The 3D-Pendulum at the World Exhibition 2010 – Control Design and Experimental Results

AbstractCurrent attempts to understand human-machine systems are complex and unwieldy. Multiple disciplines throw different concepts and constructs at the problem, but there is no agreed-to framework to assemble these interrelated moving parts into a coherent system. We propose interdependence as the common factor that unifies and explains these moving parts and undergirds the different terms people use to talk about them. In this chapter, we will describe a sound and practical theoretical framework based on interdependence that enables researchers to predict and explain experimental results in terms of interlocking relationships among well-defined operational principles. Our exposition is not intended to be exhaustive, but instead aims to describe the basic principles in a way that allows the gist to be grasped by a broad cross-disciplinary audience through simple illustrations.

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Multiple Working Mode Based Door Opening Control and Fault Detection of Mobile Modular and Reconfigurable Robot

10.32920/ryerson.14651937.v1 ◽

2021 ◽

Author(s):

Saleh Ahmad Ali

Keyword(s):

Fault Detection ◽

Control Design ◽

Torque Control ◽

Experimental Results ◽

Joint Torque ◽

Detection Scheme ◽

Door Opening ◽

Position Errors ◽

Internal Forces ◽

Reconfigurable Robot

The study in this thesis addresses the problem of opening a door with a modular and reconfigurable robot (MRR) mounted on a wheeled mobile robot platform. The foremost issue with door opening problems is the prevention of occurrence of large internal forces that arise due to position errors or imprecise modeling of the robot or its environment, i.e. the door parameters, specifically. Unlike previous methods that relied on compliance control, making the control design rather complicated, this thesis presents a new concept that utilizes the multiple working modes of the MRR modules. The control design is significantly simplified by switching selected joints of the MRR to work in passive mode during door opening operation. As a result, the occurrence of large internal forces is prevented. Different control schemes are used for control of the joint modules in different working modes. For passive joint modules, a feedforward torque control approach is used to compensate the joint friction to ensure passive motion. For the active joint modules, a distributed control method, based on torque sensing, is used to facilitate the control of joint modules working under this mode. To enable autonomous door opening, an online door parameter estimation algorithm is proposed on the basis of the least squares method; and a path planning algorithm is developed on the basis of Hermite cubic spline functions, with consideration of motion constraints of the mobile MRR. The theory is validated using simulations and experimental results, as presented herein. A distributed fault detection scheme for MRR robots with joint torque sensing is also proposed in this thesis. The proposed scheme relies on filtering the joint torque command and comparing it with a filtered torque estimate that is derived from the nonlinear dynamic model of MRR with joint torque sensing. Common joint actuator faults are considered with fault detection being performed independently for each joint module. The proposed fault detection scheme for each module does not require motion states of any other module, making it an ideal modular approach for fault detection of modular robots. Experimental results have attested the effectiveness of the proposed fault detection scheme.

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Ensembling Coalesce of Logistic Regression Classifier for Heart Disease Prediction using Machine Learning

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.l3473.1081219 ◽

2019 ◽

Vol 8 (12) ◽

pp. 127-133

Keyword(s):

Machine Learning ◽

Logistic Regression ◽

Heart Disease ◽

Heart Diseases ◽

Experimental Results ◽

Disease Prediction ◽

Feature Importance ◽

The World ◽

Feature Scaling ◽

Logistic Regression Classifier

In today’s modern world, the world population is affected with some kind of heart diseases. With the vast knowledge and advancement in applications, the analysis and the identification of the heart disease still remain as a challenging issue. Due to the lack of awareness in the availability of patient symptoms, the prediction of heart disease is a questionable task. The World Health Organization has released that 33% of population were died due to the attack of heart diseases. With this background, we have used Heart Disease Prediction dataset extracted from UCI Machine Learning Repository for analyzing and the prediction of heart disease by integrating the ensembling methods. The prediction of heart disease classes are achieved in four ways. Firstly, The important features are extracted for the various ensembling methods like Extra Trees Regressor, Ada boost regressor, Gradient booster regress, Random forest regressor and Ada boost classifier. Secondly, the highly importance features of each of the ensembling methods is filtered from the dataset and it is fitted to logistic regression classifier to analyze the performance. Thirdly, the same extracted important features of each of the ensembling methods are subjected to feature scaling and then fitted with logistic regression to analyze the performance. Fourth, the Performance analysis is done with the performance metric such as Mean Squared error (MSE), Mean Absolute error (MAE), R2 Score, Explained Variance Score (EVS) and Mean Squared Log Error (MSLE). The implementation is done using python language under Spyder platform with Anaconda Navigator. Experimental results shows that before applying feature scaling, the feature importance extracted from the Ada boost classifier is found to be effective with the MSE of 0.04, MAE of 0.07, R2 Score of 92%, EVS of 0.86 and MSLE of 0.16 as compared to other ensembling methods. Experimental results shows that after applying feature scaling, the feature importance extracted from the Ada boost classifier is found to be effective with the MSE of 0.09, MAE of 0.13, R2 Score of 91%, EVS of 0.93 and MSLE of 0.18 as compared to other ensembling methods.

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Initial Experiments on the Control of a Mobile Tower Crane

Volume 9: Mechanical Systems and Control, Parts A, B, and C ◽

10.1115/imece2007-42372 ◽

2007 ◽

Cited By ~ 3

Author(s):

Joshua Vaughan ◽

William Singhose ◽

Paulo Debenest ◽

Edwardo Fukushima ◽

Shigeo Hirose

Keyword(s):

Theoretical Model ◽

Material Handling ◽

Operational Efficiency ◽

Experimental Results ◽

Input Shaping ◽

Oscillatory Dynamics ◽

Tower Crane ◽

Operational Capabilities ◽

The World

Cranes are used extensively throughout the world in a wide variety of construction and material handling applications. The speed at which these cranes are operated is limited by payload oscillation. Input shaping is one method that reduces this oscillation, allowing higher speeds and improving operational efficiency. Another method to improve the operational capabilities of cranes is to allow base motion. This paper presents initial experimental results from a portable, mobile tower crane. A theoretical model of the crane is presented and experimentally verified. The oscillatory dynamics of the crane are highlighted and controllers to combat these unwanted dynamics are presented.

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Nonlinear FEM Analysis of Experimentally Tested Flat Slabs with Openings

Solid State Phenomena ◽

10.4028/www.scientific.net/ssp.292.191 ◽

2019 ◽

Vol 292 ◽

pp. 191-196 ◽

Cited By ~ 2

Author(s):

Tomáš Augustín ◽

Ľudovít Fillo ◽

Jaroslav Halvonik

Keyword(s):

Model Calibration ◽

Fem Analysis ◽

Linear Analysis ◽

Experimental Results ◽

Nonlinear Fem ◽

Flat Slabs ◽

The World ◽

The Face ◽

Effective Depth ◽

Reference Specimens

Experimental programs focused on the issues related to the flat slabs still attract the attention of the scientists around the world. At the Central Laboratories of STU in Bratislava, together 8 fragments of the flat slabs were tested, focusing on the influence of the openings on the punching resistance. The two reference specimens were without openings and the others had two symmetrically placed openings. The openings were moved from the face of the column in multiples of the effective depth (0d, 1d, 2d). For the assessment of the tests, the models introduced in the relevant standards and codes were applied. The experimental results were also used for NFEM model calibration. The paper will deal with comparison of the theoretical and experimental results as well as with non-linear analysis that was performed in the ATENA FEM program, with the goal to obtain the most realistic behaviour of the flat slabs with openings. The material properties used in the analysis were obtained from the laboratory tests.

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