arXiv subjects

Sebastian Albrecht

Publications and source records attributed to Sebastian Albrecht.

9 recordsLinked to original sources

arXiv2026

VERITAS 2.3.1: Optimisation and Characterisation of the Enhanced Readout ASIC for the NewAthena Wide Field Imager

VERITAS 2.3.1 is the next iteration of the VErsatile Readout based on Integrated Trapezoidal Analogue Shapers (VERITAS) integrated circuit (IC) architecture for high-speed, low-noise readout of DEPleted Field Effect Transistor (DEPFET) detectors in the Wide Field Imager (WFI) on ESA's NewAthena X-ray satellite. Building on VERITAS 2.3, which demonstrated a short processing time of 2.5 us per readout and a system noise target of about 3 e- ENC RMS, the VERITAS 2.3.1 revision has been improved with additional features and targeted optimisations of existing analogue and digital blocks, alongside refined layout routing to reduce parasitic effects, to improve transient behavior, cross talk, manufacturability, and reliability while preserving the proven VERITAS architecture. The functionality and performance of VERITAS 2.3.1 was characterised in two steps. First by using a dedicated application specific integrated circuit (ASIC) only test setup. Second, a full scale module test setup is used, with integrated DEPFET sensors and readout electronics, under vacuum and at mission like temperatures. This paper presents the design updates and implementation details of the VERITAS 2.3.1, compares its measured performance to that of VERITAS 2.3, and discusses the impact of the added features, block-level optimisations, and routing improvements on overall system performance.

astro-ph.IM↗

arXiv2026

Fast, low noise, megapixel detector and readout systems for future X-ray astronomy missions

Next-generation strategic X-ray astronomy missions will require the simultaneous achievement of high angular resolution, large effective collecting area, and wide-field imaging with large-format focal plane detectors. Realizing the associated science objectives--ranging from precision measurements of bright point sources to the detection and characterization of faint diffuse emission-places stringent and, in some cases, competing requirements on detector performance. In particular, high frame rates are necessary to mitigate photon pile-up in observations of bright sources and to reduce contamination from particle-induced background in measurements of low surface brightness structures. At the same time, these instruments must preserve excellent soft X-ray response, which places tight constraints on read noise and on the fidelity of event characterization. State-of-the-art X-ray charge-coupled devices (CCDs) approach many of the key performance metrics required for these missions, but readout speed remains a primary limitation. Addressing this gap requires readout architectures that scale to high channel count, sustain high pixel throughput, and preserve the low-noise characteristics needed for soft X-ray sensitivity.

astro-ph.IM↗

arXiv2026

Robust Rigid Body Assembly via Contact-Implicit Optimal Control with Exact Second-Order Derivatives

Efficient planning of assembly motions is a long standing challenge in the field of robotics that has been primarily tackled with reinforcement learning and sampling-based methods by using extensive physics simulations. This paper proposes a sample-efficient robust optimal control approach for the determination of assembly motions, which requires significantly less physics simulation steps during planning through the efficient use of derivative information. To this end, a differentiable physics simulation is constructed that provides second-order analytic derivatives to the numerical solver and allows one to traverse seamlessly from informative derivatives to accurate contact simulation. The solution of the physics simulation problem is made differentiable by using smoothing inspired by interior-point methods applied to both the collision detection as well as the contact resolution problem. We propose a modified variant of an optimization-based formulation of collision detection formulated as a linear program and present an efficient implementation for the nominal evaluation and corresponding first- and second-order derivatives. Moreover, a multi-scenario-based trajectory optimization problem that ensures robustness with respect to sim-to-real mismatches is derived. The capability of the considered formulation is illustrated by results where over 99\% successful executions are achieved in real-world experiments. Thereby, we carefully investigate the effect of smooth approximations of the contact dynamics and robust modeling on the success rates. Furthermore, the method's capability is tested on different peg-in-hole problems in simulation to show the benefit of using exact Hessians over commonly used Hessian approximations.

cs.RO↗

arXiv2024

High Accuracy Numerical Optimal Control for Rigid Bodies with Patch Contacts through Equivalent Contact Points -- Extended Version

This paper extends the Finite Elements with Switch Detection and Jumps (FESD-J) [1] method to problems of rigid body dynamics involving patch contacts. The FESD-J method is a high accuracy discretization scheme suitable for use in direct optimal control of nonsmooth mechanical systems. It detects dynamic switches exactly in time and, thereby, maintains the integration order of the underlying Runge- Kutta (RK) method. This is in contrast to commonly used time-stepping methods which only achieve first-order accuracy. Considering rigid bodies with possible patch contacts results in nondifferentiable signed distance functions (SDF), which introduces additional nonsmoothness into the dynamical system. In this work, we utilize so-called equivalent contact points (ECP), which parameterize force and impulse distributions on contact patches by evaluation at single points. We embed a nondifferentiable SDF into a complementarity Lagrangian system (CLS) and show that the determined ECP are well-defined. We then extend the FESD-J discretization to the considered CLS such that its integration accuracy is maintained. The functionality of the method is illustrated for both a simulation and an optimal control example.

math.OC↗

arXiv2023

Resilient Model Predictive Control of Distributed Systems Under Attack Using Local Attack Identification

With the growing share of renewable energy sources, the uncertainty in power supply is increasing. In addition to the inherent fluctuations in the renewables, this is due to the threat of deliberate malicious attacks, which may become more revalent with a growing number of distributed generation units. Also in other safety-critical technology sectors, control systems are becoming more and more decentralized, causing the targets for attackers and thus the risk of attacks to increase. It is thus essential that distributed controllers are robust toward these uncertainties and able to react quickly to disturbances of any kind. To this end, we present novel methods for model-based identification of attacks and combine them with distributed model predictive control to obtain a resilient framework for adaptively robust control. The methodology is specially designed for distributed setups with limited local information due to privacy and security reasons. To demonstrate the efficiency of the method, we introduce a mathematical model for physically coupled microgrids under the uncertain influence of renewable generation and adversarial attacks, and perform numerical experiments, applying the proposed method for microgrid control.

eess.SY↗

arXiv2022

Finite Elements with Switch Detection for Direct Optimal Control of Nonsmooth Systems

This paper introduces Finite Elements with Switch Detection (FESD), a numerical discretization method for nonsmooth differential equations. We consider the Filippov convexification of these systems and a transformation into dynamic complementarity systems introduced by [Stewart, 1990]. FESD is based on solving nonlinear complementarity problems and can automatically detect nonsmooth events in time. If standard time-stepping Runge-Kutta (RK) methods are naively applied to a nonsmooth ODE, the accuracy is at best of order one. In FESD, we let the integrator step size be a degree of freedom. Additional complementarity conditions, which we call cross complementarities, enable exact switch detection, hence FESD can recover the high order accuracy that the RK methods enjoy for smooth ODE. Additional conditions called step equilibration allow the step size to change only when switches occur and thus avoid spurious degrees of freedom. Convergence results for the FESD method are derived, local uniqueness of the solution and convergence of numerical sensitivities are proven. The efficacy of FESD is demonstrated in several simulation and optimal control examples. In an optimal control problem benchmark with FESD, we achieve up to five orders of magnitude more accurate solutions than a standard time-stepping approach for the same computational time.

math.OC↗

arXiv2021

The Time-Freezing Reformulation for Numerical Optimal Control of Complementarity Lagrangian Systems with State Jumps

This paper introduces a novel time-freezing reformulation and numerical methods for optimal control of complementarity Lagrangian systems (CLS) with state jumps. We cover the difficult case when the system evolves on the boundary of the dynamic's feasible set after the state jump. In nonsmooth mechanics, this corresponds to inelastic impacts. The main idea of the time-freezing reformulation is to introduce a clock state and an auxiliary dynamical system whose trajectory endpoints satisfy the state jump law. When the auxiliary system is active, the clock state is not evolving, hence by taking only the parts of the trajectory when the clock state was active, we can recover the original solution. The resulting time-freezing system is a Filippov system that has jump discontinuities only in the first time derivative instead of the trajectory itself. This enables one to use the recently proposed Finite Elements with Switch Detection [Nurkanovic et al., 2022], which makes high accuracy numerical optimal control of CLS with impacts and friction possible. We detail how to recover the solution of the original system and show how to select appropriate auxiliary dynamics. The theoretical findings are illustrated on a nontrivial numerical optimal control example of a hopping one-legged robot.

math.OC↗

arXiv2020

A Hierarchical Attack Identification Method for Nonlinear Systems

Many autonomous control systems are frequently exposed to attacks, so methods for attack identification are crucial for a safe operation. To preserve the privacy of the subsystems and achieve scalability in large-scale systems, identification algorithms should not require global model knowledge. We analyze a previously presented method for hierarchical attack identification, that is embedded in a distributed control setup for systems of systems with coupled nonlinear dynamics. It is based on the exchange of local sensitivity information and ideas from sparse signal recovery. In this paper, we prove sufficient conditions under which the method is guaranteed to identify all components affected by some unknown attack. Even though a general class of nonlinear dynamic systems is considered, our rigorous theoretical guarantees are applicable to practically relevant examples, which is underlined by numerical experiments with the IEEE~30 bus power system.

eess.SY↗

arXiv2020

A Time-Freezing Approach for Numerical Optimal Control of Nonsmooth Differential Equations with State Jumps

We present a novel reformulation of nonsmooth differential equations with state jumps which enables their easier simulation and use in optimal control problems without the need of using integer variables. The main idea is to introduce an auxiliary differential equation to mimic the state jump map. Thereby, also a clock state is introduced which does not evolve during the runtime of the auxiliary system. The pieces of the trajectory that correspond to the parts when the clock state was evolving recover the solution of the original system with jumps. Our reformulation results in nonsmooth ordinary differential equations where the discontinuity is in the first time derivative of the trajectory, rather than in the trajectory itself. This class of systems is easier to handle both theoretically and numerically. We provide numerical examples demonstrating the ease of use of this reformulation in both simulation and optimal control. In the optimal control example a single call of a nonlinear programming (NLP) solver yields the same solution as a multi-stage formulation, without the need for exploring the optimal number of stages by enumeration or heuristics.

math.OC↗