Company Filing History:
Years Active: 2016-2019
Title: Innovations by Inventor Markus Stadlbauer
Introduction
Markus Stadlbauer is an innovative inventor based in Vienna, Austria. With a focus on technical systems, he has made significant contributions to the field through his patented methods. His work emphasizes the importance of nonlinear relationships in system modeling and data acquisition within complex environments.
Latest Patents
Markus Stadlbauer holds two patents, showcasing his dedication to advancing technology. His latest innovations include:
1. **Method for Determining a Model of an Output Quantity of a Technical System**: This method aims to create a model for an output quantity (y) of a technical system that behaves nonlinearly depending on various input quantities. It defines a target output quantity range (COR) and selects associated input quantity vectors (u) using a distance-based selection criterion for parameterizing the model.
2. **Machine-Implemented Method for Obtaining Data from a Nonlinear Dynamic Real System During a Test Run**: This patent describes a method for data acquisition from systems such as internal combustion engines or drivetrains. It involves generating dynamic excitation signals and measuring system outputs, with the goal of optimizing the experimental design for better measurement and modeling.
Career Highlights
Markus Stadlbauer is currently associated with AVL List GmbH, a prominent company known for its commitment to engineering and technology solutions. He has dedicated his career to innovating methods that improve system efficiency and data analysis within technical environments.
Collaborations
Throughout his career, Markus has collaborated with talented individuals such as Christoph Hametner and Stefan Jakubek. These partnerships have allowed for the exchange of ideas and have further driven advancements in their respective fields.
Conclusion
Markus Stadlbauer's contributions to the field of technical systems through his patents reflect his innovative spirit and commitment to enhancing technology. His work continues to influence how complex systems are understood and optimized, paving the way for future advancements in engineering and data analysis.