4 accepted papers
This paper presents a data-driven control optimization framework for flexible joint robots (FJR) based on frequency response function (FRF) data, enabling automated controller synthesis without explicit model identification. Unlike conventional model-based approaches that rely on accurate parameter
This paper presents a data-driven control optimization framework for flexible joint robots (FJR) based on frequency response function (FRF) data, enabling automated controller synthesis without explicit model identification. Unlike conventional model-based approaches that rely on accurate parameter …
This paper presents a novel, nonlinearity robust identification method for deriving the inertia matrix of multi-DOF Flexible Joint Robots (FJR), utilizing resonance and anti-resonance frequencies in the Frequency Response Functions (FRF). Our proposed method overcomes the limitations of conventional…
Control of tasks by Flexible Joint Robots (FJR) is highly susceptible to disturbances, coupling, and vibrations that result from joint elasticity. A possible solution to this problem is a Disturbance Observer (DOB), which can address these issues in the joint space. However, this approach has limita