev) microrobot using machine learning. Contact micromanipulation methods face challenges associated with friction, backlash, and maintenance requirements; particularly in delicate applications such as cell injection. The frictionless and low-maintenance nature of attractive-type maglev makes it a viable alternative to traditional methods, but achieving precise 3-DoF control for such systems is not straightforward due to the complexity of their magnetic fields. This research addresses this problem by introducing a machine learning-based methodology that automates the learning of levitation dynamics across the workspace, effectively bypassing a major challenge associated with cross-disciplinary applications of attractive-type maglev.</div><div>Our presented approach introduces an automated system for generating training data with minimal human intervention, allowing a machine learning model to quantify the levitated microrobot’s physical response to system inputs while accounting for position-dependent variations in levitation dynamics across the workspace. This model is then used to establish 3-DoF position control of the levitated microrobot. In addition to simplifying the setup process for new and newly-modified attractive-type levitation platforms, this new data-driven methodology is demonstrated to improve performance over conventional methods; achieving up to a 20% reduction in root mean square error during trajectory tracking and up to a 36% reduction in step response settling times.</div><div>The results demonstrate the ability of our automated methodology to significantly reduce the accessibility barriers associated with establishing and modifying attractive-type maglev platforms; effectively replacing the usual methods of finite element simulation, precise magnetic field measurements, and/or analytical calculations while providing enhanced levitation control over traditional methods. This advancement contributes to the field of micromanipulation and microforce sensing by offering a more accessible and efficient approach to achieving precise control in attractive-type maglev systems.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103356"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144264135","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-06-26DOI: 10.1016/j.mechatronics.2025.103364
Yongchao Wang , Tian Zheng , Maged Iskandar , Marion Leibold , Jinoh Lee
This article proposes an optimization-based method for robust yet efficient control of flexible-joint robots by using the model predictive control approach. The time-delay estimation (TDE) technique is used to approximate uncertain and nonlinear dynamic equations, where neither concrete knowledge of mathematical system model parameters is required in the approximation, thus granting the model-free property for dynamics compensation and real-time system linearization. TDE is integrated with model predictive control, which is designated as the incremental model predictive control (IMPC) framework. This approach guarantees the tracking performance of the flexible joint robot with input and output constraints, such as motor torque and joint states. Moreover, the proposed controller can practically circumvent high-order derivatives in implementation while providing robust tracking, a capability that conventional methods for flexible joint robots often face challenges due to the inherent nature of their high-order dynamics. The input-to-state stability of IMPC in a local region around the reachable reference trajectory is theoretically proven, and the high approximation accuracy of the resulting incremental system is analyzed. Finally, a series of experiments is conducted on a flexible-joint robot to verify the practical effectiveness of IMPC, and superior performance in terms of high accuracy, high computational efficiency, and constraint admissibility is demonstrated.
{"title":"Practical and robust incremental model predictive control for flexible-joint robots","authors":"Yongchao Wang , Tian Zheng , Maged Iskandar , Marion Leibold , Jinoh Lee","doi":"10.1016/j.mechatronics.2025.103364","DOIUrl":"10.1016/j.mechatronics.2025.103364","url":null,"abstract":"<div><div>This article proposes an optimization-based method for robust yet efficient control of flexible-joint robots by using the model predictive control approach. The time-delay estimation (TDE) technique is used to approximate uncertain and nonlinear dynamic equations, where neither concrete knowledge of mathematical system model parameters is required in the approximation, thus granting the model-free property for dynamics compensation and real-time system linearization. TDE is integrated with model predictive control, which is designated as the incremental model predictive control (IMPC) framework. This approach guarantees the tracking performance of the flexible joint robot with input and output constraints, such as motor torque and joint states. Moreover, the proposed controller can practically circumvent high-order derivatives in implementation while providing robust tracking, a capability that conventional methods for flexible joint robots often face challenges due to the inherent nature of their high-order dynamics. The input-to-state stability of IMPC in a local region around the reachable reference trajectory is theoretically proven, and the high approximation accuracy of the resulting incremental system is analyzed. Finally, a series of experiments is conducted on a flexible-joint robot to verify the practical effectiveness of IMPC, and superior performance in terms of high accuracy, high computational efficiency, and constraint admissibility is demonstrated.</div></div>","PeriodicalId":49842,"journal":{"name":"Mechatronics","volume":"110 ","pages":"Article 103364"},"PeriodicalIF":3.1,"publicationDate":"2025-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481057","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"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 : 2025-10-01Epub Date: 2025-06-17DOI: 10.1016/j.mechatronics.2025.103362
Sucai Zhang , Yongfu Wang , Gang Li
A finite time adaptive output feedback control scheme with state constraint is proposed for the path tracking control of autonomous vehicle considering the asymmetric dead-zone. Firstly, the vehicle dynamics model and path tracking model are established by combining the dead-zone model, and the adaptive law is designed to approximate the parameters of dead-zone model. On this basis, an adaptive backstepping controller with output-constrained feedback control is designed by combining the filtering error compensation mechanism and the finite time technique, introducing the barrier Lyapunov function and the backstepping control technique. In order to save communication resources, a dynamic threshold event triggering mechanism is introduced. Finally, a rigorous stability analysis based on Lyapunov stability theory is presented to ensure that all signals of the closed-loop system are bounded in finite time. The effectiveness of the proposed method is verified by different simulations, hardware-in-the-loop experiments and real-time vehicle experiments. The results show that the proposed method is effective under different working conditions. The results of real-time vehicle experiments show that the controller can effectively improve the accuracy of path tracking control and reduce the maximum lateral position error to 0.1752 m compared with other methods, and the scheme can provide a theoretical reference for the control practice of autonomous vehicle.
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