4 papers
Optimal state estimation: Turnpike analysis and performance results
Julian D. Schiller, Lars Grüne, Matthias A. Müller
In this paper, we introduce turnpike arguments in the context of optimal state estimation. In particular, we show that the optimal solution of the state estimation problem involvin…
Relevance-driven Input Dropout: an Explanation-guided Regularization Technique
Shreyas Gururaj, Lars Grüne, Wojciech Samek +2
Overfitting is a well-known issue extending even to state-of-the-art (SOTA) Machine Learning (ML) models, resulting in reduced generalization, and a significant train-test performa…
Performance guarantees for optimization-based state estimation using turnpike properties
Julian D. Schiller, Lars Grüne, and Matthias A. Müller
In this paper, we develop novel accuracy and performance guarantees for optimal state estimation of general nonlinear systems (in particular, moving horizon estimation, MHE). Our r…
Stabilization of Strictly Pre-Dissipative Receding Horizon Linear Quadratic Control by Terminal Costs
Mario Zanon, Lars Grüne
Asymptotic stability in receding horizon control is obtained under a strict pre-dissipativity assumption, in the presence of suitable state constraints. In this paper we analyze ho…