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Position-based motion control for parallel manipulators under parametric uncertainties and with finite-time external disturbance rejection ⁎

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IFAC-PapersOnLine 2020年第2期53卷 8456-8461页

作者： Dmitrii Dobriborsci Sergey Kolyubin Natalia Gorokhova Marina Korotina Alexey Bobtsov Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia.

We consider the task of motion control for non-prehensile manipulation using parallel kinematics mechatronic setup, in particular, stabilization of a ball on a plate under unmeasured external harmonic disturbances. System parameters are assumed to be unknown, and only a ball position is measurable with a resistive touch sensor. To solve the task we propose a novel passivity-based output control algorithm that can be implemented for unstable linearized systems of an arbitrary relative degree. In contrast to previous works, we describe a new way to parametrize harmonic signal generators and an estimation algorithm with finite-time convergence. This scheme enables fast disturbance cancellation under control signal magnitude constraints.

关键词： Adaptive control output control motion control disturbance rejection finite-time estimation ball-and-plate

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Learning Stabilizing Control Policies for a Tensegrity Hopper with Augmented Random Search

Learning Stabilizing Control Policies for a Tensegrity Hoppe...

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International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

作者： Vladislav Kurenkov Hany Hamed Sergei Savin Centerfor Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia Robotics Institute Innopolis University Innopolis Russia

ISBN: (数字)9781728145907

ISBN: (纸本)9781728145914

In this paper, the authors consider a tensegrity hopper - a novel tensegrity-based robot, capable of moving by hopping. The paper focuses on the design of the stabilizing control policies, which are obtained with the Augmented Random Search method. In particular, the authors search for control policies, which allow the hopper to maintain vertical stability after performing a single jump. It is demonstrated, that the hopper can maintain a vertical configuration, subject to the different initial conditions and with changing control frequency rates. In particular, lowering control frequency from 1000Hz in training to 500Hz in execution does not affect the success rate of the balancing task.

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Spatio-temporal EEG activity in cortical network during visual percetion task

Spatio-temporal EEG activity in cortical network during visu...

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Alexander Kuc Natalija Malova Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Saratov Russia Neuroscience and Cognivite Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

A promising task is the analysis of the different rhythms of the brain cortical activity when performing cognitive tasks. Studying this issue allows to advance in the development of brain-computer interfaces. Some brain rhythms show certain dynamics during various cognitive activities. An important rhythm associated with cognitive activity is the alpha rhythm. In this paper, we study features of the dynamics of the alpha rhythm during bistable visual processing of information of varying complexity.

关键词： Visualization Information processing Brain-computer interfaces Complexity theory Task analysis Robots Monitoring

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Development of a digital software platform for the study of nonlinear dynamics of electronic systems 3

Development of a digital software platform for the study of ...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Badarin, Artem Neuroscience and Cognivite Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

The paper presents the results of applied research on the design and application of an integrated platform for solving applied problems of developing, studying and optimizing high-power electron-plasma devices from th... 详细信息

ISBN: (纸本)9781728124704

关键词： Simulation platform

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Database for storing and organizing data of neurophysiological experiments: description and basic functionality

Database for storing and organizing data of neurophysiologic...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Elena Pitsik Semen Kurkin Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

In present paper, we introduce a database containing multichannel experimental data of brain electrical activity (M/EEG signals) supplemented by necessary experimental protocols and additional characteristics of the subject (ECG, EOG, EMG, etc.), as well as the results of various processing methods application to the initial data. Data management and access is implemented with web-interface containing the toolkit for viewing and editing existing data and adding new items. Developed database provides increased level of data storage reliability and instant access to the neurophysiological data for analysis, processing and evaluation of accumulated experimental information.

关键词： Databases Electroencephalography Neuroscience Servers Physics Robots Brain

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Approaches for the Improvement of Motor-Related Patterns Classification in EEG Signals 3

Approaches for the Improvement of Motor-Related Patterns Cla...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Kurkin, Semen Maksimenko, Vladimir Pitsik, Elena Neuroscience and Cognitive Techology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

We apply artificial neural network (ANN) for recognition and classification of electroencephalographic (EEG) patterns associated with motor imagery for untrained subjects. Classification accuracy is optimized by reducing complexity of input experimental data. For multichannel EEG recorded by the set of 31 electrodes, we select an appropriate type of ANN which reaches 80±10% accuracy for single trial classification. We analyze the time-frequency structure of EEG signals and find that motor-related features associated with left- and right-leg motor imagery, are more pronounced in the mu (8-13 Hz) and delta (1-5 Hz) brainwaves. Based on the obtained results, we propose the optimization approach by pre-processing the EEG signals with a low-pass filter with different cutoffs. We demonstrate that the filtration of high-frequency spectral components significantly enhances the classification performance: up to 90±5% using 8 electrodes only. © 2019 IEEE.

关键词： Neural networks

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Space-charge-limited current in an external magnetic field

Space-charge-limited current in an external magnetic field

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Artem Badarin Semen Kurkin Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

This work is devoted to the study of one of the fundamental properties of the beam, namely, space-charge-limited current in a cylindrical drift tube located in an external magnetic field of various intensities. The value of the external magnetic field is determined for different beam energies, at which a sharp change in the critical current and beam dynamics occurs.

关键词： Electron beams Critical current density (superconductivity) Cathodes Plasmas Electron tubes Microwave photonics

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Multilayer perceptron reveals functional connectivity structrure in thalamo-cortical brain network 3

Multilayer perceptron reveals functional connectivity struct...

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3rd School on Dynamics of Complex Networks and their Application in Intellectual robotics, DCNAIR 2019

作者： Frolov, Nikita S. Hramov, Alexander E. Neuroscience and Cognitive Technology Laboratory Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (纸本)9781728124704

Artificial neural networks (ANNs) are known to be a powerful tool for big data analysis. They are widely used in computer science, nonlinear dynamics, robotics, and neuroscience for solving tasks of classification, forecasting, pattern recognition, etc. In neuroscience ANNs allow recognizing specific forms of brain activity from multichannel electro- (EEG) or magnetoencephalographic (MEG) data and, therefore, widely used as a computational core in various brain-computer interfaces. Another challenging problem is the analysis of connectivity structures in big multivariate data. In neuroscience restoring the functional brain network using multichannel EEG/MEG signals uncovers mechanisms of neuronal interaction during various physiological or cognitive processes. In this report we use recent advances in the area of machine learning known as feed-forward artificial neuronal network to formulate a method for detecting functional dependence in unidirectionally and bidirectionally coupled systems without additional information about them. We apply our method for the first time to reveal functional connectivity structure in the thalamo-cortical network of epileptic brain based on a rodent electrocorticography (ECoG) data set. © 2019 IEEE.

关键词： Brain

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Estimating elementary cognitive functions based on EEG signals analysis

Estimating elementary cognitive functions based on EEG signa...

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School on Dynamics of Complex Networks and their Application in Intellectual robotics (DCNAIR)

作者： Alexander Kuc Vadim Grubov Vladimir Maksimenko Vladimir Makarov Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728172866

ISBN: (纸本)9781728172873

Human performance in complex mental tasks relies on elementary cognitive abilities, e.g., information processing speed and working memory capacity. These elementary functions can be measured on a behavioral level using elementary tasks, e.g., reaction time and memory scanning tasks. Cognitive and behavioral neuroscience aims to reveal cortical activity features underlying human performance in the elementary cognitive tasks. In this work, we designed a reaction time task based on the processing of ambiguous sensory stimuli. We found a correlation between the task performance on the behavioral level and the sensor-level cortical activity.

关键词： Electroencephalography Task analysis Neuroscience Correlation Robots mechatronics Information processing

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Cognitive interaction via a brain-to-brain interface

Cognitive interaction via a brain-to-brain interface

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Nonlinearity, Information and robotics, (NIR) International Conference

作者： Vladimir Maksimenko Vadim Grubov Neuroscience and Cognitive Technology Lab Center for Technologies in Robotics and Mechatronics Components Innopolis University Innopolis Russia

ISBN: (数字)9781728187631

ISBN: (纸本)9781728187648

We developed noninvasive brain-to-brain interface for dynamical redistribution of cognitive load between subjects according to their current performances during shared cognitive task. As a result, a participant who exhibits higher cognitive performance is subjected to a higher workload, while his/her partner receives a lower workload. We demonstrate that dynamical workload redistribution allows to increase overall cognitive performance in the pair of interacting subjects.

关键词： Training Systematics Task analysis Robots

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