most citedNonlinear moving horizon estimation for robust state and parameter estimation -- extended version

3 citations · 3 across the 3 of their papers we have counts for

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eess.SY2026

Small-gain analysis of exponential incremental input/output-to-state stability for large-scale distributed systems

Christian Gatke, Julian D. Schiller, Matthias A. Müller

We provide a detectability analysis for nonlinear large-scale distributed systems in the sense of exponential incremental input/output-to-state stability (i-IOSS). In particular, w…

eess.SY20253 cited

Nonlinear moving horizon estimation for robust state and parameter estimation -- extended version

Julian D. Schiller, Matthias A. Müller

We propose a moving horizon estimation scheme to estimate the states and the unknown constant parameters of general nonlinear uncertain discrete-time systems. The proposed framewor…

eess.SY2025

Moving horizon estimation for nonlinear systems with time-varying parameters

Julian D. Schiller, Matthias A. Müller

We propose a moving horizon estimation scheme for estimating the states and time-varying parameters of nonlinear systems. We consider the case where observability of the parameters…

eess.SY2025

Event-triggered moving horizon estimation for nonlinear systems

Isabelle Krauss, Julian D. Schiller, Victor G. Lopez +1

This work proposes an event-triggered moving horizon estimation (ET-MHE) scheme for general nonlinear systems. The key components of the proposed scheme are a novel event-triggerin…

eess.SY2025

Sufficient Conditions for Detectability of Approximately Discretized Nonlinear Systems

Seth Siriya, Julian D. Schiller, Victor G. Lopez +1

In many sampled-data applications, observers are designed based on approximately discretized models of continuous-time systems, where usually only the discretized system is analyze…