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Results for “Robustness guarantees”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2005

Robust Constrained Optimization Approach to Control Design for International Space Station Centrifuge Rotor Auto Balancing Control System

This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.

Postma, Barry Dirk↗
NASA NTRSDate not supplied

Case Study: Analysis of Autonomous Center line Tracking Neural Networks

Deep neural networks have gained widespread usage in a number of applications. However, limitations such as lack of explainability and robustness inhibit building trust in their behavior, which is crucial in safety critical applications such as autonomous driving. Therefore, techniques which aid in understanding and providing guarantees for neural network behavior are the need of the hour. In this paper, we present a case study applying a recently proposed technique, Prophecy, to analyze the behavior of a neural network model, provided by our industry partner and used for autonomous guiding of airplanes on taxi runways. This regression model takes as input an image of the runway and produces two outputs, cross-track error and heading error, which represent the position of the plane relative to the center line. We use the Prophecy tool to extract neuron activation patterns for the correctness and safety properties of the model. We show the use of these patterns to identify features of the input that explain correct and incorrect behavior. We also use the patterns to provide guarantees of consistent behavior. We explore a novel idea of using sequences of images (instead of single images) to obtain good explanations and identify regions of consistent behavior.

Deep Neural Networks↗
DOE OSTI2022

Subcell limiting strategies for discontinuous Galerkin spectral element methods

Here, we present a general family of subcell limiting strategies to construct robust high-order accurate nodal discontinuous Galerkin (DG) schemes. The main strategy is to construct compatible low order finite volume (FV) type discretizations that allow for convex blending with the high-order variant with the goal of guaranteeing additional properties, such as bounds on physical quantities and/or guaranteed entropy dissipation. For an implementation of this main strategy, four main ingredients are identified that may be combined in a flexible manner: (i) a nodal high-order DG method on Legendre–Gauss–Lobatto nodes, (ii) a compatible robust subcell FV scheme, (iii) a convex combination strategy for the two schemes, which can be element-wise or subcell-wise, and (iv) a strategy to compute the convex blending factors, which can be either based on heuristic troubled-cell indicators, or using ideas from flux-corrected transport methods. By carefully designing the metric terms of the subcell FV method, the resulting methods can be used on unstructured curvilinear meshes, are locally conservative, can handle strong shocks efficiently while directly guaranteeing physical bounds on quantities such as density, pressure or entropy. We further show that it is possible to choose the four ingredients to recover existing methods such as a provably entropy dissipative subcell shock-capturing approach or a sparse invariant domain preserving approach. We test the versatility of the presented strategies and mix and match the four ingredients to solve challenging simulation setups, such as the KPP problem (a hyperbolic conservation law with non-convex flux function), turbulent and hypersonic Euler simulations, and MHD problems featuring shocks and turbulence.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Boosting the sodium storage behaviors of carbon materials in ether-based electrolyte through the artificial manipulation of microstructure

The porous carbon blacks rationally designed by a facile yet efficient NH 3 thermal etching route have been investigated as anode materials in an ether-based electrolyte for sodium-ion batteries. The as-synthesized CBN35 carbon black with a 35% weight loss after NH3 thermal etching exhibited a large specific charge capacity of 352 mAh g -1 at 50 mA g -1 and a superior rate capability of 101 mAh g -1 at 16000 mA g -1 , due to its highest microporosity, an appropriate surface area, a desirable microstructure, and a promising hybrid intercalation mechanism. Impressively, even cycled at 1600 mA g -1 over 3200 cycles, an outstanding reversible capacity of 103 mAh g -1 with a negligible 0.0162% capacity loss per cycle can still be achieved. Based on the multimodal characterizations including the structural probes of phase evolution for carbon materials, the electrochemical techniques, and the surface-sensitive XAS measurements, the exceptional electrochemical properties should stem from several merits of modified carbon black system. While the particular microporous structure provides relatively more accessible sodium storage sites, a novel hybrid intercalation mechanism in ether-based electrolyte would incorporate the sodium ion insertion into the disordered structure with the solvated sodium ion species co-intercalation into the graphitic phase. In addition to the diffusion-controlled redox reactions, the noticeable surface-induced pseudocapacitive reactions also significantly contribute to the charge storage upon sodiation and guarantee the rapid migrations of sodium ions/solvated compounds. In conclusion, this system further features a controlled emergence of a robust but thin solid electrolyte interphase layer, which could suppress the side reactions of active electrode with reactive electrolyte, maintain the fragile porous structure upon cycling, and facilitate the migrations of sodium ions and solvated sodium ion compounds.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Distributionally robust polynomial chance-constraints under mixture ambiguity sets

Given $\mathrm{X}\subset\mathbb{R}^n, ε \in (0,1)$, a parametrized family of probability distributions $(μ_a)_{a\in \mathrm{A}}$ on $\mathrm{Ω}\subset \mathbb{R}^p$, we consider the feasible set $\mathrm{X}^*_ε \subset\mathrm{X}$ associated with the distributionally robust chance-constraint $\mathrm{X}^*_ε = \mathrm{x \in X : Prob}_μ[f(\mathrm{x}, ω) >0] > 1 - ε, \forall μ \in \mathscr{M}_{\mathrm{a}}$}, where $\mathscr{M}_{\mathrm{a}}$ is the set of all possibles mixtures of distributions $μ_{\mathrm{a}}, \mathrm{a \in A}$. For instance and typically, the family $\mathscr{M}_{\mathrm{a}}$ is the set of all mixtures of Gaussian distributions on $\mathbb{R}$ with mean and standard deviation $\mathrm{a}=(a,σ)$ in some compact set $\mathrm{A}\subset \mathbb{R}^2$. We provide a sequence of inner approximations $\mathrm{X}^d_ε = {\mathrm{x \in X} : w_d(\mathrm{x}) < ε}, d \in \mathbb{N}$, where $w_d$ is a polynomial of degree d whose vector of coefficients is an optimal solution of a semidefinite program. The size of the latter increases with the degree d. We also obtain the strong and highly desirable asymptotic guarantee that $λ(\mathrm{X}^*_ε$\$\mathrm{X}^d_ε$) → 0 as d increases, where λ is the Lebesgue measure on X. Same results are also obtained for the more intricated case of distributionally robust “joint” chance-constraints. Finally, there is a price to pay for this strong asymptotic guarantee which is the scalability of such a numerical scheme, and so far this important drawback makes it limited to problems of modest dimension.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Dual-Band Polarization Control with Pairwise Positioning of Polarization Singularities in Metasurfaces

Emerging applications of metasurfaces in classical and quantum optics are driving the need for precise polarization control of nearly-degenerate, high quality (𝑄)-factor modes. However, current approaches to creating specifically polarized pairs of modes force a trade-off between maintaining high 𝑄 factors and robustness. Here, we solve this challenge by employing pairwise generation, annihilation, and positioning of polarization singularities, derived from symmetry-guaranteed pairs of symmetry-protected bound states in the continuum. We experimentally demonstrate this design paradigm in silicon metasurfaces with mode splittings of ≈ 20 nm, mode splitting deviations as low as 1 nm, and 𝑄 factors up to 200. Furthermore, this approach opens new avenues for enhancing metasurface performance across a diverse range of applications, including sensing, modulating, nonlinear mixing, and generating quantum light.

Metasurfaces↗
DOE OSTI2020

Learning to Solve Large-Scale Security-Constrained Unit Commitment Problems

Security-constrained unit commitment (SCUC) is a fundamental problem in power systems and electricity markets. In practical settings, SCUC is repeatedly solved via mixed-integer linear programming (MIP), sometimes multiple times per day, with only minor changes in input data. In this work, we propose a number of machine learning techniques to effectively extract information from previously solved instances in order to significantly improve the computational performance of MIP solvers when solving similar instances in the future. Based on statistical data, we predict redundant constraints in the formulation, good initial feasible solutions, and affine subspaces where the optimal solution is likely to lie, leading to a significant reduction in problem size. Computational results on a diverse set of realistic and large-scale instances show that using the proposed techniques, SCUC can be solved on average 4.3 times faster with optimality guarantees and 10.2 times faster without optimality guarantees, with no observed reduction in solution quality. Out-of-distribution experiments provide evidence that the method is somewhat robust against data-set shift. Summary of Contribution. The paper describes a novel computational method, based on a combination of mixed-integer linear programming (MILP) and machine learning (ML), to solve a challenging and fundamental optimization problem in the energy sector. The method advances the state-of-the-art, not only for this particular problem, but also, more generally, in solving discrete optimization problems via ML. We expect that the techniques presented can be readily used by practitioners in the energy sector and adapted, by researchers in other fields, to other challenging operations research problems that are solved routinely.

Machine Learning↗
NASA NTRS2006

A High-Authority/Low-Authority Control Strategy for Coupled Aircraft-Style Bays

This paper presents a numerical investigation of an active structural acoustic control strategy for coupled aircraft-style bays. While structural coupling can destabilize or limit the performance of some model-based decentralized control systems, fullycoupled centralized control strategies are impractical for typical aircraft containing several hundred bays. An alternative is to use classical rate feedback with matched, collocated transducer pairs to achieve active damping. Unfortunately, due to the conservative nature of this strategy, stability is guaranteed at the expense of achievable noise reduction. Therefore, this paper describes the development of a combined control strategy using robust active damping in addition to a high-authority controller based on linear quadratic Gaussian (LQG) theory. The combined control system is evaluated on a tensioned, two-bay model using piezoceramic actuators and ideal point velocity sensors. Transducer placement on the two-bay structure is discussed, and the advantages of a combined control strategy are presented.

Schiller, N. H.↗
NASA NTRS2007

A Robustly Stabilizing Model Predictive Control Algorithm

A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

Ackmece, A. Behcet↗
DOE OSTI2026

Data for The Value of Reversible Carbon Storage in a Zero-Emissions World

Atmospheric carbon dioxide removal (CDR) is required to stabilize global temperature. CDR can be achieved via ecosystem-based approaches that are cost-effective but reversible (e.g., soil and forest management) or by more durable but expensive approaches (e.g., direct air capture coupled with geologic storage). Here, we examine trade-offs between these approaches, focusing on timing, climate impacts, and cost. We simulated reversible carbon accrual for a range of CDR contract structures using a general minimalist model of ecosystem carbon cycling, and parameterized it to simulate US agricultural soil management─specifically cover cropping─as a case study. We then quantified the resulting impact on atmospheric carbon and global temperature using a climate model emulator. We find that maintaining a patchwork of reversible CDR projects by replacing lapsed projects with new projects can reduce warming by 22–195 μ°C in 2100 and that the magnitude of this cooling effect depends on how effectively the patchwork is maintained. Long-term maintenance of reversible CDR projects requires institutional stability that cannot be guaranteed over multiple decades. Consequently, effective CDR ultimately requires replacing reversible projects with durable projects. To address this problem, we modeled the cost of replacing reversible agricultural soil CDR with geologic CDR. We found that using reversible CDR as a bridge to durable CDR is potentially more cost-effective as a global cooling strategy (0.20–0.81 billion USD per μ°C avoided) than perpetual maintenance of reversible CDR (0.32–1.31 billion USD per μ°C avoided) or an immediate transition to durable CDR (1.37–2.19 billion USD per μ°C avoided). However, we emphasize that institutional commitments to maintain reversible CDR projects cannot be guaranteed. Reliance on reversible CDR as a bridge to durable CDR therefore carries an unknown amount of risk and will only function if efforts to maintain reversible CDR are robust.

Carbon↗
DOE OSTI2022

Robust trajectory-constrained frequency control for microgrids considering model linearization error

Grid supportive modes integrated within inverter-based resources can improve the frequency response of renewable-rich microgrids. The synthesis of grid supportive modes to guarantee frequency trajectory constraints under a predefined disturbance set is challenging but essential. To tackle this challenge, a numerical optimal control (NOC)-based control synthesis methodology is proposed. Without loss of generality, a wind-diesel fed microgrid is studied, where we aim to design grid supportive functions in the wind turbine. In the control design, linearized models are used, and the linearization-induced errors are quantitatively analyzed by reachability and interval arithmetics and represented in the form of interval uncertainties. Then, the NOC problem can be formulated into a robust mixed-integer linear program. The control structure is strategically configured into two levels to realize online deployment. The proposed control is verified on the modified 33-node microgrid with a full-order three-phase nonlinear model in Simulink. In conclusion, the simulation results show the effectiveness of the proposed control paradigm and the necessity of considering linearization-induced uncertainty.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS1992

Lyapunov function-based control laws for revolute robot arms - Tracking control, robustness, and adaptive control

A new class of joint level control laws for all-revolute robot arms is introduced. The analysis is similar to a recently proposed energy-like Liapunov function approach, except that the closed-loop potential function is shaped in accordance with the underlying joint space topology. This approach gives way to a much simpler analysis and leads to a new class of control designs which guarantee both global asymptotic stability and local exponential stability. When Coulomb and viscous friction and parameter uncertainty are present as model perturbations, a sliding mode-like modification of the control law results in a robustness-enhancing outer loop. Adaptive control is formulated within the same framework. A linear-in-the-parameters formulation is adopted and globally asymptotically stable adaptive control laws are derived by simply replacing unknown model parameters by their estimates (i.e., certainty equivalence adaptation).

Wen, John T.↗
DOE OSTI2023

Designing dynamically corrected gates robust to multiple noise sources using geometric space curves

Noise-induced gate errors remain one of the main obstacles to realizing a broad range of quantum information technologies. Dynamical error suppression using carefully designed control schemes is critical for overcoming this challenge. Such schemes must be able to correct against multiple noise sources simultaneously afflicting a qubit to reach error-correction thresholds. Here we present a general framework for designing control fields that simultaneously suppress both noise in the fields themselves as well as transverse dephasing noise. Using the recently developed space curve quantum control formalism, in which robust quantum evolution is mapped to closed geometric curves in a multidimensional Euclidean space, we derive the minimal conditions necessary to guarantee the simultaneous cancellation of both types of noise to leading order. In particular, we find that the cancellation of control field noise requires the derivative of the space curve to have zero-area projections, which is a much more subtle property compared to the closed-curve condition needed to suppress transverse dephasing. We present several techniques for solving both these conditions simultaneously and provide explicit examples of error-resistant control fields. Finally, our work also sheds light on the relation between holonomic evolution and the suppression of control field errors.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS1994

Vehicle following controller design for autonomous intelligent vehicles

A new vehicle following controller is proposed for autonomous intelligent vehicles. The proposed vehicle following controller not only provides smooth transient maneuvers for unavoidable nonzero initial conditions but also guarantees the asymptotic platoon stability without the availability of feedforward information. Furthermore, the achieved asymptotic platoon stability is shown to be robust to sensor delays and an upper bound for the allowable sensor delays is also provided in this paper.

Chien, C. C.↗
DOE OSTI2023

Explicit model predictive control through robust optimization

A strategy that calculates an explicit state feedback policy to regulate constrained uncertain discrete‐time uncertain linear systems is presented. We consider uncertain processes, affected by box‐bounded multiplicative uncertainty as well as bounded additive uncertainty with linear state and inputs constraints. The proposed method includes (i) the calculation of a terminal set constraint and (ii) the robust reformulation of state constraints in the prediction horizon. These features allow the derivation of the desired policy by solving a single multiparametric quadratic programming problem that guarantees feasible operation in the presence of uncertainty. Additionally, we employ variable and constraint elimination approaches to enhance the computational performance of the strategy. We demonstrate the steps and benefits of these developments with a numerical example and a chemical engineering case study.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS2021

Decentralized Control Synthesis for Air Traffic Management in Urban Air Mobility

Urban air mobility (UAM) refers to air transportation services within an urban area, often in an on-demand fashion. We study air traffic management (ATM) for vehicles in a UAM fleet, while guaranteeing system safety requirements such as traffic separation. Existing ATM methods for unmanned aerial systems, such as UAS traffic management, utilize alternative approaches which do not provide strict safety guarantees. No established infrastructure exists for providing ATM at scale for UAM. We provide a decentralized, hierarchical approach for UAM ATM that allows for scalability to high traffic densities as well as providing theoretical guarantees of correctness with respect to user-provided safety specifications. Our main contributions are two-fold. First, we propose a novel UAM ATM architecture that divides the control authority between vertihubs that are each in charge of all UAM vehicles in their local airspace. Each vertihub also contains a number of vertiports that are in charge of UAM vehicle takeoffs and landings. The resulting architecture is decentralized and hierarchical, which not only enables scalability, but also robustness in the event of any individual vertihub or vertiport no longer being operational. Second, we provide a contract-based correct-by-construction reactive synthesis approach that provably guarantees safety properties with respect to user-provided specifications in linear temporal logic. We demonstrate the approach on large-volume UAM air traffic data.

Urban Air Mobility↗
DOE OSTI2022

Extended Barton–Bandis model for rock joints under cyclic loading: Formulation and implicit algorithm

In this paper, the Barton–Bandis model for rock joints is extended to cyclic loading conditions, without any new material parameter. Also developed herein is an implicit solution algorithm for the extended Barton–Bandis model, which can also be used for the original Barton–Bandis model for which an implicit algorithm has been unavailable. To this end, we first cast the Barton–Bandis model into an incremental elasto-plastic framework, deriving an expression for the elastic shear stiffness being consistent with the original model formulation. We then extend the model formulation to cyclic loading conditions, incorporating the dependence of shear stress and dilation on the joint position and the shearing direction. The extension is achieved by introducing a few state-dependent variables which can be calculated with the existing material parameters. For robust and accurate utilization of the model, we also develop an implicit algorithm based on return mapping, which is unconditionally stable and guarantees the satisfaction of the strength criterion. We verify that the proposed model formulation and algorithm produce virtually the same results as the original Barton–Bandis model under monotonic shearing conditions. Here, we then validate the extended Barton–Bandis model against experimental data on natural rock joints under cycling loading conditions. The present work thus enables the Barton–Bandis model, which has been exceptionally popular in research and practice, to be applicable to a wider range of problems in rock mechanics and rock engineering.

58 GEOSCIENCES↗
NASA NTRS1994

Three-axis stabilization of spacecraft using parameter-independent nonlinear quaternion feedback

This paper considers the problem of rigid spacecraft. A nonlinear control law which uses the feedback of the unit quaternion and the measured angular velocities is proposed and is shown to provide global asymptotic stability. The control law does not require the knowledge of the system parameters, and is therefore robust to modeling errors. The significance of the control law is that it can be used for large-angle maneuvers with guaranteed stability.

Joshi, Suresh M.↗