Curriculum Vitae

• Demonstrated propulsion fault recovery experimentally in a laboratory setup
LINK
• Ongoing work on convex MPC formulation (QP) for robust thrust control of pressure-fed bi-liquid rocket engines

• Project lead
• Project management (budget >100 k€, time planning, ressource planning, risk management)
• System engineering and component-level-design
• Team lead for students involved in the project
• Technical outreach and coordination
• Technical Design
• System studies and requirements derivation based on the self-developed HopIt tool
• Design of the ~3kN thrust chamber assembly incl. the injector head
• Thermal analysis of the regenerative cooling liner based on the self-developed THERMAT tool
• Design of the bi-liquid cryogenic propulsion test bench (up to 3kN thrust); assembly and commissioning in close collaboration with technical staff currently ongoing
• First hotfire planned for 2026
• Ongoing work toward real-time deployment of convex MPC on rocket engine test bench to close the gap between control theory and experimental validation

• Please see "Mentoring & Teaching" section below for details

• Derived nonlinear dynamics of velocity controlled overhead crane
• Implemented artifical reference MPC (ARMPC) for the nonlinear 2D overhead crane dynamics, which allows time-optimal point-to-point motion without a-priori known trajectory (.i.e. by motion planning)
• Augmented ARMPC with forward-invariant constraint in the form of a higher-order control barrier function for collision avoidance between the load and obstacles
• Performed system identification to close the gap between first princples based model and real dynamics, tuned the low-level velocity controllers and solved practicalities such as sensor dead zones
• Deployed the ARMPC augmented controller on a Speedgoat real-time machine and demonstrated control architecture on 2D laboratory overhead crane test setup
• Achieved near free-time optimal performance (at most 10% longer than free-time solution) without residual swing for point to point motions with collision avoidance
• Results currently being prepared for first-authot submission to CCTA 2026

• Designed a 1N GH2/GO2 thruster for CubeSat applications with a focus on the thermal management, which was manufactures using SLM
• Fully designed the associated propulsion test bench including oxygen hazard analysis
• The test bench remains in active use and forms the basis for subsequent publications

• Built a broad foundation across multiple engineering disciplines
• Fluid dynamics from theory (Navier–Stokes) to application (CFD)
• Aerospace engineering with focus on propulsion and satellite systems
• Exposure to business administration and engineering management
• Selected project highlights
• Fluid-dynamic simulations for bi-liquid rocket project as part of the TUDSaT Student team
• Group project on visualization of satellite conjunction events, as part of the Rules4CREAM project
• Internatioal student group project on aeroelastic analysis of compressor blades using ANSYS

• Developed a Python-based analysis tool to correlate local CFD flow-field data with global performance metrics
• Enabled identification of regions with high sensitivity to efficiency changes and other performance metrics
• Addressed challenges related to large CFD data sets through flexible mesh decomposition strategies

Accurate and safe thrust control of rocket engines requires regulating the combustion chamber pressure and oxidizer-to-fuel ratio within strict operational limits. This paper presents a convex successive linear Model Predictive Control (SLMPC) framework for setpoint tracking of these variables in a pressure-fed rocket engine under actuator and state constraints. A lumped parameter dynamic model is derived and subsequently reduced by neglecting fast fluid dynamics. This yields a two-state representation that preserves the dominant engine dynamics while offering reduced computational complexity when employed for MPC. The resulting SLMPC formulation achieves accurate pressure and mixture-ratio control. Simulation results demonstrate that the proposed approach outperforms a conventional PI controller in tracking speed and constraint satisfaction, while closely matching the performance of a nonlinear MPC. The SLMPC requires 6 ms per solve at 30 Hz, which is six times faster than the nonlinear MPC.

Time-minimal and collision-free motion of overhead cranes is critical in industrial applications with strict productivity and safety requirements. This paper presents a control framework that combines Artificial Reference Model Predictive Control (ARMPC) with a Higher-Order Control Barrier Function (HOCBF) to achieve near time-optimal pointto- point motion with explicit collision avoidance guarantees. The ARMPC formulation enables fixed-horizon optimization suitable for real-time deployment, while the HOCBF enforces safety by ensuring forward invariance of a collision-free set without significantly increasing computational complexity. The approach is tailored to a planar overhead crane system and validated through code generation, simulations, and experimental deployment on a laboratory-scale setup. A comparison with a free-time time-optimal control formulation demonstrates that the proposed method achieves near optimal transfer times with substantially improved real-time feasibility.

We employ a decoupled control framework for the thrust control of rocket engines in which a Control Barrier Function (CBF) based Quadratic Program (QP) acts as a lightweight safety filter that enforces state constraints. Our main contribution is a control affine formulation of the dynamics of a pressure-fed rocket engine, enabling the application of CBF-QP safety filters to render arbitrary control policies safe with respect to operational limits. To demonstrate this, we synthesize a Deep Neural Network (DNN) policy via imitation learning of a setpoint-tracking Nonlinear Model Predictive Controller (NMPC). The DNN closely mimics NMPC tracking performance. The CBF-QP safety filter prevents operational limit violations without degrading steady-state tracking performance, at the cost of slower transient response.

The Chair of Space Mobility and Propulsion at the Technical University of Munich is developing a Vertical-Take-off- Vertical-Landing Platform - called the Autonomous Control and Engine Technology (ASCENT) platform - propelled by a hot gas propulsion system. One challenge lies in the complexity of synthesizing feasible design candidates due to circular interdependencies between subsystems. A model-based design approach is proposed to overcome this issue. For this, relevant governing equations (for subsystems such as the thrust chamber, structure, or parts of the feeding system) are derived. They are subsequently brought into a root-finding problem structure, which is solved given different solver architectures. This methodology is utilized to address uncertainties present in the early design phase via sensitivity analysis based on a Monte-Carlo-like sampling approach. Among other findings, this analysis shows that the determination of pressure losses between the propellant tanks and the thrust chamber significantly impacts the mass of the entire system and should neither be under- nor over-predicted.

On average, every 50th launch undergoes a propulsion system failure. Increasing commercial activities and increasing human spaceflight activities and the associated reliability demands motivate the authors to study strategies to improve reliability of space vehicles from a control perspective. A Model Predictive Controller and the Parameter Adaption System Identification Algorithm are used to build a Fault Tolerant Control Framework. The reference application case is the cold gas-propelled Rocket Hopper operated by the Chair of Space Mobility and Propulsion at TUM. Spontaneously during constant Hover flight, a permanent, and partial loss of thrust of 30% is injected. The Fault Tolerant Controller recovers from this fault scenario.

The application of Water Electrolysis Propulsion to a 3U CubeSat as a de-orbiting kit with attitude control capabilities is evaluated and presented.
Liquid water is decomposed into gaseous hydrogen and oxygen by an electrolysis unit supplied by solar power. A parametrised simulation model of the propulsion system is derived and coupled with a subsequent optimisation to determine operational and design parameters. A blowdown architecture operating at initial pressures of 15𝑏𝑎𝑟 at a nominal thrust of 0.5𝑁 is derived as being the most mass efficient. A continuous electrolyser power supply of 2𝑊 and ca. 400 burn cycles lasting 2.5𝑠 each are required to achieve the prescribed mission requirements.