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The terms ||w t ||2 control the task specific model complexity, like for standard SVR.
In [12],[13], authors propose to modify GA to control the task duplication and reduce the length of the processor queues.
However, even with the assumption that all the state variables are available for feedback control, the task of effective controlling a large-scale interconnected system using a global (centralized) state feedback controller is still not easy as there is a necessary requirement for information transfer between the subsystems [15 18].
In the framework of hierarchical control architectures able to uncouple the robot's kinematics (guidance) and dynamics (velocity control), the task of bottom-following is accomplished by suitable guidance task functions, which enable the system to handle unmodeled, i.e. not measured or estimated, kinematics interactions between the robot and the operating environment.
In the framework of hierarchical control architectures able to uncouple the robot's kinematics (guidance) and dynamics (velocity control), the task of bottom-following is accomplished by suitable guidance task functions, which enable the system to handle unmodelled, i.e. not measured or estimated, kinematics interactions between the robot and the operating environment.
Our results hint of a mechanism that determines which hemisphere will control the task.
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Both lesion groups accumulated fewer points than healthy controls across the task.
Many research works have been proposed to control the manipulation tasks using a model of the manipulated object.
Thereby, the choice of the control task and the comparison methodology are oriented on industrial practice.
Groups did not differ significantly in performance in terms of mean accuracy or reaction time on either the EFT or on the control task, or the relative difference in accuracy or reaction time between EFT and control task conditions.
Second, to what extent can one compare the no-reward trials in the control task with the no-reward trials in the reward task?
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