scholarly journals Adaptive State Observer for Robot Manipulators Diagnostics and Health Degree Assessment

2020 ◽  
Vol 10 (2) ◽  
pp. 514 ◽  
Author(s):  
Sanlei Dang ◽  
Zhengmin Kong ◽  
Long Peng ◽  
Yilin Ji ◽  
Yongwang Zhang
Keyword(s):  
Fault Detection ◽  
Robot Manipulator ◽  
Robot Manipulators ◽  
Health Assessment ◽  
Dynamic Environment ◽  
Detection Algorithm ◽  
Real System ◽  
Adaptive Observer ◽  
Output Measurement ◽  
The Real

To avoid serious damages caused by the dynamic environment, fault detection and health assessment are essential for an integrated robotic system. In this paper, we propose a fault detection algorithm and a health degree assessment approach for a robot manipulator system. Both the internal disturbance and the output measurement disturbance are considered in the proposed method. In addition, an adaptive observer is utilized to reconstruct the real system of robot manipulators. Under the proposed observer, the real system is estimated to detect the fault and obtain the health degree of the robot manipulator. The feasibility and reliability of the proposed fault detection algorithm and health degree assessment index for robot manipulator systems are proved by simulation experiments.

Actuator Fault Detection and Isolation for Robot Manipulators with the Adaptive Observer

2012 ◽  
Vol 482-484 ◽  
pp. 529-532
Author(s):  
Shao Cong Guo ◽  
Mo Han Yang ◽  
Zi Rui Xing ◽  
Yi Li ◽  
Ji Qing Qiu
Keyword(s):  
Fault Detection ◽  
Robot Manipulators ◽  
Industrial Robot ◽  
Experimental Results ◽  
Fault Detection And Isolation ◽  
Adaptive Observer ◽  
Actuator Fault ◽  
Unknown Parameters ◽  
State Observers ◽  
Planar Robot

The fault detection and isolation (FDI) for industrial robot manipulators, subject to faults of actuator, is devised in this paper. An adaptive observer is designed to tackle the robustness problem for unknown parameters due to faults，based on a bank of state observers. By using an adaptive regulating algorithm, the observer is ensured to be stable and the estimated errors are guaranteed to converge. Experimental results are reported for a planar robot under gravity, considering partial failures of the motor torques.

Carbon monoxide adaptive observer for fuel cell fault detection

2007 ◽  
Author(s):  
Damiano Di Penta ◽  
Karim Bencherif ◽  
Qinghua Zhang ◽  
Michel Sorine
Keyword(s):  
Carbon Monoxide ◽  
Fuel Cell ◽  
Fault Detection ◽  
Adaptive Observer

FAULT DETECTION ALGORITHM FOR TEMPERATURE SENSORS OF HOUSEHOLD REFRIGERATORS

2017 ◽  
Author(s):  
Everton Machado ◽  
Alexsandro Santos Silveira ◽  
Alexandre Trofino ◽  
claudio melo
Keyword(s):  
Fault Detection ◽  
Detection Algorithm ◽  
Temperature Sensors

scholarly journals A Tool for the Analysis and Characterization of School Mathematical Models

Mathematics ◽  
2021 ◽  
Vol 9 (13) ◽  
pp. 1569
Author(s):  
Jesús Montejo-Gámez ◽  
Elvira Fernández-Ahumada ◽  
Natividad Adamuz-Povedano
Keyword(s):  
Mathematical Modeling ◽  
Mathematical Models ◽  
Educational Research ◽  
Analysis Procedure ◽  
Real System ◽  
The Real ◽  
School Model ◽  
Corresponding Analysis ◽  
Three Components

This paper shows a tool for the analysis of written productions that allows for the characterization of the mathematical models that students develop when solving modeling tasks. For this purpose, different conceptualizations of mathematical models in education are discussed, paying special attention to the evidence that characterizes a school model. The discussion leads to the consideration of three components, which constitute the main categories of the proposed tool: the real system to be modeled, its mathematization and the representations used to express both. These categories and the corresponding analysis procedure are explained and illustrated through two working examples, which expose the value of the tool in establishing the foci of analysis when investigating school models, and thus, suggest modeling skills. The connection of this tool with other approaches to educational research on mathematical modeling is also discussed.

Pseudoinverse-type bi-criteria minimization scheme for redundancy resolution of robot manipulators

Robotica ◽  
2014 ◽  
Vol 33 (10) ◽  
pp. 2100-2113 ◽  
Author(s):  
Bolin Liao ◽  
Weijun Liu
Keyword(s):  
Robot Manipulator ◽  
Robot Manipulators ◽  
Weighting Factor ◽  
Redundancy Resolution ◽  
Type Solution ◽  
Revolute Joints ◽  
Joint Velocity ◽  
Joint Acceleration ◽  
Minimum Velocity ◽  
Minimization Scheme

SUMMARYIn this paper, a pseudoinverse-type bi-criteria minimization scheme is proposed and investigated for the redundancy resolution of robot manipulators at the joint-acceleration level. Such a bi-criteria minimization scheme combines the weighted minimum acceleration norm solution and the minimum velocity norm solution via a weighting factor. The resultant bi-criteria minimization scheme, formulated as the pseudoinverse-type solution, not only avoids the high joint-velocity and joint-acceleration phenomena but also causes the joint velocity to be near zero at the end of motion. Computer simulation results based on a 4-Degree-of-Freedom planar robot manipulator comprising revolute joints further verify the efficacy and flexibility of the proposed bi-criteria minimization scheme on robotic redundancy resolution.

scholarly journals Recognition of Human Emotion Detection and Annotation, using Local Descriptor and Support Vector Machine

2019 ◽  
Vol 9 (2) ◽  
pp. 2838-2843
Keyword(s):  
Support Vector Machine ◽  
Object Detection ◽  
Dynamic Environment ◽  
Detection Algorithm ◽  
Research Area ◽  
Multimedia Data ◽  
Video Annotation ◽  
Support Vector ◽  
People Detection ◽  
Local Descriptor

In multimedia data analysis, video tagging is the most challenging and active research area. In which finding or detecting the object with the dynamic environment is most challenging. Object detection and its validation are an essential functional step in video annotation. Considering the above challenges, the proposed system designed to presents the people detection module from a complex background. Detected persons are validated for further annotation process. Using publically available dataset for module design, Viola-Jones object detection algorithm is used for person detection. Support Vector Machine (SVM) authenticate the detected object/person based on it local features using Local Binary Pattern (LBP). The performance of the proposed system presents given architecture is effectively annotating the detected people emotion.

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