3 citations · 7 across the 15 of their papers we have counts for
15 papers
Validation of a Computational Respiratory System Model for Mechanical Ventilation
Carlotta Hennigs, Charlott Danielson, Franziska Bilda +7
Computational modeling and simulation have emerged as powerful tools for assessing medical device performance and safety, particularly in silico clinical trials (ISCTs) for automat…
LPV Updates for Sequentially Linearized Moving Horizon Estimation of Nonlinear Systems
Jiaxin Ji, Jan Heiland, Dimitrios S. Karachalios +1
Moving horizon estimation (MHE) provides high precision state estimation for nonlinear systems, but it is often limited by the substantial computational demands of solving a nonlin…
Stochastic Error Bounds in Nonlinear Model Predictive Control with Gaussian Processes via Parameter-Varying Embeddings
Dimitrios S. Karachalios, Hossam S. Abbas
This study utilized the Gaussian Processes (GPs) regression framework to establish stochastic error bounds between the actual and predicted state evolution of nonlinear systems. Th…
Obstacle Avoidance of Autonomous Vehicles: An LPVMPC with Scheduling Trust Region
Maryam Nezami, Dimitrios S. Karachalios, Georg Schildbach +1
Reference tracking and obstacle avoidance rank among the foremost challenging aspects of autonomous driving. This paper proposes control designs for solving reference tracking prob…
Closed-Loop Identification and Tracking Control of a Ballbot
Tobias Fischer, Dimitrios S. Karachalios, Ievgen Zhavzharov +1
Identifying and controlling an unstable, underactuated robot to enable reference tracking is a challenging control problem. In this paper, a ballbot (robot balancing on a ball) is…
Efficient Nonlinear MPC by Leveraging LPV Embedding and Sequential Quadratic Programming
Dimitrios S. Karachalios, Hossam S. Abbas
In this paper, we present efficient solutions for the nonlinear program (NLP) associated with nonlinear model predictive control (NMPC) by leveraging the linear parameter-varying (…
Parameter Refinement of a Ballbot and Predictive Control for Reference Tracking with Linear Parameter-Varying Embedding
Dimitrios S. Karachalios, Hossam S. Abbas
In this study, we implement a control method for stabilizing a ballbot that simultaneously follows a reference. A ballbot is a robot balancing on a spherical wheel where the single…
Error Bounds in Nonlinear Model Predictive Control with Linear Differential Inclusions of Parametric-Varying Embeddings
Dimitrios S. Karachalios, Maryam Nezami, Georg Schildbach +1
In this work, we provide deterministic error bounds for the actual state evolution of nonlinear systems embedded with the linear parametric variable (LPV) formulation and steered b…
On the Design of Nonlinear MPC and LPVMPC for Obstacle Avoidance in Autonomous Driving
Maryam Nezami, Dimitrios S. Karachalios, Georg Schildbach +1
In this study, we are concerned with autonomous driving missions when a static obstacle blocks a given reference trajectory. To provide a realistic control design, we employ a mode…
Data-driven quadratic modeling in the Loewner framework from input-output time-domain measurements
D. S. Karachalios, I. V. Gosea, L. Gkimisis +1
In this study, we present a purely data-driven method that uses the Loewner framework (LF) along with nonlinear optimization techniques to infer quadratic with affine control dynam…
Bilinear realization from input-output data with neural networks
Dimitrios S. Karachalios, Ion Victor Gosea, Kirandeep Kour +1
We present a method that connects a well-established nonlinear (bilinear) identification method from time-domain data with neural network (NNs) advantages. The main challenge for f…
A framework for fitting quadratic-bilinear systems with applications to models of electrical circuits
Dimitrios S. Karachalios, Ion Victor Gosea, Athanasios C. Antoulas
In this contribution, we propose a data-driven procedure to fit quadratic-bilinear surrogate models from data. Although the dynamics characterizing the original model are strongly…
Learning reduced-order models of quadratic control systems from input-output data
Ion Victor Gosea, Dimitrios S. Karachalios, Athanasios C. Antoulas
In this paper, we address an extension of the Loewner framework for learning quadratic control systems from input-output data. The proposed method first constructs a reduced-order…
On Bilinear Time Domain Identification and Reduction in the Loewner Framework
D. S. Karachalios, I. V. Gosea, A. C. Antoulas
The Loewner framework-(LF) in combination with Volterra series-(VS) offers a non-intrusive approximation method that is capable of identifying bilinear models from time-domain meas…
Case study: Approximations of the Bessel Function
D. S. Karachalios, I. V. Gosea, Q. Zhang +1
The purpose of this note is to compare various approximation methods as applied to the inverse of the Bessel function of the first kind, in a given domain of the complex plane.