Estimation of the Balance-Keeping Control Law Applied by a Human Being Upon a Sudden Sagittal Tilt Perturbation

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Nurdan Bilgin ◽  
M. Kemal Özgören
Keyword(s):  
Experimental Data ◽  
Biomechanical Model ◽  
Control Law ◽  
Control Parameters ◽  
Velocity Feedback ◽  
Instantaneous Position ◽  
Sagittal Tilt ◽  
The Central Nervous System ◽  
Time Variations ◽  
Adaptation Scheme

This study aims to estimate the control law employed by the central nervous system (CNS) to keep a person in balance after a sudden disturbance. For this aim, several experiments were carried out, in which the subjects were perturbed sagittally by using a single-axis tilt-platform and their motions were recorded with appropriate sensors. The analysis of the experimental results leads to the contribution of this paper as a conjecture that the CNS commands the muscular actuators of the joints according to an adaptive proportional-derivative (PD) control law such that its gains and set points are updated continuously. This conjecture is accompanied with an assumption that the CNS is able to acquire perfect and almost instantaneous position and velocity feedback by means of a fusion of the signals coming from the proprioceptive, somatosensory, and vestibular systems. In order to verify the conjectured control law, an approximate biomechanical model was developed and several simulations were carried out to imitate the experimentally observed motions. The time variations of the set points and the control gains were estimated out of the experimental data. The simulated motions were observed to be considerably close to the experimental motions. Thus, the conjectured control law is validated. However, the experiments also indicate that the mentioned adaptation scheme is quite variable even for the same subject tested repeatedly with the same perturbation. In other words, this experimental study also leads to the implication that the way the CNS updates the control parameters is not quite predictable.

NeuN As a Neuronal Nuclear Antigen and Neuron Differentiation Marker

Acta Naturae ◽  
2015 ◽  
Vol 7 (2) ◽  
pp. 42-47 ◽  
Author(s):  
V. V. Gusel’nikova ◽  
D. E. Korzhevskiy
Keyword(s):  
Experimental Data ◽  
Intracellular Localization ◽  
Nuclear Antigen ◽  
Structure And Properties ◽  
Immunocytochemical Detection ◽  
Perinuclear Cytoplasm ◽  
Diagnosis Of Cancer ◽  
Morphological Diagnosis ◽  
The Central Nervous System ◽  
Differentiation Marker

The NeuN protein is localized in nuclei and perinuclear cytoplasm of most of the neurons in the central nervous system of mammals. Monoclonal antibodies to the NeuN protein have been actively used in the immunohistochemical research of neuronal differentiation to assess the functional state of neurons in norm and pathology for more than 20 years. Recently, NeuN antibodies have begun to be applied in the differential morphological diagnosis of cancer. However, the structure of the protein, which can be revealed by antibodies to NeuN, remained unknown until recently, and the functions of the protein are still not fully clear. In the present mini-review, data on NeuN accumulated so far are summarized and analyzed. Data on the structure and properties of the protein, its isoforms, intracellular localization, and hypothesized functions are reported. The application field of immunocytochemical detection of NeuN in scientific and clinical studies, as well as the difficulties in the interpretation of the obtained experimental data and their possible causes, is described in details.

Evolution of hindlimb posture in nonmammalian therapsids: biomechanical tests of paleontological hypotheses

Paleobiology ◽  
2001 ◽  
Vol 27 (1) ◽  
pp. 14-38 ◽  
Author(s):  
Richard W. Blob
Keyword(s):  
Experimental Data ◽  
Biomechanical Model ◽  
Axial Rotation ◽  
Morphological Data ◽  
Upright Posture ◽  
Cross Sectional ◽  
Model Calculations ◽  
Limb Bones ◽  
Plausible Model ◽  
Bending Stresses

Analyses of limb joint morphology in nonmammalian therapsid “mammal-like reptiles” have suggested that among many lineages, individual animals were capable of shifting between sprawling and upright hindlimb postures, much like modern crocodilians. The ability to use multiple limb postures thus might have been ancestral to the generally more upright posture that evolved during the transition from “mammal-like reptiles” to mammals. Here I derive a biomechanical model to test this hypothesis through calculations of expected posture-related changes in femoral stress for therapsid taxa using different limb postures. The model incorporates morphological data from fossil specimens and experimental data from force platform experiments on iguanas and alligators.Experimental data suggest that the evolutionary transition from sprawling to nonsprawling posture was accompanied by a change in the predominant loading regime of the limb bones, from torsion to bending. Changes in the cross-sectional morphology of the hindlimb bones between sphenacodontid “pelycosaurs” and gorgonopsid therapsids are consistent with the hypothesis that bending loads increased in importance early in therapsid evolution; thus, bending stresses are an appropriate model for the maximal loads experienced by the limb bones of theriodont therapsids. Results from the model used to estimate stresses in these taxa do not refute the use of both sprawling and more upright stance among basal theriodont therapsids. Thus, the hypothesis that the use of multiple postures was ancestral to the more upright posture typical of most mammals is biomechanically plausible. Model calculations also indicate that the axial rotation of the femur typical in sprawling locomotion can reduce peak bending stresses. Therefore, as experimental data from alligators and iguanas suggest, the evolution of nonsprawling limb posture and kinematics in therapsids might have been accompanied by increased limb bone bending stress.

scholarly journals Posture similarity index: a method to compare hand postures in synergy space

PeerJ ◽  
2018 ◽  
Vol 6 ◽  
pp. e6078 ◽  
Author(s):  
Nayan Bhatt ◽  
Varadhan SKM
Keyword(s):  
Experimental Data ◽  
Tracking System ◽  
Synthetic Data ◽  
Similarity Index ◽  
Principal Component ◽  
Synthetic Dataset ◽  
Human Hand ◽  
Task Requirements ◽  
Kinematic Synergies ◽  
The Central Nervous System

Background The human hand can perform a range of manipulation tasks, from holding a pen to holding a hammer. The central nervous system (CNS) uses different strategies in different manipulation tasks based on task requirements. Attempts to compare postures of the hand have been made for use in robotics and animation industries. In this study, we developed an index called the posture similarity index to quantify the similarity between two human hand postures. Methods Twelve right-handed volunteers performed 70 postures, and lifted and held 30 objects (total of 100 different postures, each performed five times). A 16-sensor electromagnetic tracking system captured the kinematics of individual finger phalanges (segments). We modeled the hand as a 21-DoF system and computed the corresponding joint angles. We used principal component analysis to extract kinematic synergies from this 21-DoF data. We developed a posture similarity index (PSI), that represents the similarity between posture in the synergy (Principal component) space. First, we tested the performance of this index using a synthetic dataset. After confirming that it performs well with the synthetic dataset, we used it to analyze the experimental data. Further, we used PSI to identify postures that are “representative” in the sense that they have a greater overlap (in synergy space) with a large number of postures. Results Our results confirmed that PSI is a relatively accurate index of similarity in synergy space both with synthetic data and real experimental data. Also, more special postures than common postures were found among “representative” postures. Conclusion We developed an index for comparing posture similarity in synergy space and demonstrated its utility by using synthetic dataset and experimental dataset. Besides, we found that “special” postures are actually “special” in the sense that there are more of them in the “representative” postures as identified by our posture similarity index.

scholarly journals Genetic Optimization-Based Consensus Control of Multi-Agent 6-DoF UAV System

Sensors ◽  
2020 ◽  
Vol 20 (12) ◽  
pp. 3576 ◽  
Author(s):  
Aws Najm ◽  
Ibraheem Ibraheem ◽  
Ahmad Azar ◽  
Amjad Humaidi
Keyword(s):  
Genetic Algorithm ◽  
Optimization Technique ◽  
Switching Topology ◽  
Control Law ◽  
Genetic Optimization ◽  
Multi Agent System ◽  
Control Parameters ◽  
Consensus Control ◽  
Communication Topology ◽  
Multi Agent

A consensus control law is proposed for a multi-agent system of quadrotors with leader–follower communication topology for three quadrotor agents. The genetic algorithm (GA) is the proposed optimization technique to tune the consensus control parameters. The complete nonlinear model is used without any further simplifications in the simulations, while simplification in the model is used to theoretically design the controller. Different case studies and tests are done (i.e., trajectory tracking formation and switching topology) to show the effectiveness of the proposed controller. The results show good performance in all tests while achieving the consensus of the desired formations.

scholarly journals Retrieval of water vapor profile in the mesosphere from satellite ozone and hydroxyl measurements by the basic dynamic model of mesospheric photochemical system

2009 ◽  
Vol 9 (21) ◽  
pp. 8199-8210 ◽  
Author(s):  
M. Y. Kulikov ◽  
A. M. Feigin ◽  
G. R. Sonnemann
Keyword(s):  
Experimental Data ◽  
Water Vapor ◽  
Initial Data ◽  
Dynamic Model ◽  
Indirect Method ◽  
Dynamic Models ◽  
Vapor Concentration ◽  
Water Vapor Concentration ◽  
Control Parameters ◽  
Photochemical Systems

Abstract. We propose an indirect method for retrieving a number of significant minor gas constituents of the atmosphere. The technique is based on the use of so-called basic dynamic models of atmospheric photochemical systems simplified mathematically correctly in a special manner. It is applied to a mesospheric system describing day evolution of key minor gas constituents at these heights. We take as initial data experimental data of the CRISTA-MAHRSI satellite campaign of August 1997 during which ozone and hydroxyl (O3 and OH) concentrations were measured simultaneously. It is demonstrated that the use of the basic dynamic model allows retrieval of vertical distribution (within the 53–85 km range of heights) of water vapor concentration that is one of the control parameters of the mesospheric photochemistry.

Research of Subsection Optimal Acceleration Control Law of Aircraft Engines Using Fuzzy Switching Based on a Cloud Model

2011 ◽  
Vol 308-310 ◽  
pp. 1242-1247
Author(s):  
Xiao Jie Qiu ◽  
Jin Quan Huang ◽  
Feng Lu
Keyword(s):  
Control Method ◽  
Cloud Model ◽  
Aircraft Engine ◽  
Effective Control ◽  
Control Law ◽  
Acceleration Process ◽  
Aircraft Engines ◽  
Control Parameters ◽  
Objective Functions ◽  
Switching Controller

Considering the problem of optimal acceleration control of aircraft engine, the subsection optimal acceleration control method using fuzzy switching based on a cloud model is proposed. The acceleration process is divided into three phases, optimal objective functions and constraints are different in each phase. The optimal acceleration control law is obtained using the SQP algorithm with adjusted objective functions and constraints to improve the ability of engine acceleration. Considering the significant jump of control parameters and the exceeding limit of aircraft engine state parameters problem during the shift of different phase on the acceleration process, the method of fuzzy switching controller based on a cloud model is designed. Compared with the normal SQP acceleration control law and the subsection one based on direct switching, the simulation results show that the proposed method not only is the most effective control law but also can ensure the aircraft engine stable.

Linear robust trajectory control of flexible joint manipulators

Robotica ◽  
1996 ◽  
Vol 14 (4) ◽  
pp. 375-380 ◽  
Author(s):  
Yueh-Jaw Lin ◽  
Aiping Yu
Keyword(s):  
Control Algorithm ◽  
Control Law ◽  
Parameter Uncertainties ◽  
Velocity Feedback ◽  
Flexible Joint ◽  
Flexible Joint Robots ◽  
Control Schemes ◽  
On Line ◽  
General Meaning ◽  
Point To Point

SUMMARYThis paper presents a practical approach for the point-to-point control of elastic-jointed robot manipulators. With the proposed approach only position and velocity feedback are referenced, as opposed to most of the existing control schemes of elastic-jointed manipulators which require additional acceleration and/or jerk feedback. To guarantee the robustness of the controller, it is designed on extreme parameter uncertainties due to highly elastic joints of manipulators and energy motivated Lyapunov functions are used to derive the control law. Four pertinent controller gains are chosen in light of the on-line position and velocity feedback of the links and joint sensors. Through a simulated experimental verification, it is demonstrated that the designed simple position and velocity feedback controller, similar to that used for rigid-jointed robots, can globally stabilize the elastic-jointed robot for a bounded reference position. In addition, the tracking performance of the controller reveals that this simple control algorithm is robust in terms of joint flexibility. And the simplicity of the presented control algorithm, as compared to other model-based techniques for flexiblejoint robots, is particularly advantageous. Even though the simulated experiments are conducted on a single-link flexible joint robot, control law derived in this paper has general meaning for multi-link flexible joint robots.

scholarly journals Locus Coeruleus Modulates Neuroinflammation in Parkinsonism and Dementia

2020 ◽  
Vol 21 (22) ◽  
pp. 8630
Author(s):  
Filippo Sean Giorgi ◽  
Francesca Biagioni ◽  
Alessandro Galgani ◽  
Nicola Pavese ◽  
Gloria Lazzeri ◽  
...  
Keyword(s):  
Experimental Data ◽  
Locus Coeruleus ◽  
Clinical Symptoms ◽  
Experimental Studies ◽  
Anatomy And Physiology ◽  
The Central Nervous System ◽  
Near Future

Locus Coeruleus (LC) is the main noradrenergic nucleus of the central nervous system, and its neurons widely innervate the whole brain. LC is severely degenerated both in Alzheimer’s disease (AD) and in Parkinson’s disease (PD), years before the onset of clinical symptoms, through mechanisms that differ among the two disorders. Several experimental studies have shown that noradrenaline modulates neuroinflammation, mainly by acting on microglia/astrocytes function. In the present review, after a brief introduction on the anatomy and physiology of LC, we provide an overview of experimental data supporting a pathogenetic role of LC degeneration in AD and PD. Then, we describe in detail experimental data, obtained in vitro and in vivo in animal models, which support a potential role of neuroinflammation in such a link, and the specific molecules (i.e., released cytokines, glial receptors, including pattern recognition receptors and others) whose expression is altered by LC degeneration and might play a key role in AD/PD pathogenesis. New imaging and biochemical tools have recently been developed in humans to estimate in vivo the integrity of LC, the degree of neuroinflammation, and pathology AD/PD biomarkers; it is auspicable that these will allow in the near future to test the existence of a link between LC-neuroinflammation and neurodegeneration directly in patients.

Osteocalcin: A Protein Hormone Connecting Metabolism, Bone and Testis Function

2020 ◽  
Vol 27 (12) ◽  
pp. 1268-1275
Author(s):  
Luca De Toni ◽  
Kenda Jawich ◽  
Maurizio De Rocco Ponce ◽  
Andrea Di Nisio ◽  
Carlo Foresta
Keyword(s):  
Experimental Data ◽  
Male Fertility ◽  
Endocrine Function ◽  
Protective Effects ◽  
Original Function ◽  
Endocrine Organ ◽  
The Central Nervous System ◽  
Depressive States ◽  
Novel Therapeutic

During the last decade, the disclosure of systemic effects of osteocalcin (OCN) in its undercarboxylated form contributed to switch the concept of bone from a merely structural apparatus to a fully endocrine organ involved in the regulation of systemic functions. Since that time, the role of OCN as osteokine has been more and more widened appreciated and detailed by the major use of animal models, starting from the original function in the bone extracellular matrix as Gla-protein and spanning from the protective effects towards weight gain, insulin sensitivity and glucose homeostasis, to the anabolic and metabolic roles in skeletal muscle, to the stimulating effects on the testis endocrine function and male fertility, to the most recent preservation from anxious and depressive states through a direct activity on the central nervous system. In this review, experimental data supporting the inter-organ communication roles of this protein are discussed, together with the available data supporting the consistency between experimental data obtained in animals and those reported in humans. In addition, a specific session has been devoted to the possible significance the OCN as a template agonist on its receptor GPRC6A, for the development of novel therapeutic and pharmacological approaches for the treatment of dismetabolic states and male infertility.

Design and Experimental Evaluation of a Data-Oriented Generalized Predictive PID Controller

2016 ◽  
Vol 28 (5) ◽  
pp. 722-729 ◽  
Author(s):  
Zhe Guan ◽  
◽  
Shin Wakitani ◽  
Toru Yamamoto ◽  
Keyword(s):  
Predictive Control ◽  
Pid Controller ◽  
Control Design ◽  
Point Of View ◽  
Generalized Predictive Control ◽  
Control Law ◽  
Control Parameters ◽  
Proportional Integral Derivative ◽  
Molding Machine ◽  
Output Data

[abstFig src='/00280005/15.jpg' width='300' text='Schematic figure of data-oriented GPC-PID controller' ] This paper presents a data-oriented technique for designing a proportional-integral-derivative (PID) controller based on a generalized predictive control law for linear unknown systems. In several control design approaches, a model-based control theory, which requires accurate modeling and identification of the plant, is used to calculate the control parameters. However, in higher-order systems and/or systems with an unknown time delay such as chemical industries and thermal industries, it is difficult to model or identify the plant accurately. Over the last decade, data-oriented techniques in which the online or offline data are utilized have been attracting considerable attention. Designing the controllers for unknown plants based on only the input/output data is the main feature of this technique. In this study, controller parameters are first obtained by using a generalized predictive control law with the data-oriented technique, and are converted to PID parameters from the practical point of view. The proposed method is validated experimentally using a real injection-molding machine. The results demonstrate the efficiency of the proposed method.

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