Inter-Trial Dynamics of Repeated Skilled Movements

2007 ◽  
Author(s):  
Joby John ◽  
Joseph P. Cusumano
Keyword(s):  
Hierarchical Control ◽  
Goal Function ◽  
Human Movements ◽  
Control Scheme ◽  
Goal Level ◽  
Goal Equivalent Manifold ◽  
Goal Functions ◽  
The Stability ◽  
Passive Sensitivity ◽  
Definition Of

In this paper, we develop a class of discrete dynamical systems for modeling repeated, goal-directed, kinematically redundant human movements. The approach is based on a mathematical definition of movement tasks in terms of goal functions. Each goal function can give rise to an associated goal equivalent manifold (GEM), which contains all body states that exactly satisfy the task requirements. A hierarchical control scheme involving in-trial action templates and inter-trial stochastic optimal error correction is included to generate a nonlinear map for the repeated execution of the task. A simple throwing task is used to illustrate the underlying concepts and to develop a model problem for further study. The performance at the goal level, as measured by the root mean square error, is shown to result from factors that are measures of passive sensitivity, the magnitude of body fluctuations, the orientation of fluctuations with the GEM, and the stability properties of the inter-trial controller. The action of the inter-trial controller developed for our model system is simulated and is shown to agree with the mathematically predicted performance.

scholarly journals An adaptive hierarchical control for aerial manipulators

Robotica ◽  
2018 ◽  
Vol 36 (10) ◽  
pp. 1527-1550 ◽  
Author(s):  
Francesco Pierri ◽  
Giuseppe Muscio ◽  
Fabrizio Caccavale
Keyword(s):  
Control Algorithm ◽  
Hierarchical Control ◽  
Bottom Layer ◽  
Trajectory Tracking Control ◽  
Aerial Manipulator ◽  
Control Scheme ◽  
Modelling Uncertainties ◽  
Aerial Vehicle ◽  
The Stability

SUMMARYThis paper addresses the trajectory tracking control problem for a quadrotor aerial vehicle, equipped with a robotic manipulator (aerial manipulator). The controller is organized in two layers: in the top layer, an inverse kinematics algorithm computes the motion references for the actuated variables; in the bottom layer, a motion control algorithm is in charge of tracking the motion references computed by the upper layer. To the purpose, a model-based control scheme is adopted, where modelling uncertainties are compensated through an adaptive term. The stability of the proposed scheme is proven by resorting to Lyapunov arguments. Finally, a simulation case study is proposed to prove the effectiveness of the approach.

Control of grasp stiffness using a multifingered robot hand with redundant joints

Robotica ◽  
1995 ◽  
Vol 13 (4) ◽  
pp. 351-362 ◽  
Author(s):  
H. R. Choi ◽  
W. K. Chung ◽  
Y. Youm
Keyword(s):  
Control Method ◽  
Hierarchical Control ◽  
Joint Stiffness ◽  
Least Square ◽  
Robot Hand ◽  
Control Scheme ◽  
Least Square Problem ◽  
Stiffness Control ◽  
Planar Robot ◽  
The Stability

SummaryThis paper addresses a method of satisfactorily controlling the grasp of objects. Emphasis is placed on achieving the desired stiffness of a grasped object as accurately as possible, especially when the fingers have redundant joints. A model describing the relation between stiffness and force is derived. Based upon this model, a hierarchical control scheme of the grasp stiffness, called decentralized object stiffness control (DOSC) is proposed. DOSC is composed of a fingertip stiffness synthesis (FSS) algorithm and orthogonal stiffness decomposition control (OSDC). Employing the proposed FSS always achieves the desired grasp stiffness by solving the constrained least square problem. The computed fingertip stiffness is achieved by OSDC. It offers a feasible way of controlling the fingertip stiffness as well as maintaining the stability of the finger configuration by modulating the joint stiffness. The developed control method is implemented on a two-fingered planar robot hand one finger of which has a redundant joint. The effectiveness of the control method is confirmed experimentally.

scholarly journals Trial-to-trial dynamics and learning in a generalized, redundant reaching task

2013 ◽  
Vol 109 (1) ◽  
pp. 225-237 ◽  
Author(s):  
Jonathan B. Dingwell ◽  
Rachel F. Smallwood ◽  
Joseph P. Cusumano
Keyword(s):  
Goal Function ◽  
General Strategy ◽  
Reaching Task ◽  
Subsequent Learning ◽  
Learning Rates ◽  
Specific Goal ◽  
Goal Equivalent Manifold ◽  
Variance Ratios ◽  
Goal Functions ◽  
Do So

If humans exploit task redundancies as a general strategy, they should do so even if the redundancy is decoupled from the physical implementation of the task itself. Here, we derived a family of goal functions that explicitly defined infinite possible redundancies between distance ( D) and time ( T) for unidirectional reaching. All [ T, D] combinations satisfying any specific goal function defined a goal-equivalent manifold (GEM). We tested how humans learned two such functions, D/T = c (constant speed) and D·T = c, that were very different but could both be achieved by neurophysiologically and biomechanically similar reaching movements. Subjects were never explicitly shown either relationship, but only instructed to minimize their errors. Subjects exhibited significant learning and consolidation of learning for both tasks. Initial error magnitudes were higher, but learning rates were faster, for the D· T task than for the D/ T task. Learning the D/ T task first facilitated subsequent learning of the D· T task. Conversely, learning the D· T task first interfered with subsequent learning of the D/ T task. Analyses of trial-to-trial dynamics demonstrated that subjects actively corrected deviations perpendicular to each GEM faster than deviations along each GEM to the same degree for both tasks, despite exhibiting significantly greater variance ratios for the D/ T task. Variance measures alone failed to capture critical features of trial-to-trial control. Humans actively exploited these abstract task redundancies, even though they did not have to. They did not use readily available alternative strategies that could have achieved the same performance.

Postmodern More

Moreana ◽  
2003 ◽  
Vol 40 (Number 153- (1-2) ◽  
pp. 219-239
Author(s):  
Anne Lake Prescott
Keyword(s):  
Human Language ◽  
Thomas More ◽  
The Stability ◽  
Definition Of ◽  
Recent Critic

Thomas More is often called a “humanist,” and rightly so if the word has its usual meaning in scholarship on the Renaissance. “Humanist” has by now acquired so many different and contradictory meanings, however, that it needs to be applied carefully to the likes of More. Many postmodernists tend to use the word, pejoratively, to mean someone who believes in an autonomous self, the stability of words, reason, and the possibility of determinable meanings. Without quite arguing that More was a postmodernist avant la lettre, this essay suggests that he was not a “humanist” who stalks the pages of much recent postmodernist theory and that in fact even while remaining a devout Catholic and sensible lawyer he was quite as aware as any recent critic of the slipperiness of human selves and human language. It is time that literary critics tightened up their definition of “humanist,” especially when writing about the Renaissance.

scholarly journals Influence of study model, baseline catalytic concentrations and analytical system on the stability of serum alanine aminotransferase

2020 ◽  
Vol 1 (2) ◽  
Author(s):  
Josep Miquel Bauça ◽  
Andrea Caballero ◽  
Carolina Gómez ◽  
Débora Martínez-Espartosa ◽  
Isabel García del Pino ◽  
...  
Keyword(s):  
Alanine Aminotransferase ◽  
Experimental Models ◽  
Individual Variability ◽  
Serum Samples ◽  
Multicentric Study ◽  
Different Temperatures ◽  
The Stability ◽  
Analytical System ◽  
Definition Of ◽  
Analytical Platforms

AbstractObjectivesThe stability of the analytes most commonly used in routine clinical practice has been the subject of intensive research, with varying and even conflicting results. Such is the case of alanine aminotransferase (ALT). The purpose of this study was to determine the stability of serum ALT according to different variables.MethodsA multicentric study was conducted in eight laboratories using serum samples with known initial catalytic concentrations of ALT within four different ranges, namely: <50 U/L (<0.83 μkat/L), 50–200 U/L (0.83–3.33 μkat/L), 200–400 U/L (3.33–6.67 μkat/L) and >400 U/L (>6.67 μkat/L). Samples were stored for seven days at two different temperatures using four experimental models and four laboratory analytical platforms. The respective stability equations were calculated by linear regression. A multivariate model was used to assess the influence of different variables.ResultsCatalytic concentrations of ALT decreased gradually over time. Temperature (−4%/day at room temperature vs. −1%/day under refrigeration) and the analytical platform had a significant impact, with Architect (Abbott) showing the greatest instability. Initial catalytic concentrations of ALT only had a slight impact on stability, whereas the experimental model had no impact at all.ConclusionsThe constant decrease in serum ALT is reduced when refrigerated. Scarcely studied variables were found to have a significant impact on ALT stability. This observation, added to a considerable inter-individual variability, makes larger studies necessary for the definition of stability equations.

A computationally efficient adaptive robust control scheme for a quad-rotor transporting cable-suspended payloads

2021 ◽  
pp. 095441002110136
Author(s):  
Nasim Ullah ◽  
Irfan Sami ◽  
Wang Shaoping ◽  
Hamid Mukhtar ◽  
Xingjian Wang ◽  
...  
Keyword(s):  
Robust Control ◽  
Fractional Order ◽  
Sliding Mode ◽  
Adaptive Robust Control ◽  
Computationally Efficient ◽  
Control Scheme ◽  
Control Schemes ◽  
Adaptive Laws ◽  
Unknown Disturbances ◽  
The Stability

This article proposes a computationally efficient adaptive robust control scheme for a quad-rotor with cable-suspended payloads. Motion of payload introduces unknown disturbances that affect the performance of the quad-rotor controlled with conventional schemes, thus novel adaptive robust controllers with both integer- and fractional-order dynamics are proposed for the trajectory tracking of quad-rotor with cable-suspended payload. The disturbances acting on quad-rotor due to the payload motion are estimated by utilizing adaptive laws derived from integer- and fractional-order Lyapunov functions. The stability of the proposed control systems is guaranteed using integer- and fractional-order Lyapunov theorems. Overall, three variants of the control schemes, namely adaptive fractional-order sliding mode (AFSMC), adaptive sliding mode (ASMC), and classical Sliding mode controllers (SMC)s) are tested using processor in the loop experiments, and based on the two performance indicators, namely robustness and computational resource utilization, the best control scheme is evaluated. From the results presented, it is verified that ASMC scheme exhibits comparable robustness as of SMC and AFSMC, while it utilizes less sources as compared to AFSMC.

Adaptive attitude-tracking control of spacecraft considering on-orbit refuelling

2020 ◽  
pp. 014233122097313
Author(s):  
Yiqi Xu
Keyword(s):  
Tracking Control ◽  
Closed Loop ◽  
Closed Loop System ◽  
Tracking Errors ◽  
Attitude Tracking ◽  
Control Scheme ◽  
Inertia Model ◽  
And Performance ◽  
Attitude Tracking Control ◽  
The Stability

This paper studies the attitude-tracking control problem of spacecraft considering on-orbit refuelling. A time-varying inertia model is developed for spacecraft on-orbit refuelling, which actually includes two processes: fuel in the transfer pipe and fuel in the tank. Based upon the inertia model, an adaptive attitude-tracking controller is derived to guarantee the stability of the resulted closed-loop system, as well as asymptotic convergence of the attitude-tracking errors, despite performing refuelling operations. Finally, numerical simulations illustrate the effectiveness and performance of the proposed control scheme.

scholarly journals Reliable Learning with PDE-Based CNNs and DenseNets for Detecting COVID-19, Pneumonia, and Tuberculosis from Chest X-Ray Images

Mathematics ◽  
2021 ◽  
Vol 9 (4) ◽  
pp. 434
Author(s):  
Anca Nicoleta Marginean ◽  
Delia Doris Muntean ◽  
George Adrian Muntean ◽  
Adelina Priscu ◽  
Adrian Groza ◽  
...  
Keyword(s):  
Transfer Learning ◽  
Negative Impact ◽  
X Ray ◽  
Domain Specific ◽  
Direct Training ◽  
Public Data ◽  
Normal Chest ◽  
Chest X Ray ◽  
The Stability ◽  
Definition Of

It has recently been shown that the interpretation by partial differential equations (PDEs) of a class of convolutional neural networks (CNNs) supports definition of architectures such as parabolic and hyperbolic networks. These networks have provable properties regarding the stability against the perturbations of the input features. Aiming for robustness, we tackle the problem of detecting changes in chest X-ray images that may be suggestive of COVID-19 with parabolic and hyperbolic CNNs and with domain-specific transfer learning. To this end, we compile public data on patients diagnosed with COVID-19, pneumonia, and tuberculosis, along with normal chest X-ray images. The negative impact of the small number of COVID-19 images is reduced by applying transfer learning in several ways. For the parabolic and hyperbolic networks, we pretrain the networks on normal and pneumonia images and further use the obtained weights as the initializers for the networks to discriminate between COVID-19, pneumonia, tuberculosis, and normal aspects. For DenseNets, we apply transfer learning twice. First, the ImageNet pretrained weights are used to train on the CheXpert dataset, which includes 14 common radiological observations (e.g., lung opacity, cardiomegaly, fracture, support devices). Then, the weights are used to initialize the network which detects COVID-19 and the three other classes. The resulting networks are compared in terms of how well they adapt to the small number of COVID-19 images. According to our quantitative and qualitative analysis, the resulting networks are more reliable compared to those obtained by direct training on the targeted dataset.

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