Publikationen

• Abschlussbericht Projekt OBSERVE, 2019
• Workshop: Nichtwohngebäude energieeffizient betreiben, Hamburg, 2017
• SEWE, E., PANGALOS, G., LICHTENBERG, G.: Approaches to Fault Detection for Heating Systems Using CP Tensor Decompositions, Advances in Intelligent Systems and Computing, Band 873, Springer 2018; 128-152.
• LAUTENSCHLAGER, B., PFEIFFER, S., SCHMIDT, C., LICHTENBERG, G.: Real-Time Iterative Learning Control – Two applications with time scales between years and nanoseconds, International Journal of adaptive control and signal processing, 2018;1–2.
• KRUPPA, K., LICHTENBERG, G.: Feedback Linearization of Multilinear Time-Invariant Systems Using Tensor Decomposition Methods, 8th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, Porto, 2018.
• SEWE, E., PANGALOS, G., LICHTENBERG, G.: Fault Detection for Heating Systems using Tensor Decompositions of Multi-Linear Models,7th International Conference on Simulation and Modeling Methodologies, Technologies and Applications, Madrid 2017.
• MÜLLER-EPING, T., LICHTENBERG, G., VOGELMANN, V.: Fault Detection Algorithms based on Decomposed Tensor Representations for Qualitative Models, 20th IFAC World Congress, Toulouse 2017.
• KRUPPA, K.: Comparison of Tensor Decomposition Methods for Simulation of Multilinear Time-Invariant Systems with the MTI Toolbox,20th IFAC World Congress, Toulouse 2017.
• KRUPPA, K., LICHTENBERG, G.: Decentralized State Feedback Design for Multilinear Time-Invariant Systems, 20th IFAC World Congress, Toulouse 2017.
• KRUPPA, K., MÜLLER, T., LAUTENSCHLAGER, B., LICHTENBERG, G., RÉHAULT, N.:State Space Models as a common tool for Control design, Optimization and Fault detection in Building Systems,BauSIM, Dresden 2016.
• MÜLLER, T., LICHTENBERG, G.:Fault Detection with CP-Decomposed Qualitative Models,4th IFAC International Conference on Intelligent Control and Automation Sciences, Reims 2016.
• LAUTENSCHLAGER, B., LICHTENBERG, G.:Data-driven Iterative Learning for Model Predictive Control of Heating Systems,12th IFAC International Workshop on Adaptation and Learning in Control and Signal Processing, Eindhoven 2016.
• KRUPPA, K., LICHTENBERG, G.: Comparison of CP Tensors, Tucker Tensors and Tensor Trains for Representation of Right Hand Sides of Ordinary Differential Equations, TDA 2016, Workshop on Tensor Decompositions and Applications, Leuven 2016.
• REESE, K:Automatische Erfassung von Energiedaten – Herausforderungen und Lösungen, INservFM, Messe und Kongress für Facility Management und Industrieservice, Frankfurt 2016.
• LAUTENSCHLAGER, B., KRUPPA, K., LICHTENBERG, G.: Convexity Properties of the Model Predictive Control Problem for Subclasses of Multilinear Time-Invariant Systems, 5th IFAC Conference on Nonlinear Model Predictive Control, Sevilla 2015.
• MÜLLER, T., KRUPPA, K., LICHTENBERG, G., RÉHAULT, N.: Fault Detection with Qualitative Models reduced by Tensor Decomposition methods,9th IFAC Symposium on Fault Detection, Supervision and Safety for Technical Processes SAFEPROCESS’15, Paris 2015.
• MINT-STUDIUM Hamburg – Regelungstechnik