scholarly journals Bipedal Model and Hybrid Zero Dynamics of Human Walking With Foot Slip

2019 ◽  
Vol 14 (10) ◽  
Author(s):  
Mitja Trkov ◽  
Kuo Chen ◽  
Jingang Yi
Keyword(s):  
Control Strategies ◽  
Human Locomotion ◽  
Human Walking ◽  
Model Parameters ◽  
Zero Dynamics ◽  
Reactive Control ◽  
Analysis And Design ◽  
Hybrid Zero Dynamics ◽  
Dynamics Models ◽  
And Control

Abstract Foot slip is one of the major causes of falls in human locomotion. Analytical bipedal models provide an insight into the complex slip dynamics and reactive control strategies for slip-induced fall prevention. Most of the existing bipedal dynamics models are built on no foot slip assumption and cannot be used directly for such analysis. We relax the no-slip assumption and present a new bipedal model to capture and predict human walking locomotion under slip. We first validate the proposed slip walking dynamic model by tuning and optimizing the model parameters to match the experimental results. The results demonstrate that the model successfully predicts both the human walking and recovery gaits with slip. Then, we extend the hybrid zero dynamics (HZD) model and properties to capture human walking with slip. We present the closed-form of the HZD for human walking and discuss the transition between the nonslip and slip states through slip recovery control design. The analysis and design are illustrated through human walking experiments. The models and analysis can be further used to design and control wearable robotic assistive devices to prevent slip-and-fall.

scholarly journals Understanding the Propagation and Control Strategies of Congestion in Urban Rail Transit Based on Epidemiological Dynamics Model

Information ◽  
2019 ◽  
Vol 10 (8) ◽  
pp. 258 ◽  
Author(s):  
Shi ◽  
Zhang ◽  
Lei
Keyword(s):  
Control Strategies ◽  
Urban Rail Transit ◽  
Model Parameters ◽  
Rail Transit ◽  
Dynamics Model ◽  
Passenger Flow ◽  
Urban Rail ◽  
Passenger Volume ◽  
And Control ◽  
Demand Control

With the construction of the urban rail transit (URT) network, the explosion of passenger volume is more rapid than the increased capacity of the newly built infrastructure, which results in serious passenger flow congestion (PLC). Understanding the propagation process of PLC is the key to formulate sustainable policies for reducing congestion and optimizing management. This study proposes a susceptible-infected-recovered (SIR) model based on the theories of epidemiological dynamics and complex network to analyze the PLC propagation. We simulate the PLC propagation under various situations, and analyze the sensitivity of PLC propagation to model parameters. Finally, the control strategies of restricting PLC propagation are introduced from two aspects, namely, supply control and demand control. The results indicate that both of the two control strategies contribute to relieving congestion pressure. The propagating scope of PLC is more sensitive when taking mild supply control, whereas, the demand control strategy shows some advantages in flexibly implementing and dealing with serious congestion. These results are of important guidance for URT agencies to understand the mechanism of PLC propagation and formulate appropriate congestion control strategies.

Design and Control of the Planar Bipedal Robot ERNIE

2007 ◽  
Author(s):  
T. Yang ◽  
E. R. Westervelt ◽  
J. P. Schmiedeler ◽  
R. A. Bockbrader
Keyword(s):  
Sagittal Plane ◽  
Control Strategies ◽  
Frontal Plane ◽  
High Gain ◽  
Bipedal Walking ◽  
Knee Joints ◽  
Confined Space ◽  
Bipedal Robot ◽  
Hybrid Zero Dynamics ◽  
And Control

This paper presents the development of the planar bipedal robot ERNIE. ERNIE has 5 links: a torso, two femurs and two tibias without feet. ERNIE was designed and constructed to serve as a testbed for the development of novel control strategies for bipedal walking. A boom provides frontal plane stability, restricting walking motions to the sagittal plane, and ERNIE is configured to walk on a treadmill so that it can walk indefinitely in a confined space. ERNIE’s legs are modular so that morphological asymmetries and the use of feet may be explored more in future studies. Springs can be attached across the knee joints in parallel with the knee actuators to enable gaits that are more energetically efficient. ERNIE is currently controlled using the hybrid zero dynamics framework in which a function of the robot’s configuration that monotonically increases over a step is used to parameterize holonomic constraints on the robot’s motion. The constraints are designed via parameter optimization to minimize an objective function, such as the energy consumed over a step, and, at the same time, ensure gait stability. The constraints are enforced using decoupled high-gain PD control.

scholarly journals Dynamics of swine influenza model with optimal control

2019 ◽  
Vol 2019 (1) ◽  
Author(s):  
Takasar Hussain ◽  
Muhammad Ozair ◽  
Kazeem Oare Okosun ◽  
Muhammad Ishfaq ◽  
Aziz Ullah Awan ◽  
...  
Keyword(s):  
Deterministic Model ◽  
Reproduction Number ◽  
Control Strategies ◽  
Influenza Pandemic ◽  
Swine Influenza ◽  
Transmission Dynamics ◽  
Model Parameters ◽  
And Control ◽  
Disease Free ◽  
Good Agreement

AbstractTransmission dynamics of swine influenza pandemic is analysed through a deterministic model. Qualitative analysis of the model includes global asymptotic stability of disease-free and endemic equilibria under a certain condition based on the reproduction number. Sensitivity analysis to ponder the effect of model parameters on the reproduction number is performed and control strategies are designed. It is also verified that the obtained numerical results are in good agreement with the analytical ones.

scholarly journals A Data-Informed Approach for Analysis, Validation, and Identification of COVID-19 Models

2020 ◽  
Author(s):  
S. Yagiz Olmez ◽  
Jameson Mori ◽  
Erik Miehling ◽  
Tamer Başar ◽  
Rebecca L. Smith ◽  
...  
Keyword(s):  
Control Strategies ◽  
Epidemiological Data ◽  
Model Parameters ◽  
Modeling And Analysis ◽  
Viral Shedding ◽  
Markovian Processes ◽  
Transition Times ◽  
Hidden States ◽  
And Control ◽  
Data Informed

AbstractThe COVID-19 pandemic has generated an enormous amount of data, providing a unique opportunity for modeling and analysis. In this paper, we present a data-informed approach for building stochastic compartmental models that is grounded in the Markovian processes underlying these models. Our initial data analyses reveal that the SIRD model – susceptiple (S), infected (I), recovered (R), and death (D) – is not consistent with the data. In particular, the transition times expressed in the dataset do not obey exponential distributions, implying that there exist unmodeled (hidden) states. We make use of the available epidemiological data to inform the location of these hidden states, allowing us to develop an augmented compartmental model which includes states for hospitalization (H) and end of infectious viral shedding (V). Using the proposed model, we characterize delay distributions analytically and match model parameters to empirical quantities in the data to obtain a good model fit. Insights from an epidemiological perspective are presented, as well as their implications for mitigation and control strategies.

scholarly journals Analysis of COVID-19 Prevention and Control Effects Based on the SEITRD Dynamic Model and Wuhan Epidemic Statistics

2020 ◽  
Vol 17 (24) ◽  
pp. 9309
Author(s):  
Yusheng Zhang ◽  
Liang Li ◽  
Yuewen Jiang ◽  
Biqing Huang
Keyword(s):  
Dynamic Model ◽  
Control Method ◽  
Control Strategies ◽  
Dynamical Behavior ◽  
Model Parameters ◽  
Time Control ◽  
Intervention Measures ◽  
Travel Restrictions ◽  
And Control ◽  
The Impact

Since December 2019, millions of people worldwide have been diagnosed with COVID-19, which has caused enormous losses. Given that there are currently no effective treatment or prevention drugs, most countries and regions mainly rely on quarantine and travel restrictions to prevent the spread of the epidemic. How to find proper prevention and treatment methods has been a hot topic of discussion. The key to the problem is to understand when these intervention measures are the best strategies for disease control and how they might affect disease dynamics. In this paper, we build a transmission dynamic model in combination with the transmission characteristics of COVID-19. We thoroughly study the dynamical behavior of the model and analyze how to determine the relevant parameters, and how the parameters influence the transmission process. Furthermore, we subsequently compare the impact of different control strategies on the epidemic, the variables include intervention time, control duration, control intensity, and other model parameters. Finally, we can find a better control method by comparing the results under different schemes and choose the proper preventive control strategy according to the actual epidemic stage and control objectives.

scholarly journals Modeling the COVID-19 Epidemic With Multi-Population and Control Strategies in the United States

2022 ◽  
Vol 9 ◽  
Author(s):  
Deshun Sun ◽  
Xiaojun Long ◽  
Jingxiang Liu
Keyword(s):  
United States ◽  
Mathematical Model ◽  
Control Strategies ◽  
The United States ◽  
Basic Reproductive Number ◽  
Effective Control ◽  
Model Parameters ◽  
Cumulative Number ◽  
And Control ◽  
Sensitive Parameters

As of January 19, 2021, the cumulative number of people infected with coronavirus disease-2019 (COVID-19) in the United States has reached 24,433,486, and the number is still rising. The outbreak of the COVID-19 epidemic has not only affected the development of the global economy but also seriously threatened the lives and health of human beings around the world. According to the transmission characteristics of COVID-19 in the population, this study established a theoretical differential equation mathematical model, estimated model parameters through epidemiological data, obtained accurate mathematical models, and adopted global sensitivity analysis methods to screen sensitive parameters that significantly affect the development of the epidemic. Based on the established precise mathematical model, we calculate the basic reproductive number of the epidemic, evaluate the transmission capacity of the COVID-19 epidemic, and predict the development trend of the epidemic. By analyzing the sensitivity of parameters and finding sensitive parameters, we can provide effective control strategies for epidemic prevention and control. After appropriate modifications, the model can also be used for mathematical modeling of epidemics in other countries or other infectious diseases.

Effective infection prevention and control strategies in a large accredited psychiatric facility in Singapore

2020 ◽  
Author(s):  
Daniel Poremski ◽  
Sandra Henrietta Subner ◽  
Grace Lam Fong Kin ◽  
Raveen Dev Ram Dev ◽  
Mok Yee Ming ◽  
...  
Keyword(s):  
Mental Health ◽  
Prevention And Control ◽  
Infection Prevention ◽  
Control Strategies ◽  
Infection Prevention And Control ◽  
Psychiatric Facility ◽  
Essential Services ◽  
Community Transmission ◽  
And Control

The Institute of Mental Health in Singapore continues to attempt to prevent the introduction of COVID-19, despite community transmission. Essential services are maintained and quarantine measures are currently unnecessary. To help similar organizations, strategies are listed along three themes: sustaining essential services, preventing infection, and managing human and consumable resources.

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