Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans
The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, r...
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| Year of Publication: | 2021 |
| Language: | English |
| Physical Description: | 1 electronic resource (256 p.) |
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(CKB)5400000000042506 (oapen)https://directory.doabooks.org/handle/20.500.12854/77012 (EXLCZ)995400000000042506 |
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Cuadrado, Javier edt Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans Basel, Switzerland MDPI - Multidisciplinary Digital Publishing Institute 2021 1 electronic resource (256 p.) text txt rdacontent computer c rdamedia online resource cr rdacarrier The combination of physical sensors and computational models to provide additional information about system states, inputs and/or parameters, in what is known as virtual sensing, is becoming increasingly popular in many sectors, such as the automotive, aeronautics, aerospatial, railway, machinery, robotics and human biomechanics sectors. While, in many cases, control-oriented models, which are generally simple, are the best choice, multibody models, which can be much more detailed, may be better suited to some applications, such as during the design stage of a new product. English Technology: general issues bicssc Kalman filter motion capture gait analysis inertial sensor rail vehicles track irregularities multibody dynamics inertial sensors computer vision singular configuration parallel robot motion control 3D tracking screw theory Kalman filtering coupled states-inputs estimation virtual sensors slider-crank mechanism virtual sensoring physical sensors smart/intelligent sensors sensor technology and applications sensing principles signal processing in sensor systems symbolic generation real-time computation human-in-the-loop haptic devices parameter estimation curve fitting method hydraulic system predictive maintenance characteristic curve product life cycle digital twin adaptive Kalman filter nonlinear models virtual sensing multibody based observers vehicle dynamics estimation sideslip angle estimation factor graph graphical models movable repetitive lander fault-tolerant soft-landing landing configuration stability optimization 3-0365-2357-X 3-0365-2358-8 Naya, Miguel edt Cuadrado, Javier oth Naya, Miguel oth |
| language |
English |
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eBook |
| author2 |
Naya, Miguel Cuadrado, Javier Naya, Miguel |
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Naya, Miguel Cuadrado, Javier Naya, Miguel |
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j c jc m n mn |
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HerausgeberIn Sonstige Sonstige |
| title |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| spellingShingle |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_full |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_fullStr |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_full_unstemmed |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_auth |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_new |
Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
| title_sort |
combining sensors and multibody models for applications in vehicles, machines, robots and humans |
| publisher |
MDPI - Multidisciplinary Digital Publishing Institute |
| publishDate |
2021 |
| physical |
1 electronic resource (256 p.) |
| isbn |
3-0365-2357-X 3-0365-2358-8 |
| illustrated |
Not Illustrated |
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Combining Sensors and Multibody Models for Applications in Vehicles, Machines, Robots and Humans |
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