Design of a Neural Super-Twisting Controller to Emulate a Flywheel Energy Storage System

In this work, a neural super-twisting algorithm is applied to the design of a controller for a flywheel energy storage system (FESS) emulator. Emulation of the FESS is achieved through driving a Permanent Magnet Synchronous Machine (PMSM) coupled to a shaft to shaft DC-motor. The emulation of the FESS is carried out by controlling the velocity of the PMSM in the energy storage stag and then by controlling the DC-motor velocity in the energy feedback stage, where the plant’s states of both electrical machines are identified via a neural network. For the neural identification, a Recurrent Wavelet First-Order Neural Network (RWFONN) is proposed. For the design of the velocity controller, a super-twisting algorithm is applied by using a sliding surface as the argument; the latter is designed based on the states of the RWFONN, in combination with the block control linearization technique to the control of the angular velocity from both machines in their respective operation stage. The RWFONN is trained online using the filtered error algorithm. Closed-loop stability analysis is included when assuming boundedness of the synaptic weights. The results obtained from Matlab/Simulink validate the performance of the proposal in the control of an FESS.

Adiabatic Brownian motor with a stepwise potential perturbed by a dichotomous harmonic sygnal

We obtained an analytical expression for the average motion velocity of an adiabatic Brownian motor (ratchet), which operates due to small dichotomous spatially harmonic fluctuations of a stepwise potential. The symmetry properties of the average velocity as a functional of the stationary and fluctuating components of the nanoparticle potential energy are revealed, and the ranges of values of the system parameters that ensure the rightward and leftward motion of the motor are determined. We showed that the average motor velocity is a non-monotonic function of the stepwise potential height. For a singular (infinitely high and narrow) potential barrier, the average velocity depends non-monotonically on the «power» of this barrier (the barrier width multiplied by the exponent of the ratio of the barrier height to the thermal energy). The article continues the further development of theoretical methods of symmetry analysis by applying the general approaches proposed by the authors to specific motor systems.

Discussion On “Selective-Compliance-Based Lagrange Model and Multilevel Non-Collocated Feedback Control of a Humanoid Robot”

The publication [1] makes unjustified claims, has many inconsistencies, numerous technical errors in the theoretical exposition and omitted proofs. The stability claim of the COM dynamics is incomplete and errors increase in time indicating that the robot is unstable and will eventually fall. The range of disturbances that the controller can handle is not suitably addressed. In addition the reported tracking stability results, for PDD control (motor position, motor velocity and link velocity feedback) and PPDD (full state feedback), have already been published by Lanari [1a], [2a] for a larger class of models and with full details of the corresponding Lagrange stability proofs.

Genotype and defects in microtubule-based motility correlate with clinical severity in KIF1A Associated Neurological Disorder

KIF1A Associated Neurological Disorder (KAND) encompasses a recently identified group of rare neurodegenerative conditions caused by variants in KIF1A, a member of the kinesin-3 family of microtubule (MT) motor proteins. Here we characterize the natural history of KAND in 117 individuals using a combination of caregiver or self-reported medical history, a standardized measure of adaptive behavior, clinical records, and neuropathology. We developed a heuristic severity score using a weighted sum of common symptoms to assess disease severity. Focusing on 100 individuals, we compared the average clinical severity score for each variant with in silico predictions of deleteriousness and location in the protein. We found increased severity is strongly associated with variants occurring in regions involved with ATP and MT-binding: the P-loop, switch I, and switch II. For a subset of identified variants, we generated recombinant mutant proteins which we used to assess transport in vivo by assessing neurite tip accumulation, and to assess MT binding, motor velocity, and processivity using total internal reflection fluorescence microscopy. We find all patient variants result in defects in transport, and describe three classes of protein dysfunction: reduced MT binding, reduced velocity and processivity, and increased non-motile rigor MT binding. The molecular rigor phenotype is consistently associated with the most severe clinical phenotype, while reduced binding is associated with milder clinical phenotypes. Our findings suggest the clinical phenotypic heterogeneity in KAND likely reflects and parallels diverse molecular phenotypes. We propose a new way to describe KAND subtypes to better capture the breadth of disease severity.

Classification of Tactile and Motor Velocity-Evoked Hemodynamic Response in Primary Somatosensory and Motor Cortices as Measured by Functional Near-Infrared Spectroscopy

Functional near-infrared spectroscopy (fNIRS) is an emerging technique in studying cerebral hemodynamics; however, consensus on the analysis methods and the clinical applications has yet to be established. In this study, we demonstrate the results of a pilot fNIRS study of cerebral hemodynamic response (HR) evoked by pneumotactile and sensorimotor stimuli on the dominant hand. Our goal is to find the optimal stimulus parameters to maximally evoke HR in the primary somatosensory and motor cortices. We use a pulsatile pneumatic array of 14 tactile cells that were attached to the glabrous surface of the dominant hand, with a patterned stimulus that resembles saltation at three distinct traverse velocities [10, 25, and 45 cm/s]. NIRS optodes (16 sources; 20 detectors) are bilaterally and symmetrically placed over the pre-and post-central gyri (M1 and S1). Our objective is to identify the extent to which cerebral HR can encode the velocity of the somatosensory and/or motor stimuli. We use common spatial pattern for feature extraction and regularized-discriminant analysis for classifying the fNIRS time series into velocity classes. The classification results demonstrate discriminatory features of the fNIRS signal from each distinct stimulus velocity. The results are inconclusive regarding the velocity which evokes the highest intensity of hemodynamic response.

Recycling and Updating an Educational Robot Manipulator with Open-Hardware-Architecture

This article presents a methodology to recycle and upgrade a 4-DOF educational robot manipulator with a gripper. The robot is upgraded by providing it an artificial vision that allows obtaining the position and shape of objects collected by it. A low-cost and open-source hardware solution is also proposed to achieve motion control of the robot through a decentralized control scheme. The robot joints are actuated through five direct current motors coupled to optical encoders. Each encoder signal is fed to a proportional integral derivative controller with anti-windup that employs the motor velocity provided by a state observer. The motion controller works with only two open-architecture Arduino Mega boards, which carry out data acquisition of the optical encoder signals. MATLAB-Simulink is used to implement the controller as well as a friendly graphical interface, which allows the user to interact with the manipulator. The communication between the Arduino boards and MATLAB-Simulink is performed in real-time utilizing the Arduino IO Toolbox. Through the proposed controller, the robot follows a trajectory to collect a desired object, avoiding its collision with other objects. This fact is verified through a set of experiments presented in the paper.

Processivity and Velocity for Motors Stepping on Periodic Tracks

Processive molecular motors enable cargo transportation by assembling into dimers capable of taking several consecutive steps along a cytoskeletal filament. In the well-accepted hand-over-hand stepping mechanism the trailing motor detaches from the track and binds the filament again in leading position. This requires fuel consumption in the form of ATP hydrolysis, and coordination of the catalytic cycles between the leading and the trailing heads. However, alternative stepping mechanisms exist, including inchworm-like movements, backward steps, and foot stomps. Whether all of these pathways are coupled to ATP hydrolysis remains to be determined. Here, in order to establish the principles governing the dynamics of processive movement, we present a theoretical framework which includes all of the alternative stepping mechanisms. Our theory bridges the gap between the elemental rates describing the biochemical and structural transitions in each head, and the experimentally measurable quantities, such as velocity, processivity, and probability of backward stepping. Our results, obtained under the assumption that the track is periodic and infinite, provide expressions which hold regardless of the topology of the network connecting the intermediate states, and are therefore capable of describing the function of any molecular motor. We apply the theory to myosin VI, a motor that takes frequent backward steps, and moves forward with a combination of hand-over-hand and inchworm-like steps. Our model reproduces quantitatively various observables of myosin VI motility measured experimentally from two groups. The theory is used to predict the gating mechanism, the pathway for backward stepping, and the energy consumption as a function of ATP concentration.Significance StatementMolecular motors harness the energy released by ATP hydrolysis to transport cargo along cytoskeletal filaments. The two identical heads in the motor step alternatively on the polar track by communicating with each other. Our goal is to elucidate how the coordination between the two heads emerges from the catalytic cycles. To do so, we created a theoretical framework that allows us to relate the measurable features of motility, such as motor velocity, with the biochemical rates in the leading and trailing heads, thereby connecting biochemical activity and motility. We illustrate the efficacy of the theory by analyzing experimental data for myosin VI, which takes frequent backward steps, and moves forward by a hand-over-hand and inchworm-like steps.