Vibration and motion control design and trade-off for high-performance mechatronic systems

2006 ◽  
Author(s):  
Diederik Verscheure ◽  
Bart Paijmans ◽  
Hendrik Brussel ◽  
Jan Swevers
Keyword(s):  
Motion Control ◽  
High Performance ◽  
Control Design ◽  
Mechatronic Systems ◽  
Trade Off

Advances in High-Performance Motion Control of Mechatronic Systems

2017 ◽  
Author(s):  
Takashi Yamaguchi ◽  
Mitsuo Chee ◽  
Khiang Pang Chee
Keyword(s):  
Motion Control ◽  
High Performance ◽  
Mechatronic Systems

Special Issue on 2nd International Conference on Recent Advances in Mechatronics (ICRAM'99)

2000 ◽  
Vol 12 (3) ◽  
pp. 193-193
Author(s):  
Toshiro Noritsugu ◽  
Keyword(s):  
Adaptive Control ◽  
Mobile Robots ◽  
Motion Control ◽  
Control Design ◽  
Robust Adaptive Control ◽  
Magnetic Suspension ◽  
Special Issue ◽  
Mechatronic Systems ◽  
Recent Advances ◽  
Systems Control

ICRAM'99 has been organized by UNESCO Chair on Mechatronics and Mechatronics Research and Application Center of Bogazici University, Istanbul in Turkey, during 24-26 May 1999, co-sponsored by IEEE (Institute of Electrical and Electronics Engineers) Industrial Electronics Society and IEEE Robotics and Automation Society. The purpose of this conference is to provide an international forum for the discussion on the most recent advances in the field of mechatronics. The program of the conference contains three kinds of papers, 4 plenary papers, 44 long papers and 90 regular papers. The long papers have been published by Springer-Verlag (ISBN 981-4021-34-2), under the name Recent Advances in Mechatronics (Eds. Okyay Kaynak, Sabri Tosunoglu and Marcelo Ang Jr.). The long papers have been presented in the following 12 sessions: Advances in Robotics, Motion control 1, Intelligent Techniques in Mechatronics 1, Virtual Techniques and Telecommanding, Robust Adaptive Control, Design of Mechanical System 1, Fault Detection and Inspection 1, Motion Control 2, Intelligent Techniques in Mechatronics 2, Analysis of Mechatronic Systems, Mobile Robots 1 and Biomedical Applications. For the regular papers, Modeling and Simulation, Trajectory Planning and Control, Variable-Structure Control Systems, Control of Mechatronic Systems, Production Automation, Machine Vision, Adaptive Control, Design of Mechatronic Systems 2, Measurement Technology, Intelligent Systems, Control of Robot Manipulators, Flexible Manufacturing Systems, Education and Training in Mechatronics, Neural Networks and Applications, Fuzzy Systems, Hydraulic and Pneumatic Applications, Mobile Robots 2, Control Applications and Sensors and Actuators. The papers have been submitted to the conference from 30 countries in the world. From Japan 14 papers have been presented, one plenary paper, S long papers and 8 regular papers. This special issue comprises 10 papers edited from the conference papers contributed from Japan. Each paper has been revised and updated for this issue from the original conference paper to describe the recent status of research and development of mechatronics in Japan. The included papers are concerned with some important and attractive subjects such as mobile robot, robot behavior evolution, nanoelectromechanical system, magnetic suspension, human symbiotic robot, stereovision, force control of robot, soft pneumatic actuator and so on. I would like to thank all the authors for their valuable contributions to this issue.

scholarly journals Statistical and machine learning models for optimizing energy in parallel applications

2019 ◽  
Vol 33 (6) ◽  
pp. 1079-1097 ◽  
Author(s):  
Mark Endrei ◽  
Chao Jin ◽  
Minh Ngoc Dinh ◽  
David Abramson ◽  
Heidi Poxon ◽  
...  
Keyword(s):  
Machine Learning ◽  
Energy Efficiency ◽  
High Performance ◽  
Large Scale ◽  
Energy Use ◽  
Parallel Applications ◽  
Learning Models ◽  
Trade Off ◽  
Time Required ◽  
Machine Learning Models

Rising power costs and constraints are driving a growing focus on the energy efficiency of high performance computing systems. The unique characteristics of a particular system and workload and their effect on performance and energy efficiency are typically difficult for application users to assess and to control. Settings for optimum performance and energy efficiency can also diverge, so we need to identify trade-off options that guide a suitable balance between energy use and performance. We present statistical and machine learning models that only require a small number of runs to make accurate Pareto-optimal trade-off predictions using parameters that users can control. We study model training and validation using several parallel kernels and more complex workloads, including Algebraic Multigrid (AMG), Large-scale Atomic Molecular Massively Parallel Simulator, and Livermore Unstructured Lagrangian Explicit Shock Hydrodynamics. We demonstrate that we can train the models using as few as 12 runs, with prediction error of less than 10%. Our AMG results identify trade-off options that provide up to 45% improvement in energy efficiency for around 10% performance loss. We reduce the sample measurement time required for AMG by 90%, from 13 h to 74 min.

scholarly journals Calculating the optimal hematocrit under the constraint of constant cardiac power

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Michal Sitina ◽  
Heiko Stark ◽  
Stefan Schuster
Keyword(s):  
Blood Flow ◽  
High Performance ◽  
Animal Species ◽  
Normal Values ◽  
Mechanical Load ◽  
The Body ◽  
Trade Off ◽  
Cardiac Power ◽  
Optimal Value ◽  
Good Agreement

AbstractIn humans and higher animals, a trade-off between sufficiently high erythrocyte concentrations to bind oxygen and sufficiently low blood viscosity to allow rapid blood flow has been achieved during evolution. Optimal hematocrit theory has been successful in predicting hematocrit (HCT) values of about 0.3–0.5, in very good agreement with the normal values observed for humans and many animal species. However, according to those calculations, the optimal value should be independent of the mechanical load of the body. This is in contradiction to the exertional increase in HCT observed in some animals called natural blood dopers and to the illegal practice of blood boosting in high-performance sports. Here, we present a novel calculation to predict the optimal HCT value under the constraint of constant cardiac power and compare it to the optimal value obtained for constant driving pressure. We show that the optimal HCT under constant power ranges from 0.5 to 0.7, in agreement with observed values in natural blood dopers at exertion. We use this result to explain the tendency to better exertional performance at an increased HCT.

Trade-Off Analysis for the Design of a High Performance Hydrostatic Actuation System

2000 ◽  
Author(s):  
S. R. Habibi
Keyword(s):  
Mathematical Modeling ◽  
Quadratic Programming ◽  
High Performance ◽  
Design Parameters ◽  
Mathematical Functions ◽  
Trade Off ◽  
Actuation System ◽  
Trade Offs ◽  
Expected Performance ◽  
Dominant Design

Abstract This paper considers the design of a high performance hydrostatic actuation system referred to as the ElectroHydraulic Actuator (EHA). The expected performance of EHA and its dominant design parameters are identified by using mathematical modeling. The design parameters are classified into Direct and Indirect categories based on the measure of their accessibility to the designer. The Direct parameters are directly quantifiable and, can be linked to the performance of EHA through a set of mathematical functions. A prototype of EHA has been produced and described. The mathematical functions linking performance to design parameters are used to investigate design trade-offs. Design improvements to the prototype are suggested by using constrained quadratic programming.

Age and Performance Under Pressure

2012 ◽  
pp. 134-152 ◽  
Author(s):  
Harold O. Fried ◽  
Loren W. Tauer
Keyword(s):  
Correlation Coefficient ◽  
High Performance ◽  
Age Distribution ◽  
Mental Ability ◽  
Trade Off ◽  
Athletic Ability ◽  
Front End ◽  
Ladies Professional Golf Association ◽  
And Performance ◽  
Performance Under Pressure

This article explores how well an individual manages his or her own talent to achieve high performance in an individual sport. Its setting is the Ladies Professional Golf Association (LPGA). The order-m approach is explained. Additionally, the data and the empirical findings are presented. The inputs measure fundamental golfing athletic ability. The output measures success on the LPGA tour. The correlation coefficient between earnings per event and the ability to perform under pressure is 0.48. The careers of golfers occur on the front end of the age distribution. There is a classic trade-off between the inevitable deterioration in the mental ability to handle the pressure and experience gained with time. The ability to perform under pressure peaks at age 37.

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