9 papers · 1 filter
Computing the Hard Scaled Relative Graph of LTI Systems
Julius P. J. Krebbekx, Eder Baron-Prada, Roland Tóth +1
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems, where Linear Time-Invariant (LTI) systems are the fundamental…
Tensor-based reduction of linear parameter-varying state-space models
Bogoljub Terzin, E. Javier Olucha, Amritam Das +2
The Linear Parameter-Varying (LPV) framework is a powerful tool for controlling nonlinear and complex systems, but the conversion of nonlinear models into LPV forms often results i…
Scaled Relative Graph Analysis of General Interconnections of SISO Nonlinear Systems
Julius P. J. Krebbekx, Roland Tóth, Amritam Das
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. However, we show that the current SRG analysis suffers from a…
Analysis of Non-Square Nonlinear MIMO Systems using Scaled Relative Graphs
Julius P. J. Krebbekx, Roland Tóth, Amritam Das
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems. There have been recent efforts to generalize SRG analysis to…
Reset Controller Analysis and Design for Unstable Linear Plants using Scaled Relative Graphs
Julius P. J. Krebbekx, Roland Tóth, Amritam Das
In this technical communique, we develop a graphical design procedure for reset controllers for unstable LTI plants based on recent developments on Scaled Relative Graph analysis,…
Nonlinear Bandwidth and Bode Diagrams based on Scaled Relative Graphs
Julius P. J. Krebbekx, Roland Tóth, Amritam Das
Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of Nonlinear (NL) systems. In this paper, we restrict the SRG to particular input s…
On-the-fly Surrogation for Complex Nonlinear Dynamics
E. Javier Olucha, Rajiv Singh, Amritam Das +1
High-fidelity models are essential for accurately capturing nonlinear system dynamics. However, simulation of these models is often computationally too expensive and, due to their…
ON-Traffic: An Operator Learning Framework for Online Traffic Flow Estimation and Uncertainty Quantification from Lagrangian Sensors
Jake Rap, Amritam Das
Accurate traffic flow estimation and prediction are critical for the efficient management of transportation systems, particularly under increasing urbanization. Traditional methods…
Automated Linear Parameter-Varying Modeling of Nonlinear Systems: A Global Embedding Approach
E. Javier Olucha, Patrick J. W. Koelewijn, Amritam Das +1
In this paper, an automated Linear Parameter-Varying (LPV) model conversion approach is proposed for nonlinear dynamical systems. The proposed method achieves global embedding of t…