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Item type:Publication, Access status: with files , Data-driven feedback optimization for particle accelerator application(De Gruyter, 2025-06-01); ; ; ; For many engineering problems involving control systems, finding a good working point for steady-state operation is crucial. Therefore, this paper presents an application of steady-state optimization with feedback on particle accelerators, specifically the European X-ray free-electron laser. In simulation studies, we demonstrate that feedback optimization is able to reach a near-optimal steady-state operation in the presence of uncertainties, even without relying on a priori known model information but purely data-driven through input-output measurements. Additionally, we discuss the importance of including second-order information in the optimization to ensure a satisfactory convergence speed and propose an approximated Hessian representation for problems without second-order knowledge on the plant.Publicationtype: Journal Article38 40 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Data-driven and learning-based control – perspectives and prospectsThe use of data to build models for feedback design is a classic topic of systems and control. Indeed, the term system identification can be traced back to the early 1956 work of Lotfi Zadeh [1]. Step and impulse responses remain pivotal concepts in undergraduate control education. Yet, recently, there is a rapidly growing trend towards data-driven and learning-based control in which classic results are revisited and expanded. As a prime example one may consider the 2005 note by Jan C. Willems and co-authors on persistency of excitation [2]. As illustrated in Figure 1, for the first 15 years after its publication this paper did not spark major interest beyond the community working on subspace identification of dynamic systems. Beginning with the understanding that its main result – which is also coined Willems’ fundamental lemma – enables data-driven control of LTI systems, its citation impact bifurcated to exponential growth after 2018. On this canvas, this special issue presents a snapshot of research on data-driven and learning-based methods in the German control community. Inter alia this special issues demonstrates that the ever-growing impact of data-driven and learning-based methods on systems and control goes far beyond Willems’ lemma. This includes papers working also with Koopman operators, neural networks and Gaussian processes. A major commonality of all contributed papers is the consideration of optimization-based approaches. Following the established structure of the journal the articles of this special issue are clustered into two categories – methods and applications.Publicationtype: Editorial41 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , The dynamics of a bicycle on a pump track - first results on modeling and optimal control(2024-02-01); ; We investigate the dynamics of a bicycle on an uneven mountain bike track split into straight sections with small jumps (kickers) and banked corners. A basic model of the interaction of bicycle and rider proposed and used to derive equations of motion, which capture the possibilities to accelerate the bicycle without pedaling. Since this is a first approach to the problem, only corners connected by straight lines are considered to compute optimal riding strategies. The simulation is validated with experimental data obtained on a real pump track. It is demonstrated that the model effectively captures the longitudinal bike acceleration resulting from the relative vertical motion between the rider's upper body and the bicycle. Our numerical results are in good analogy with real rider's actions on similar tracks.Publicationtype: Journal Article25 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , 31 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: with files , A compendium of optimization algorithms for distributed linear-quadratic MPCModel Predictive Control (MPC) for {networked, cyber-physical, multi-agent} systems requires numerical methods to solve optimal control problems while meeting communication and real-time requirements. This paper presents an introduction on six distributed optimization algorithms and compares their properties in the context of distributed MPC for linear systems with convex quadratic objectives and polytopic constraints. In particular, dual decomposition, the alternating direction method of multipliers, a distributed active set method, an essentially decentralized interior point method, and Jacobi iterations are discussed. Numerical examples illustrate the challenges, the prospect, and the limits of distributed MPC with inexact solutions.Publicationtype: Journal ArticleScopus© Citations 6 7 39 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Mathematical innovations fostering the energy transition-control and optimizationPublicationtype: Journal Article17 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Wirtschaftliche Leistungsregulierung für Offshore-Windparks mit Ringnetz(2020-09-25); ; ; The Canadian developer and owner of green power facilities Northland Power Inc. owns two offshore wind farms (OWFs) in the German Bight, Deutsche Bucht and Nordsee One, operated by the subsidiary Northland Power Europe GmbH. The company supports and conducts research in the field of power flow optimization in wind farm networks. The work at hand represents the results of this effort to maximize the efficiency of the assets. The project was accomplished within a cooperation between the Nordsee One GmbH and the Institute of Electrical Power and Energy Technology at the Hamburg University of Technology. From an external point of view, an OWF represents an "en bloc"power plant connected to the onshore transmission grid via power export cables. Nevertheless, such a power plant comprises a complex, large-scale internal medium voltage network. In case of failure or cable outage, the network topology of an OWF may be modified and unintended overloading of inter-array cables (IACs) is possible. In order to address this issue, a new algorithm and software tool for economic power control in OWFs are introduced in the following which can be employed in wind farms with integrated loop connection cables (LCCs). This configuration particularly entails the risk of overloading cable segments depending on the present wind speed. The new algorithm provides the operator with adapted active power setpoints for each wind turbine generator (WTG) in a given network topology. The aim is to maximize OWF power generation and minimize internal power losses while secure network operation is guaranteed. Using load flow analysis based on WTG power output measurements, the load on each cable section is monitored and the cables can be utilized to their individual full capacity while overload is avoided. The practicability of the approach is demonstrated by means of simulation results.Publicationtype: Journal Article152 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Optimal power flow : an introduction to predictive, distributed and stochastic control challenges(De Gruyter, 2018-07-26); 8 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Towards model predictive control of longitudinal beam dynamics in synchrotronsHadron synchrotrons accelerate protons and heavy ions to very high energies. The stabilization of the longitudinal beam dynamics in these particle accelerators is a demanding control problemsince typical sample times of the beam-feedback loop are on the order of several ìs to several hundred ns. This work examines if model predictive control is a suitable candidate for longitudinal beam feedback in synchrotrons. We show that, by combining an appropriate problem formulation with efficient numer-ical algorithms, the optimization problem can be solved sufficiently fast on a high-end FPGA. Realistic simulations for the synchrotron SIS18 of the GSI Helmholtz Center for Heavy-Ion Research illustrate that the proposed control scheme can lead to a significant improvement of the control performance.Publicationtype: Journal Article7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , A predictive solution to nonlinear path-following problems subject to constraintsA model predictive control scheme to solve path-following problems for nonlinear systems subject to input and state constraints is proposed. Sufficient conditions which guarantee the stability of the proposed scheme are derived. Furthermore, it is discussed how additional degrees of freedom in the path description can be formulated in an extended path-following setup. The presented schemes are exemplified by simulations of a vehicle. © Oldenbourg Wissenschaftsverlag.Publicationtype: Journal Article5