75 citations · 309 across the 47 of their papers we have counts for
49 papers
Turnpike properties in nonlinear system identification
Julian D. Schiller, Matthias A. Müller
We analyze the problem of learning general discrete-time nonlinear state-space models using the simulation error minimization (SEM) method. In this setting, model parameters are ty…
Local Observability and Moving Horizon Estimation-based Training of Feedforward Neural Networks
Yi Yang, Victor G. Lopez, Matthias A. Müller
In this paper, we propose a moving horizon estimation (MHE)-based training method for feedforward neural networks (FNNs) with rectified linear unit (ReLU) activation functions to d…
On stability and non-averaged performance of economic MPC with terminal conditions for optimal periodic operation
Jonas Mair, Lukas Schwenkel, Matthias A. Müller +1
Operation at steady state is often not optimal when optimizing over an economic cost objective. In many cases, periodic operation yields better performance. Therefore, we derive as…
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…
An Output Feedback Q-learning Algorithm for Optimal Control of Nonlinear Systems with Koopman Linear Embedding
Victor G. Lopez, Malte Heinrich, Matthias A. Müller
In the reinforcement learning literature, strong theoretical guarantees have been obtained for algorithms applicable to LTI systems. However, in the nonlinear case only weaker resu…
Sample-based detectability and moving horizon state estimation of continuous-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this paper we propose a detectability condition for nonlinear continuous-time systems with irregular/infrequent output measurements, namely a sample-based version of incremental…
On Data-based Nash Equilibria in LQ Nonzero-sum Differential Games
Victor G. Lopez, Matthias A. Müller
This paper considers data-based solutions of linear-quadratic nonzero-sum differential games. Two cases are considered. First, the deterministic game is solved and Nash equilibrium…
Inference in Latent Force Models Using Optimal State Estimation
Tobias M. Wolff, Victor G. Lopez, Matthias A. Müller +1
Latent force models, a class of hybrid modeling approaches, integrate physical knowledge of system dynamics with a latent force - an unknown, unmeasurable input modeled as a Gaussi…
Data-based Moving Horizon Estimation under Irregularly Measured Data
Tobias M. Wolff, Isabelle Krauss, Victor G. Lopez +1
In this work, we introduce a sample- and data-based moving horizon estimation framework for linear systems. We perform state estimation in a sample-based fashion in the sense that…
Estimating Hormone Concentrations in the Pituitary-Thyroid Feedback Loop from Irregularly Sampled Measurements
Seth Siriya, Tobias M. Wolff, Isabelle Krauss +2
Model-based control techniques have recently been investigated for the recommendation of medication dosages to address thyroid diseases. These techniques often rely on knowledge of…
Data-driven stabilization of nonlinear systems via descriptor embedding
Mohammad Alsalti, Claudio De Persis, Victor G. Lopez +1
We introduce the notion of descriptor embedding for nonlinear systems and use it for the data-driven design of stabilizing controllers. Specifically, we provide sufficient data-dep…
Robust stability of event-triggered nonlinear moving horizon estimation
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
In this work, we propose an event-triggered moving horizon estimation (ET-MHE) scheme for the remote state estimation of general nonlinear systems. In the presented method, wheneve…
Local Observability of a Class of Feedforward Neural Networks
Yi Yang, Victor G. Lopez, Matthias A. Müller
Beyond the traditional neural network training methods based on gradient descent and its variants, state estimation techniques have been proposed to determine a set of ideal weight…
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…
Insights into the explainability of Lasso-based DeePC for nonlinear systems
Gianluca Giacomelli, Simone Formentin, Victor G. Lopez +2
Data-enabled Predictive Control (DeePC) has recently gained the spotlight as an easy-to-use control technique that allows for constraint handling while relying on raw data only. In…
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…
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…
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…
Disturbance feedback-based model predictive control in uncertain dynamic environments
Philipp Buschermöhle, Taouba Jouini, Torsten Lilge +1
This paper presents a robust MPC scheme for linear systems subject to time-varying, uncertain constraints that arise from uncertain environments. The predicted input sequence is pa…
Data-Based System Representation and Synchronization for Multiagent Systems
Victor G. Lopez, Matthias A. Müller
This paper presents novel solutions of the data-based synchronization problem for continuous-time multiagent systems. We consider the cases of homogeneous and heterogeneous systems…
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…
Data-Based Control of Continuous-Time Linear Systems with Performance Specifications
Victor G. Lopez, Matthias A. Müller
The design of direct data-based controllers has become a fundamental part of control theory research in the last few years. In this paper, we consider three classes of data-based s…
Online convex optimization for robust control of constrained dynamical systems
Marko Nonhoff, Emiliano Dall'Anese, Matthias A. Müller
This article investigates the problem of controlling linear time-invariant systems subject to time-varying and a priori unknown cost functions, state and input constraints, and exo…
Sample-based nonlinear detectability for discrete-time systems
Isabelle Krauss, Victor G. Lopez, Matthias A. Müller
This paper introduces two sample-based formulations of incremental input/output-to-state stability (i-IOSS), a suitable detectability notion for general nonlinear systems. In this…