Machine learning with nonlinear state space models
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Max Schüssler
Dr.-Ing. Max Schüssler was a research assistant with the working group Automatic Control – Mechatronics of Prof. Dr.-Ing. Oliver Nelles. In his work he focuses on machine learning perspectives for nonlinear system identification and adjacent research fields.
Abstract
In this dissertation, a novel class of model structures and associated training algorithms for building data-driven nonlinear state space models is developed. The new identification procedure with the resulting model is called local model state space network (LMSSN). Furthermore, recurrent neural networks (RNNs) and their similarities to nonlinear state space models are elaborated on. The overall outstanding performance of the LMSSN is demonstrated on various applications.
Zusammenfassung
In dieser Disseration wird eine neue Klasse von Modellstrukturen und dazugehörigen Trainingsalgorithmen für die datengetriebene Modellierung von nichtlinearen dynamischen Prozessen entwickelt. Der neue Identifikationsalgorithmus mit resultierendem Modell heißt Local Model State Space Network (LMSSN). Außerdem werden rekurrente neuronale Netze (RNNs) und deren Ähnlichkeit zu nichtlinearen Zustandsraummodellen behandelt. Die insgesamt herausragende Leistungsfähigkeit von LMSSN wird anhand einiger Anwendungsbeispiele demonstriert.
About the author
Dr.-Ing. Max Schüssler was a research assistant with the working group Automatic Control – Mechatronics of Prof. Dr.-Ing. Oliver Nelles. In his work he focuses on machine learning perspectives for nonlinear system identification and adjacent research fields.
© 2022 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- Editorial
- Special issue: AUTOMED 2021: Automation in Medical Technology
- Methods
- Score rectification for online assessments in robot-assisted arm rehabilitation
- Concept for the testing of automated functions in therapeutic medical devices
- Applications
- Model-based analysis and optimization of pressure-controlled ventilation of COPD patients in relation to BMI
- Non-occlusive pumping principle for blood pump application
- Determining relationship between bone screw insertion torque and insertion speed
- Model predictive control for retinal laser treatment at 1 kHz
- PoRi device: portable hand assessment and rehabilitation after stroke
- Hardware development and control of a motorized rollator as an extension for exoskeletons
- Dissertations
- Machine learning with nonlinear state space models
- Perönliches
- Nachruf: Prof. Dr. rer. nat. Henning Tolle verstorben
Artikel in diesem Heft
- Frontmatter
- Editorial
- Special issue: AUTOMED 2021: Automation in Medical Technology
- Methods
- Score rectification for online assessments in robot-assisted arm rehabilitation
- Concept for the testing of automated functions in therapeutic medical devices
- Applications
- Model-based analysis and optimization of pressure-controlled ventilation of COPD patients in relation to BMI
- Non-occlusive pumping principle for blood pump application
- Determining relationship between bone screw insertion torque and insertion speed
- Model predictive control for retinal laser treatment at 1 kHz
- PoRi device: portable hand assessment and rehabilitation after stroke
- Hardware development and control of a motorized rollator as an extension for exoskeletons
- Dissertations
- Machine learning with nonlinear state space models
- Perönliches
- Nachruf: Prof. Dr. rer. nat. Henning Tolle verstorben
