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NASA NTRS2022

Robust Controller Synthesis for Vision-based Spacecraft Guidance and Control

This work develops a method for Robust Controller for Vision-based Spacecraft (RCVS) guidance and control, integral to the robust autonomy framework for multi-spacecraft for- mation control and reconfiguration applications. The method is built around the use of a photo-realistic simulator, where a camera is deployed on a tracking spacecraft (ego) in order to observe an uncontrolled spacecraft (target) in a Low Earth Orbit (LEO). In this direction, the proposed approach performs the relative state (attitude and position) estimation of the target spacecraft using Convolutional Neural Network (CNN). The state estimation error is then modeled and the corresponding error-bounds are obtained around a nominal trajectory of the ego and target spacecraft. Next, this work proposes a linear matrix inequalities (LMIs) based approach to controller synthesis, guaranteed to be robust against both model uncertainties and measurement errors, resulting from vision-based estimation. This controller is comprised of two distinct components, one synthesized based on the nominal trajectory, while the “robust” component corrects for deviations from the nominal trajectory. Finally, a tracking scenario that directly utilize the image data for spacecraft guidance and control, is presented to showcase the performance of the proposed robust autonomy framework.

Rahmani, Amir↗

DOE OSTI2025

Designing robust energy policy packages under deep uncertainty: A multi-metric decision support framework

The complexity of transitioning to sustainable energy systems requires policy frameworks capable of balancing multiple objectives while addressing deep uncertainty. However, existing approaches often lack systematic methods to identify combinations of policy levers that remain effective across a wide range of uncertain futures. This paper presents a novel decision support framework that guides the selection of robust policy packages based on their performance across multiple objectives under uncertainty. Our method leverages a large ensemble of scenarios and applies scenario discovery techniques to identify influential policy levers. Here, we introduce new indicators to assess the robustness of policies by evaluating their ability to mitigate adverse outcomes across metrics. These indicators support an iterative process to build a robust policy package. Finally, we map the technological and energy pathways associated with the robust policy package by leveraging an energy system optimization model. We illustrate the application of this framework to the Spanish energy system, providing insights into how specific combinations of policy levers shape decarbonization pathways under uncertainty.

Decision-support method↗

DOE OSTI2025

Robustness of quasi-symmetry along parametric boundary variation

Quasi-symmetry is a guiding principle to modern stellarator optimization for improved plasma confinement. However, the robustness of optimized configurations, which can be crucial for maintaining performance under diverse engineering constraints and practical limitations, has received relatively little attention. Here, in this work, we present various case studies on this robustness, by investigating variations in 1/ v neoclassical transport when plasma configurations are smoothly altered across distinct optimized targets. These targets, optimized from different families—quasi-axisymmetric, quasi-helical, and quasi-isodynamic—are approximately matched in major radius as part of a flexible stellarator design. Our study shows that an optimized target does not always represent a local minimum in transport and that the robustness of a local minimum when present can vary significantly. Furthermore, there are configurations which belong to no established families but have transport levels as low as those of optimized targets. These results highlight the importance of conducting extended searches with key parametric variations around optimized configurations, to ensure its robustness as well as flexibility if desired.

neoclassical transport↗

DOE OSTI2024

Distributionally Robust Variational Quantum Algorithms With Shifted Noise

Given their potential to demonstrate near-term quantum advantage, variational quantum algorithms (VQAs) have been extensively studied. Although numerous techniques have been developed for VQA parameter optimization, it remains a significant challenge. A practical issue is the high sensitivity of quantum noise to environmental changes, and its propensity to shift in real time. This presents a critical problem as an optimized VQA ansatz may not perform effectively under a different noise environment. For the first time, we explore how to optimize VQA parameters to be robust against unknown shifted noise. We model the noise level as a random variable with an unknown probability density function (PDF), and we assume that the PDF may shift within an uncertainty set. This assumption guides us to formulate a distributionally robust optimization problem, with the goal of finding parameters that maintain effectiveness under shifted noise. We utilize a distributionally robust Bayesian optimization solver for our proposed formulation. This provides numerical evidence in both the Quantum Approximate Optimization Algorithm (QAOA) and the Variational Quantum Eigensolver (VQE) with hardware-efficient ansatz, indicating that we can identify parameters that perform more robustly under shifted noise. We regard this work as the first step towards improving the reliability of VQAs influenced by real-time noise.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2024

Photocathode characterisation for robust PICOSEC Micromegas precise-timing detectors

The PICOSEC Micromegas detector is a precise-timing gaseous detector based on a Cherenkov radiator coupled with a semi-transparent photocathode and a Micromegas amplifying structure, targeting a time resolution of tens of picoseconds for minimum ionising particles. Initial single-pad prototypes have demonstrated a time resolution below σ = 25 ps, prompting ongoing developments to adapt the concept for High Energy Physics applications, where sub-nanosecond precision is essential for event separation, improved track reconstruction and particle identification. The achieved performance is being transferred to robust multi-channel detector modules suitable for large-area detection systems requiring excellent timing precision. To enhance the robustness and stability of the PICOSEC Micromegas detector, research on robust carbon-based photocathodes, including Diamond-Like Carbon (DLC) and Boron Carbide (B 4 C), is pursued. Results from prototypes equipped with DLC and B 4 C photocathodes exhibited a time resolution of σ ≈ 32 ps and σ ≈ 34.5 ps, respectively. Efforts dedicated to improve detector robustness and stability enhance the feasibility of the PICOSEC Micromegas concept for large experiments, ensuring sustained performance while maintaining excellent timing precision.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

DOE OSTI2025

Robust error calibration for serial crystallography

Serial crystallography is an important technique with unique abilities to resolve enzymatic transition states, minimize radiation damage to sensitive metalloenzymes and perform de novo structure determination from micrometre-sized crystals. This technique requires the merging of data from thousands of crystals, making manual identification of errant crystals unfeasible. cctbx.xfel.merge uses filtering to remove problematic data. However, this process is imperfect, and data reduction must be robust to outliers. We add robustness to cctbx.xfel.merge at the step of uncertainty determination for reflection intensities. This step is a critical point for robustness because it is the first step where the data sets are considered as a whole, as opposed to individual lattices. Robustness is conferred by reformulating the error-calibration procedure to have fewer and less stringent statistical assumptions and incorporating the ability to down-weight low-quality lattices. We then apply this method to five macromolecular XFEL data sets and observe the improvements to each. The appropriateness of the intensity uncertainties is demonstrated through internal consistency. This is performed through theoretical CC 1/2 and I /σ relationships and by weighted second moments, which use Wilson's prior to connect intensity uncertainties with their expected distribution. This work presents new mathematical tools to analyze intensity statistics and demonstrates their effectiveness through the often underappreciated process of uncertainty analysis.

Mittan-Moreau, David W.↗

DOE OSTI2024

Robust Data-Driven Predictive Run-to-Run Control for Automated Serial Sectioning

This letter presents a one-step predictive run-to-run controller (R2R-MPC) for the automation of mechanical serial sectioning (MSS), a destructive material analysis process. To address the inherent uncertainty and disturbances in the MSS process, a robust closed-loop approach is presented. Here, the robust R2R-MPC models the uncertainty of the MSS process using a linear differential inclusion. As an analytical model of the MSS process is unavailable, the differential inclusion is identified from historical data. The R2R-MPC is posed as an optimization problem that computes incremental changes to the control input which minimize the worst-case material removal errors. This optimization-based controller is combined with a run-to-run controller to provide integral action that rejects constant disturbances and tracks constant reference removal rates. To demonstrate the efficacy of our robust R2R-MPC, we present simulation results which compare the presented controller with a conventional non-robust R2R.

42 ENGINEERING↗

DOE OSTI2025

Robustness: The Missing Ingredient in Generation Scheduling

This article highlights robustness as an essential factor to cope with the ever-increasing levels of uncertainty in generation scheduling under significant renewable energy penetration, as is the case in Brazil and Spain. To that end, robust generation scheduling is framed within the different optimization-based approaches that are available for uncertainty handling. In addition, the suitability of robust optimization to accommodate practical security criteria in generation scheduling is also emphasized. Interestingly, this article points out the existence of an effective algorithm allowing the discovery of critical or so-called umbrella scenarios, which paves the way for the implementation of robust generation scheduling in industry practice.

Street, Alexandre↗

DOE OSTI2024

“Understanding Robustness Lottery”: A Geometric Visual Comparative Analysis of Neural Network Pruning Approaches

Deep learning approaches have provided state-of-the-art performance in many applications by relying on large and overparameterized neural networks. However, such networks are very brittle and are difficult to deploy on resource-limited platforms. Model pruning, i.e., reducing the size of the network, is a widely adopted strategy that can lead to a more robust and compact model. Many heuristics exist for model pruning, but our understanding of the pruning process remains limited due to the black-box nature of a neural network model. Empirical studies show that some heuristics improve performance whereas others can make models more brittle. Here, this work aims to shed light on how different pruning methods alter the network’s internal feature representation and the corresponding impact on model performance. To facilitate a comprehensive comparison and characterization of the high-dimensional model feature space, we introduce a visual geometric analysis of feature representations. We evaluated a set of critical geometric concepts decomposed from the commonly adopted classification loss and used them to design a visualization system to compare and highlight the impact of pruning on model performance and feature representation. The proposed tool provides an environment for an in-depth comparison of pruning methods and a comprehensive understanding of how the model responds to common data corruption. By leveraging the proposed visualization, machine learning researchers can reveal the similarities between pruning methods and redundancy in robustness evaluation benchmarks, obtain geometric insights about the differences between pruned models that achieve superior robustness performance, and identify samples that are robust or fragile to model pruning and common data corruption.

Li, Zhimin [Univ. of Utah, Salt Lake City, UT (Uni↗

NASA NTRS1974

Robust design of dynamic observers

The two (identity) observer realizations z = Mz + Ky and z = transpose of Az + transpose of K(y - transpose of Cz), respectively called the open loop and closed loop realizations, for the linear system x = Ax, y = Cx are analyzed with respect to the requirement of robustness; i.e., the requirement that the observer continue to regulate the error x - z satisfactorily despite small variations in the observer parameters from the projected design values. The results show that the open loop realization is never robust, that robustness requires a closed loop implementation, and that the closed loop realization is robust with respect to small perturbations in the gains transpose of K if and only if the observer can be built to contain an exact replica of the unstable and underdamped dynamics of the system being observed. These results clarify the stringent accuracy requirements on both models and hardware that must be met before an observer can be considered for use in a control system.

Bhattacharyya, S. P.↗

NASA NTRS1986

Robust detection, isolation and accommodation for sensor failures

The objective is to extend the recent advances in robust control system design of multivariable systems to sensor failure detection, isolation, and accommodation (DIA), and estimator design. This effort provides analysis tools to quantify the trade-off between performance robustness and DIA sensitivity, which are to be used to achieve higher levels of performance robustness for given levels of DIA sensitivity. An innovations-based DIA scheme is used. Estimators, which depend upon a model of the process and process inputs and outputs, are used to generate these innovations. Thresholds used to determine failure detection are computed based on bounds on modeling errors, noise properties, and the class of failures. The applicability of the newly developed tools are demonstrated on a multivariable aircraft turbojet engine example. A new concept call the threshold selector was developed. It represents a significant and innovative tool for the analysis and synthesis of DiA algorithms. The estimators were made robust by introduction of an internal model and by frequency shaping. The internal mode provides asymptotically unbiased filter estimates.The incorporation of frequency shaping of the Linear Quadratic Gaussian cost functional modifies the estimator design to make it suitable for sensor failure DIA. The results are compared with previous studies which used thresholds that were selcted empirically. Comparison of these two techniques on a nonlinear dynamic engine simulation shows improved performance of the new method compared to previous techniques

Emami-Naeini, A.↗

NASA NTRS1986

Integrated control/structure design and robustness

When a flexible structure is to be controlled actively, optimum performance is obtained by integrated, or simultaneous, design of the structure and the controller, as opposed to the common practice of designing the structure independently of control consideration and then designing a controller for a fixed structure. The primary design objective from the structural point of view usually is to minimize weight, while the control design objectives depend on the application. An important requirement for a practical control system is robustness with respect to uncertain plant parameters. This paper discusses simultaneous control/structure design when the overall design objective combines the weight of the structure and the robustness of the closed-loop control system. For numerical optimization, robustness is represented by the sensitivity of the closed-loop eigenvalues with respect to uncertain parameters. An example illustrates the optimal design of a flexible structure along with a robust compensator.

Adamian, A.↗

NASA NTRS1987

Lyapunov function gradient generated robust control in the absence of the nominal stabilizing control

A relevant facet of the application of Lyapunov gradient-generated robust control to unstable linear autonomous plants is explored. It is demonstrated that if the plant, the output, and the nominal stabilizing control satisfy certain conditions, then the robust component alone stabilizes the nominal plant. An example characterized by two zero eigenvalues and two negative real value poles is presented. These results assure that the robust component will fulfill the role of nominal stabilization successfully so long as the possible magnitude of the robust component can overcome the contribution of the instability to positiveness of the Lyapunov rate.

Blackwell, C. C.↗

NASA NTRS1988

Robustness analysis based on passivity

A technique of robust stability analysis for multivariable control systems is introduced. Existing tools in the literature are mostly based on small gain type of conditions such as the H(infinity)-norm or mu measure. In contrast, the approach presented is motivated by passivity theory. The natural energy Lyapunov function associated with a passive system allows robustness to be analyzed with Lyapunov stability theory. Consequently, nonlinear and time-varying perturbations can be considered within the same framework. For unstructured uncertainties, the robustness margin is characterized in terms of an index related to the Hermitian part of a transfer function. If the uncertainties contain additional diagonal structure, stability margins are obtained for variations of each uncertain block in both positive and negative directions. Applications of this robustness analysis technique are illustrated.

Wen, John T.↗

NASA NTRS1988

Robust eigenvalue/eigenvector selection in linear state feedback systems

Design procedures are developed to select both eigenvalues and eigenvectors to improve system robustness. A robustness metric based on the determinant of the normalized eigenvector matrix defined. It is shown that this metric significantly speeds up the convergence of robust eigenvector solutions close to the optimal. A procedure to blend multiple inputs to improve achievable system robustness in the lower dimensional pseudo control space has also been derived.

Srinathkumar, S.↗

NASA NTRS1989

Robust control design for aerospace applications

Time-domain control design for stability robustness of linear systems with structured uncertainty is addressed. Upper bounds on the linear perturbation of an asymptotically stable linear system are obtained, making it possible to maintain stability by using the structural information of the uncertainty. A quantitative measure called the stability robustness index is introduced and used to design controllers for robust stability. The proposed state feedback control design algorithm can be used, for a given set of perturbations, to select the range of control effort for which the system is stability-robust. Conversely it can be used, for a given control effort, to determine the size of the tolerable perturbation. The algorithm is illustrated with examples from aircraft control and large-space-structure control problems.

Yedavalli, Rama K.↗

NASA NTRS1990

Robust H(infinity) control design for the Space Station with structured parameter uncertainty

A robust H(infinity) control design methodology and its application to a Space Station attitude and momentum control problem are presented. This new approach incorporates nonlinear multiparameter variations in the state-space formulation of H(infinity) control theory. An application of this robust control synthesis technique tothe Space Station control problem yields a remarkable result in stability robustness with respect to the moments-of-inertia variation of about 73 percent in one of the structured uncertainty directions. The performance and stability of this new robust H(infinity) controller for the Space Station are compared to those of other controllers designed using a standard linear-quadratic-regulator synthesis technique.

Byun, Kuk-Whan↗

NASA NTRS1990

Feedforward/feedback control synthesis for performance and robustness

Both feedforward and feedback control approaches for uncertain dynamical systems are investigated. The control design objective is to achieve a fast settling time (high performance) and robustness (insensitivity) to plant modeling uncertainty. Preshapong of an ideal, time-optimal control input using a 'tapped-delay' filter is shown to provide a rapid maneuver with robust performance. A robust, non-minimum-phase feedback controller is synthesized with particular emphasis on its proper implementation for a non-zero set-point control problem. The proposed feedforward/feedback control approach is robust for a certain class of uncertain dynamical systems, since the control input command computed for a given desired output does not depend on the plant parameters.

Wie, Bong↗