A
Andreas Kugi
Researcher at Vienna University of Technology
Publications - 463
Citations - 5565
Andreas Kugi is an academic researcher from Vienna University of Technology. The author has contributed to research in topics: Feed forward & Control theory. The author has an hindex of 31, co-authored 430 publications receiving 4548 citations. Previous affiliations of Andreas Kugi include Johannes Kepler University of Linz & Festo.
Papers
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Journal ArticleDOI
On the Passivity-Based Impedance Control of Flexible Joint Robots
TL;DR: A novel type of impedance controllers for flexible joint robots with physical interpretation as a scaling of the motor inertia and the physical interpretation of torque feedback allows a proof of the asymptotic stability of the closed-loop system based on the passivity properties of the system.
Journal ArticleDOI
Unscented Kalman filter for vehicle state estimation
TL;DR: In this article, an unscented Kalman filter is used for estimation purposes, since it is based on a numerically efficient nonlinear stochastic estimation technique, and an advanced vertical tyre load calculation method is developed that additionally considers the vertical tyre stiffness and increases the estimation accuracy.
Journal ArticleDOI
Tracking control for boundary controlled parabolic PDEs with varying parameters: Combining backstepping and differential flatness
Thomas Meurer,Andreas Kugi +1 more
TL;DR: The combination of backstepping-based state-feedback control and flatness-based trajectory planning and feedforward control is considered for the design of an exponentially stabilizing tracking controller for a linear diffusion-convection-reaction system with spatially and temporally varying parameters and nonlinear boundary input.
Proceedings ArticleDOI
A passivity based Cartesian impedance controller for flexible joint robots - part I: torque feedback and gravity compensation
TL;DR: It is shown that the closed loop system can be seen as a feedback interconnection of passive systems, and a proof of asymptotic stability is presented.
Journal ArticleDOI
Stability and Incremental Improvement of Suboptimal MPC Without Terminal Constraints
Knut Graichen,Andreas Kugi +1 more
TL;DR: The stability of suboptimal model predictive control without terminal constraints is investigated for continuous-time nonlinear systems under input constraints and the decay of the optimization error shows the incremental improvement of theSuboptimal MPC scheme.