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Human-Machine Cooperative Decision Making
The research reported in this thesis focuses on the decision making aspect of human-machine cooperation and reveals new insights from theoretical modeling to experimental evaluations: Two mathematical behavior models of two emancipated cooperation partners in a cooperative decision making process are introduced. The model-based automation designs are experimentally evaluated and thereby demonstrate their benefits compared to state-of-the-art approaches.
Dynamical Modeling and Control of Multiphase Heat Transport Systems Based on Loop Heat Pipes
Effective heat transport systems in aerospace are based on multiphase loop heat pipes (LHPs). For a precise thermal control of the electronics, electrical heaters are additionally used to control the operating temperature of the LHP. This work focusses on the dynamical modeling and model-based control design for LHP-based heat transport systems. The results of this work can be used for the optimization of current control parameters and the efficient control design for future LHP applications.
Transactive Control of Coupled Electric Power and District Heating Networks
Der Entwurf von Ansätzen zur marktbasierten Betriebsführung zukünftiger Energienetze steht vor der technischen Herausforderung, eine enorme Anzahl von Netzteilnehmern zeitlich und örtlich zu koordinieren, um Erzeugung und Verbrauch auszugleichen und einen sicheren Netzbetrieb zu ermöglichen. Um dieser Herausforderung zu begegnen entstand das Forschungsfeld der Transactive Control Ansätze. In dieser Arbeit wird ein neuer Transactive Control Ansatz für gekoppelte Strom- und Wärmenetze vorgestellt. - The design of approaches for future market-based energy network operation faces the technical challenge of needing to coordinate a vast number of network participants spatially and temporally, in order to balance energy supply and demand, while achieving secure network operation. To meet this challenge, the research field of transactive control emerged. Within this work a new transactive control approach for coupled electric power and district heating networks is presented.
Dynamic Incentives for Optimal Control of Competitive Power Systems
This work presents a real-time dynamic pricing framework for future electricity markets. Deduced by first-principles analysis of physical, economic, and communication constraints within the power system, the proposed feedback control mechanism ensures both closed-loop system stability and economic efficiency at any given time. The resulting price signals are able to incentivize competitive market participants to eliminate spatio-temporal shortages in power supply quickly and purposively.
Self-Learning Longitudinal Control for On-Road Vehicles
Reinforcement Learning is a promising tool to automate controller tuning. However, significant extensions are required for real-world applications to enable fast and robust learning. This work proposes several additions to the state of the art and proves their capability in a series of real world experiments.
Guaranteed Verification of Dynamic Systems
This work introduces a new specification and verification approach for dynamic systems. The introduced approach is able to provide type II error free results by definition, i.e. there are no hidden faults in the verification result. The approach is based on Kaucher interval arithmetic to enclose the measurement in a bounded error sense. The developed methods are proven mathematically to provide a reliable verification for a wide class of safety critical systems.
Limited Information Shared Control and its Applications to Large Vehicle Manipulators
This work focuses on the Limited Information Shared Control and its controller design using potential games. Through the developed systematic controller design, the experiments demonstrate the effectiveness and superiority of this concept compared to traditional manual and non-cooperative control approaches in the application of large vehicle manipulators.
Automated Model Generation and Observer Design for Interconnected Systems : A Port-Hamiltonian Approach
This work addresses the automated generation of physical-based models and model-based observers. We develop port-Hamiltonian methods, which for the first time allow a complete and consistent automation of these two processes for a large class of interconnected systems.
Adaptive Dynamic Programming: Solltrajektorienfolgeregelung und Konvergenzbedingungen
In diesem Werk werden erstmals zeitdiskrete und zeitkontinuierliche Methoden präsentiert und analysiert, um flexible Solltrajektoriendarstellungen in Adaptive-Dynamic-Programming-Ansätze zu integrieren. Zudem werden theoretische Bedingungen an den Systemzustand hergeleitet, die eine zentrale Anregungseigenschaft für die Konvergenz der Adaption sicherstellen. Reale Anwendungen der vorgestellten adaptiven optimalen Trajektorienfolgeregelungsmethoden offenbaren das Potenzial dieser Ansätze. - In this work, discrete-time and continuous-time methods that integrate flexible reference trajectory representations into Adaptive Dynamic Programming approaches are presented and analyzed for the first time. Moreover, theoretical conditions on the system state are derived that ensure the persistent excitation property, which is crucial for the convergence of the adaptation. Real-world applications of the presented adaptive optimal trajectory tracking control methods reveal their potential.
Parameter- und Ordnungsidentifikation von fraktionalen Systemen mit einer Anwendung auf eine Lithium-Ionen-Batteriezelle
Für einen sicheren und effizienten Betrieb von Batteriezellen werden zunehmend modellbasierte Methoden eingesetzt. Zur Modellierung der Batteriezellen haben sich fraktionale Modelle, die durch nicht-ganzzahlige Ableitungsordnungen gekennzeichnet sind, aufgrund der elektrochemischen Interpretierbarkeit etabliert. In der Arbeit werden Verfahren zur Parameter- und Ableitungsordnungsidentifikation fraktionaler Systeme ohne Einschränkung bezüglich der Anregung zu Identifikationsbeginn hergeleitet. - Model-based methods are increasingly being used for a safe and efficient operation of battery cells. For modeling battery cells, fractional models which are characterized by non-integer derivative orders have become established due to their electrochemical interpretability. In this work, methods for parameter and derivative order identification of fractional systems are derived without restriction with respect to the excitation at the begin of identification.
