This work brings forward several interesting facts about system properties of LTI discrete-time systems like output controllability, state controllability and state observability, trackability and input and state observability. Particularly, the work brings about the inter-relationships between these properties while taking a state-space formulation based approach to come up with simple facts that are backed up by proofs using preliminary linear algebra.
{"title":"Some Results on the Properties of Discrete-Time LTI State-Space Systems","authors":"S. Kadam, Harish J. Palanthandalam-Madapusi","doi":"10.1115/1.4065590","DOIUrl":"https://doi.org/10.1115/1.4065590","url":null,"abstract":"\u0000 This work brings forward several interesting facts about system properties of LTI discrete-time systems like output controllability, state controllability and state observability, trackability and input and state observability. Particularly, the work brings about the inter-relationships between these properties while taking a state-space formulation based approach to come up with simple facts that are backed up by proofs using preliminary linear algebra.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"114 21","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-05-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141106165","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper proposes the usage of constrained convex optimization in improving the quality of the parameter estimates of a typical process plant with dead time from its time response data by incorporating system-specific constraints that are not considered in standard estimation methods. As the majority of the process plants are identified as second-order plus dead time (SOPDT) systems, the proposed method uses the same for establishing the optimization process. Traditional methods for parameter estimation in SOPDT systems have often relied on heuristic approaches or simplified assumptions, leading to suboptimal results. The proposed methodology augments the accuracy of the estimated values by leveraging the power of constrained convex optimization techniques, using Newton's Quadratic Model and Sequential Quadratic Programming, which provide a rigorous mathematical framework for parameter estimation. By incorporating system constraints, such as bounds on the parameters or stability requirements, it is ensured that the obtained parameter estimates adhere to physical and practical limitations. The proposed approach is demonstrated using simulations and on a real-time system, and the results show that it is effective not only in accurately estimating the parameters of the underdamped SOPDT systems but also works efficiently for parameter estimation of SOPDT systems in the presence of measurement noise. The efficacy of the proposed algorithm is verified by comparing it with similar published methods.
{"title":"Using Constrained Convex Optimization in Parameter Estimation of Process Dynamics with Dead Time","authors":"M. Pal, K. Banerjee, Bivas Dam","doi":"10.1115/1.4064770","DOIUrl":"https://doi.org/10.1115/1.4064770","url":null,"abstract":"\u0000 This paper proposes the usage of constrained convex optimization in improving the quality of the parameter estimates of a typical process plant with dead time from its time response data by incorporating system-specific constraints that are not considered in standard estimation methods. As the majority of the process plants are identified as second-order plus dead time (SOPDT) systems, the proposed method uses the same for establishing the optimization process. Traditional methods for parameter estimation in SOPDT systems have often relied on heuristic approaches or simplified assumptions, leading to suboptimal results. The proposed methodology augments the accuracy of the estimated values by leveraging the power of constrained convex optimization techniques, using Newton's Quadratic Model and Sequential Quadratic Programming, which provide a rigorous mathematical framework for parameter estimation. By incorporating system constraints, such as bounds on the parameters or stability requirements, it is ensured that the obtained parameter estimates adhere to physical and practical limitations. The proposed approach is demonstrated using simulations and on a real-time system, and the results show that it is effective not only in accurately estimating the parameters of the underdamped SOPDT systems but also works efficiently for parameter estimation of SOPDT systems in the presence of measurement noise. The efficacy of the proposed algorithm is verified by comparing it with similar published methods.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"37 14","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139961855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces an adaptive control design tailored for robotic systems described by Euler-Lagrange equations under actuator saturation and partial loss of effectiveness. The adaptive law put forth not only retains conventional control properties but also extends its scope to effectively address challenges posed by actuator saturation and partial loss of effectiveness. The framework's primary focus is on bolstering system robustness, thereby ensuring the achievement of uniformly ultimate bounded tracking errors. The stability and convergence of the system's behavior are rigorously established through the application of the Lyapunov analysis technique. Moreover, the effectiveness and superiority of the introduced framework are compellingly demonstrated through a series of practical simulation and experimental instances.
{"title":"Adaptive Tracking Control of Robotic Manipulator Subjected to Actuator Saturation and Partial Loss of Effectiveness","authors":"Van-Tam Ngo, Yen-Chen Liu","doi":"10.1115/1.4064653","DOIUrl":"https://doi.org/10.1115/1.4064653","url":null,"abstract":"\u0000 This paper introduces an adaptive control design tailored for robotic systems described by Euler-Lagrange equations under actuator saturation and partial loss of effectiveness. The adaptive law put forth not only retains conventional control properties but also extends its scope to effectively address challenges posed by actuator saturation and partial loss of effectiveness. The framework's primary focus is on bolstering system robustness, thereby ensuring the achievement of uniformly ultimate bounded tracking errors. The stability and convergence of the system's behavior are rigorously established through the application of the Lyapunov analysis technique. Moreover, the effectiveness and superiority of the introduced framework are compellingly demonstrated through a series of practical simulation and experimental instances.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"8 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139806011","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper introduces an adaptive control design tailored for robotic systems described by Euler-Lagrange equations under actuator saturation and partial loss of effectiveness. The adaptive law put forth not only retains conventional control properties but also extends its scope to effectively address challenges posed by actuator saturation and partial loss of effectiveness. The framework's primary focus is on bolstering system robustness, thereby ensuring the achievement of uniformly ultimate bounded tracking errors. The stability and convergence of the system's behavior are rigorously established through the application of the Lyapunov analysis technique. Moreover, the effectiveness and superiority of the introduced framework are compellingly demonstrated through a series of practical simulation and experimental instances.
{"title":"Adaptive Tracking Control of Robotic Manipulator Subjected to Actuator Saturation and Partial Loss of Effectiveness","authors":"Van-Tam Ngo, Yen-Chen Liu","doi":"10.1115/1.4064653","DOIUrl":"https://doi.org/10.1115/1.4064653","url":null,"abstract":"\u0000 This paper introduces an adaptive control design tailored for robotic systems described by Euler-Lagrange equations under actuator saturation and partial loss of effectiveness. The adaptive law put forth not only retains conventional control properties but also extends its scope to effectively address challenges posed by actuator saturation and partial loss of effectiveness. The framework's primary focus is on bolstering system robustness, thereby ensuring the achievement of uniformly ultimate bounded tracking errors. The stability and convergence of the system's behavior are rigorously established through the application of the Lyapunov analysis technique. Moreover, the effectiveness and superiority of the introduced framework are compellingly demonstrated through a series of practical simulation and experimental instances.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"4 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139865775","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of robots into environments shared by humans has been enhanced through the use of redundant robots capable of executing primary tasks and secondary objectives such as obstacle avoidance and null space impedance control. A critical secondary objective involves optimizing manipulator configurations to reduce torque and prevent torque saturation, similar to how athletes distribute loads to minimize the risk of injury. This paper suggests employing robotic redundancy to evenly distribute joint loads, thereby improving performance and avoiding torque saturation. Prior studies primarily focused on either endpoint stiffness control or kinetic energy minimization, each having its drawbacks. This paper introduces a novel objective function that responds to all external disturbances at the end effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances. This method, which provides an inverse kinematics solution adaptable to various controllers, demonstrated a 29.85% reduction in peak torque and a 14.69% decrease in cumulative torques in the KUKA LBRiiwa 14 R820 robot.
通过使用能够执行主要任务和次要目标（如避开障碍物和无效空间阻抗控制）的冗余机器人，机器人与人类共享环境的融合得到了加强。一个关键的次要目标涉及优化机械手配置，以降低扭矩并防止扭矩饱和，这与运动员如何分配负载以最大限度降低受伤风险类似。本文建议采用机器人冗余来平均分配关节负载，从而提高性能并避免扭矩饱和。之前的研究主要集中在端点刚度控制或动能最小化上，这两种方法各有缺点。本文介绍了一种新的目标函数，它能对末端效应器的所有外部干扰做出响应，旨在通过冗余降低关节扭矩，从而在干扰中实现精确的轨迹跟踪。该方法提供了一种适用于各种控制器的逆运动学解决方案，在 KUKA LBRiiwa 14 R820 机器人中，峰值扭矩降低了 29.85%，累积扭矩降低了 14.69%。
{"title":"Utilisation of Manipulator Redundancy for Torque Reduction During Force Interaction","authors":"Shail V Jadav, H. Palanthandalam-Madapusi","doi":"10.1115/1.4064654","DOIUrl":"https://doi.org/10.1115/1.4064654","url":null,"abstract":"\u0000 The integration of robots into environments shared by humans has been enhanced through the use of redundant robots capable of executing primary tasks and secondary objectives such as obstacle avoidance and null space impedance control. A critical secondary objective involves optimizing manipulator configurations to reduce torque and prevent torque saturation, similar to how athletes distribute loads to minimize the risk of injury. This paper suggests employing robotic redundancy to evenly distribute joint loads, thereby improving performance and avoiding torque saturation. Prior studies primarily focused on either endpoint stiffness control or kinetic energy minimization, each having its drawbacks. This paper introduces a novel objective function that responds to all external disturbances at the end effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances. This method, which provides an inverse kinematics solution adaptable to various controllers, demonstrated a 29.85% reduction in peak torque and a 14.69% decrease in cumulative torques in the KUKA LBRiiwa 14 R820 robot.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"109 2","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139804449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The integration of robots into environments shared by humans has been enhanced through the use of redundant robots capable of executing primary tasks and secondary objectives such as obstacle avoidance and null space impedance control. A critical secondary objective involves optimizing manipulator configurations to reduce torque and prevent torque saturation, similar to how athletes distribute loads to minimize the risk of injury. This paper suggests employing robotic redundancy to evenly distribute joint loads, thereby improving performance and avoiding torque saturation. Prior studies primarily focused on either endpoint stiffness control or kinetic energy minimization, each having its drawbacks. This paper introduces a novel objective function that responds to all external disturbances at the end effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances. This method, which provides an inverse kinematics solution adaptable to various controllers, demonstrated a 29.85% reduction in peak torque and a 14.69% decrease in cumulative torques in the KUKA LBRiiwa 14 R820 robot.
通过使用能够执行主要任务和次要目标（如避开障碍物和无效空间阻抗控制）的冗余机器人，机器人与人类共享环境的融合得到了加强。一个关键的次要目标涉及优化机械手配置，以降低扭矩并防止扭矩饱和，这与运动员如何分配负载以最大限度降低受伤风险类似。本文建议采用机器人冗余来平均分配关节负载，从而提高性能并避免扭矩饱和。之前的研究主要集中在端点刚度控制或动能最小化上，这两种方法各有缺点。本文介绍了一种新的目标函数，它能对末端效应器的所有外部干扰做出响应，旨在通过冗余降低关节扭矩，从而在干扰中实现精确的轨迹跟踪。该方法提供了一种适用于各种控制器的逆运动学解决方案，在 KUKA LBRiiwa 14 R820 机器人中，峰值扭矩降低了 29.85%，累积扭矩降低了 14.69%。
{"title":"Utilisation of Manipulator Redundancy for Torque Reduction During Force Interaction","authors":"Shail V Jadav, H. Palanthandalam-Madapusi","doi":"10.1115/1.4064654","DOIUrl":"https://doi.org/10.1115/1.4064654","url":null,"abstract":"\u0000 The integration of robots into environments shared by humans has been enhanced through the use of redundant robots capable of executing primary tasks and secondary objectives such as obstacle avoidance and null space impedance control. A critical secondary objective involves optimizing manipulator configurations to reduce torque and prevent torque saturation, similar to how athletes distribute loads to minimize the risk of injury. This paper suggests employing robotic redundancy to evenly distribute joint loads, thereby improving performance and avoiding torque saturation. Prior studies primarily focused on either endpoint stiffness control or kinetic energy minimization, each having its drawbacks. This paper introduces a novel objective function that responds to all external disturbances at the end effector, aiming to lower joint torques via redundancy for precise trajectory tracking amidst disturbances. This method, which provides an inverse kinematics solution adaptable to various controllers, demonstrated a 29.85% reduction in peak torque and a 14.69% decrease in cumulative torques in the KUKA LBRiiwa 14 R820 robot.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"55 5","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139864326","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
A reliability-based design optimization (RBDO) approach for uncertain linear systems subjected to random vibrations is presented. The computation of the first-passage failure probability with uncertain system parameters is computed as the total probability, which accounts for both the stochastic excitation and the randomness of the parameters. This quantity, which is dependent on the failure rate, is in general difficult to compute for complex problems involving finite element simulations. This difficulty becomes even more pronounced in the case of RBDO. To mitigate this problem, this work uses surrogate models and a dedicated adaptive sampling scheme to significantly reduce the number of simulations. Gaussian Processes (GPs) are used as surrogates to approximate the failure rate over the extended space that includes design variables and random parameters. The adaptive sampling scheme leverages the availability of the prediction variance while accounting for the joint distribution of the system's random parameters, enabling the scheme to focus on regions of the space with high probabilistic content. The RBDO algorithm is applied to two test problems modeled with finite elements: a cantilever beam with tip mass and a payload adapter.
{"title":"RELIABILITY-BASED DESIGN OPTIMIZATION OF UNCERTAIN LINEAR SYSTEMS SUBJECTED TO RANDOM VIBRATIONS","authors":"L. E. Ballesteros Martínez, S. Missoum","doi":"10.1115/1.4064378","DOIUrl":"https://doi.org/10.1115/1.4064378","url":null,"abstract":"A reliability-based design optimization (RBDO) approach for uncertain linear systems subjected to random vibrations is presented. The computation of the first-passage failure probability with uncertain system parameters is computed as the total probability, which accounts for both the stochastic excitation and the randomness of the parameters. This quantity, which is dependent on the failure rate, is in general difficult to compute for complex problems involving finite element simulations. This difficulty becomes even more pronounced in the case of RBDO. To mitigate this problem, this work uses surrogate models and a dedicated adaptive sampling scheme to significantly reduce the number of simulations. Gaussian Processes (GPs) are used as surrogates to approximate the failure rate over the extended space that includes design variables and random parameters. The adaptive sampling scheme leverages the availability of the prediction variance while accounting for the joint distribution of the system's random parameters, enabling the scheme to focus on regions of the space with high probabilistic content. The RBDO algorithm is applied to two test problems modeled with finite elements: a cantilever beam with tip mass and a payload adapter.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":" 36","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139143399","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Collecting gait data and providing haptic feedback are essential for the safety and efficiency of robot-based rehabilitation. However, readily available devices that can perform both are scarce. This work presents a novel method for mutual sensing and haptic feedback, through the development of an Inflatable Soft Haptic Sensor (ISHASE). The design, modeling and characterization of ISHASE are discussed. Four ISHASE are embedded in the insole of a shoe to measure ground reaction forces and provide haptic feedback. Four participants were recruited to evaluate the performance of ISHASE as a sensor and haptic device. Experimental results indicate that ISHASE can accurately estimate the user's ground reaction forces while walking, with a maximum and a minimum accuracy of 91% and 85% respectively. Haptic feedback was delivered to four different locations under the foot and the users could identify the location with an average 92% accuracy. A case study, that exemplifies a rehabilitation scenario, is presented to demonstrate the ISHASE's usefulness for mutual sensing and haptic feedback.
{"title":"Gait Sensing and Haptic Feedback Using an Inflatable Soft Haptic Sensor","authors":"Emiliano Quinones Yumbla, Jahnav Rokalaboina, Amber Kanechika, Souvik Poddar, Tolemy M. Nibi, Wenlong Zhang","doi":"10.1115/1.4064377","DOIUrl":"https://doi.org/10.1115/1.4064377","url":null,"abstract":"Collecting gait data and providing haptic feedback are essential for the safety and efficiency of robot-based rehabilitation. However, readily available devices that can perform both are scarce. This work presents a novel method for mutual sensing and haptic feedback, through the development of an Inflatable Soft Haptic Sensor (ISHASE). The design, modeling and characterization of ISHASE are discussed. Four ISHASE are embedded in the insole of a shoe to measure ground reaction forces and provide haptic feedback. Four participants were recruited to evaluate the performance of ISHASE as a sensor and haptic device. Experimental results indicate that ISHASE can accurately estimate the user's ground reaction forces while walking, with a maximum and a minimum accuracy of 91% and 85% respectively. Haptic feedback was delivered to four different locations under the foot and the users could identify the location with an average 92% accuracy. A case study, that exemplifies a rehabilitation scenario, is presented to demonstrate the ISHASE's usefulness for mutual sensing and haptic feedback.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"197 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139145811","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Kaushik Rahman, Daniel Ehme, Clint Penick, Dal Hyung Kim
A locomotion compensator is normally utilized to observe the behavior of walking insects. These compensators cancel out the movement of freely walking insects to facilitate long-term imaging for studying behavior. However, controlling the locomotion compensator with a small error (≤1 mm) has been challenging due to the random motion of walking insects. This study introduces an adaptive model predictive control (MPC) approach combined with trajectory prediction to effectively control the Transparent Omnidirectional Locomotion Compensator (TOLC) for a randomly walking fire ant. The proposed MPC with prediction (MPCwP) utilizes the average velocity from the previous gaiting cycle to estimate its future trajectory. Experimental results demonstrate that MPCwP significantly outperforms MPC without prediction (MPCwoP), which relies solely on the current position and orientation. The distance error of the MPCwP method remains below 0.6 mm for 90.3% and 1.0 mm for 99.2% of the time, whereas MPCwoP achieves this only 32.6% and 69.1% of the time, respectively. Furthermore, the proposed method enhances the tracking performance of the heading angle, with the heading angle error staying below 8° for 92.6% of the time (ωθ = 1.0). The enhanced performance of the proposed MPC has the potential to improve the observation images and enable the integration of additional equipment such as an optical microscope for brain or organ imaging.
{"title":"Motion Compensator for an Untethered Walking Insect Using Adaptive Model Predictive Control","authors":"Kaushik Rahman, Daniel Ehme, Clint Penick, Dal Hyung Kim","doi":"10.1115/1.4064370","DOIUrl":"https://doi.org/10.1115/1.4064370","url":null,"abstract":"A locomotion compensator is normally utilized to observe the behavior of walking insects. These compensators cancel out the movement of freely walking insects to facilitate long-term imaging for studying behavior. However, controlling the locomotion compensator with a small error (≤1 mm) has been challenging due to the random motion of walking insects. This study introduces an adaptive model predictive control (MPC) approach combined with trajectory prediction to effectively control the Transparent Omnidirectional Locomotion Compensator (TOLC) for a randomly walking fire ant. The proposed MPC with prediction (MPCwP) utilizes the average velocity from the previous gaiting cycle to estimate its future trajectory. Experimental results demonstrate that MPCwP significantly outperforms MPC without prediction (MPCwoP), which relies solely on the current position and orientation. The distance error of the MPCwP method remains below 0.6 mm for 90.3% and 1.0 mm for 99.2% of the time, whereas MPCwoP achieves this only 32.6% and 69.1% of the time, respectively. Furthermore, the proposed method enhances the tracking performance of the heading angle, with the heading angle error staying below 8° for 92.6% of the time (ωθ = 1.0). The enhanced performance of the proposed MPC has the potential to improve the observation images and enable the integration of additional equipment such as an optical microscope for brain or organ imaging.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"22 23","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-12-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139148457","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Avinash Baskaran, David Hollinger, Rhet O. Hailey, Michael Zabala, Chad G Rose
Robotic exoskeletons for the hand are being explored to improve health, safety, and physical performance. However, much research effort is needed to establish reliable models of human behavior for effective human-robot interaction control. In this work, surface electromyography is used to measure and model muscle activity of healthy participants performing quasi-isometric and dynamic hand exercises. Non-negative matrix tri-factorization (NM3F) is used to extract hidden neuromuscular parameters encoded in spatial and temporal muscle synergies, which are used to estimate probabilistic linear models of intent, effort, and fatigue. This paper thereby presents steps toward reliable modeling of nonlinear time-varying hand neuromuscular dynamics for intuitive and robust human-robot interaction.
{"title":"Neuromuscular State Estimation via Space-by-Time Neural Signal Decomposition","authors":"Avinash Baskaran, David Hollinger, Rhet O. Hailey, Michael Zabala, Chad G Rose","doi":"10.1115/1.4064069","DOIUrl":"https://doi.org/10.1115/1.4064069","url":null,"abstract":"Robotic exoskeletons for the hand are being explored to improve health, safety, and physical performance. However, much research effort is needed to establish reliable models of human behavior for effective human-robot interaction control. In this work, surface electromyography is used to measure and model muscle activity of healthy participants performing quasi-isometric and dynamic hand exercises. Non-negative matrix tri-factorization (NM3F) is used to extract hidden neuromuscular parameters encoded in spatial and temporal muscle synergies, which are used to estimate probabilistic linear models of intent, effort, and fatigue. This paper thereby presents steps toward reliable modeling of nonlinear time-varying hand neuromuscular dynamics for intuitive and robust human-robot interaction.","PeriodicalId":327130,"journal":{"name":"ASME Letters in Dynamic Systems and Control","volume":"59 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2023-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"139264270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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