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Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Friction Model Parameter Identification of a Servomotor with Genetic Algorithms
Friction has been identified as one of the primary contributors to the problems associated with motion control system accuracy. Several approaches have been offered to identify friction parameters, such as direct measurement, trial-and-error, and so on. However, obtaining the proper and exact values for friction model parameters is a challenging task. The aforementioned methods have large time consumption and likely yield experimental errors. In this paper, a Genetic Algorithm is used to identify friction model parameters for a servomotor system, namely, the Quanser QUBE-Servo 2. Both simulation and experiment findings demonstrate that a successful implementation of friction parameter identification can be done in a short amount of time while maintaining high accuracy.
Friction Model Parameter Identification of a Servomotor with Genetic Algorithms
Friction has been identified as one of the primary contributors to the problems associated with motion control system accuracy. Several approaches have been offered to identify friction parameters, such as direct measurement, trial-and-error, and so on. However, obtaining the proper and exact values for friction model parameters is a challenging task. The aforementioned methods have large time consumption and likely yield experimental errors. In this paper, a Genetic Algorithm is used to identify friction model parameters for a servomotor system, namely, the Quanser QUBE-Servo 2. Both simulation and experiment findings demonstrate that a successful implementation of friction parameter identification can be done in a short amount of time while maintaining high accuracy.
Friction Model Parameter Identification of a Servomotor with Genetic Algorithms
Ahmad, Saleh (Autor:in) / Alhashmi, Ahmad (Autor:in) / Khan, Najeeb U. (Autor:in)
20.02.2023
851067 byte
Aufsatz (Konferenz)
Elektronische Ressource
Englisch
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