6 papers
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…