6 papers · 1 filter
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…
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…
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…