Andreas Knoblach
Papers
3
Total Citations
32
H-Index
3
About
Andreas Knoblach is a specialist in the identification and control of complex robotic systems, with a primary focus on industrial manipulators. His research centers on developing advanced experimental methods for system identification, particularly for flexible joint robots with serial kinematics. Knoblach’s major contributions include pioneering techniques for estimating frequency response functions (FRFs) in closed-loop systems, a critical challenge in robotics where nonlinearities like Coulomb friction distort measurements. His most-cited work, “Experimental determination of frequency response function estimates for flexible joint industrial manipulators with serial kinematics” (2014, 22 citations), provides a practical framework for obtaining accurate dynamic models of these systems. He also advanced the field through the design of optimal excitation signals that minimize nonlinear disturbances, as detailed in his 2012 paper on closed-loop identification. Additionally, Knoblach has explored linear parameter-varying (LPV) gray box identification, creating low-complexity yet accurate models suitable for LPV controller design. His work bridges the gap between theoretical system identification and real-world industrial applications, enabling more precise control of robotic manipulators. With a career spanning foundational papers on closed-loop experiment design and model-based control, Knoblach’s research continues to influence the development of smarter, more responsive industrial robots.
Research Focus
Key Achievements
Top Papers
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- 3LPV gray box identification of industrial robots for control3 citations · 2012