Spelling suggestions: "subject:"anline parameter identification"" "subject:"0nline parameter identification""
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Online Identification of Friction Coefficients in an Industrial RobotLängkvist, Martin January 2009 (has links)
<p>All mechanical systems with moving parts are affected by friction, including industrial robots. Being able to design an accurate friction model would further increase the performance of todays robots. Friction is a complex dynamic phenomena that is constantly changing depending on the state and environment of the robot. It is therefore beneficial to update the parameters of the friction model online. An estimate of the friction will be made using the feedback control signal with the help of a feedforward control scheme in a two axis simulation setup. The friction estimate is then used for an offline identification of three friction model parameters in a static Lugre friction model. Improvements on the identification will be done by introducing some shut-off rules that will improve the estimate. The normalized least mean square method (NLMS) will then be used to update the parameters online. A simulation of friction compensation with a fixed friction model, and with an adaptive friction model will be studied. The method will also be simulated using experimental data taken from a real industrial robot.</p>
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Sensorless Control of Permanent-Magnet Synchronous Motors Using Online Parameter Identification Based on System Identification TheoryIchikawa, Shinji, Tomita, Mutuwo, Doki, Shinji, Okuma, Shigeru January 2006 (has links)
No description available.
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Online Identification of Friction Coefficients in an Industrial RobotLängkvist, Martin January 2009 (has links)
All mechanical systems with moving parts are affected by friction, including industrial robots. Being able to design an accurate friction model would further increase the performance of todays robots. Friction is a complex dynamic phenomena that is constantly changing depending on the state and environment of the robot. It is therefore beneficial to update the parameters of the friction model online. An estimate of the friction will be made using the feedback control signal with the help of a feedforward control scheme in a two axis simulation setup. The friction estimate is then used for an offline identification of three friction model parameters in a static Lugre friction model. Improvements on the identification will be done by introducing some shut-off rules that will improve the estimate. The normalized least mean square method (NLMS) will then be used to update the parameters online. A simulation of friction compensation with a fixed friction model, and with an adaptive friction model will be studied. The method will also be simulated using experimental data taken from a real industrial robot.
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An Intelligent Battery Managment System For Electric And Hybrid Electric AircraftHashemi, Seyed Reza 24 March 2021 (has links)
No description available.
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