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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 1,189 records · Page 66
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Reinforcement Learning-based Output Structured Feedback for Distributed Multi-Area Power System Frequency Control

Load frequency control (LFC) is a key factor to maintain the stable frequency in multi-area power systems. As the modern power systems evolve from centralized to decentralized paradigm, LFC needs to consider the decentralized scheme that considers limited information from the information-exchange graph for the generator control of each interconnected area. This paper aims to solve a data-driven constrained LQR problem with mean-variance risk constraints and output structured feedback, and applies this framework to solve the LFC problem in multi-area power systems. By reformulating the constrained optimization problem into a minimax problem, the stochastic gradient descent max-oracle (SGDmax) algorithm with zero-order policy gradient (ZOPG) is adopted to find the optimal feedback gain from the learning, while guaranteeing the convergence. In addition, to improve the adaptation of the proposed learning method to new or varying models, we construct an emulator grid that approximates the dynamics of a physical grid and performs training based on this model. Once the feedback gain is obtained from the emulator grid, it is applied to the physical grid with a robustness test to check whether the controller from the approximated emulator applies to the actual system. Numerical tests show that the obtained feedback controller can successfully control the frequency of each area, while mitigating the uncertainty from the loads, with reliable robustness that ensures the adaptability of the obtained feedback gain to the actual physical grid.

Kwon, Kyung-bin↗
NASA NTRS1979

Robustness with observers

The paper describes an adjustment procedure for observer-based linear control systems which asymptotically achieves the same loop transfer functions (and hence the same relative stability, robustness, and disturbance rejection properties) as full-state feedback control implementations. Full-state loop-transfer properties can be recovered asymptotically if the plant is minimum phase; this occurs at the expense of noise performance.

Doyle, J. C.↗
NASA NTRS1981

Robustness tests utilizing the structure of modelling error

The present investigation is essentially concerned with the extension of results presented by Lehtomaki et al. (1981) on the robustness of multivariable linear time invariant feedback control systems. The work reported by Lehtomaki et al. is based on a multivariable version of Nyquist's theorem from which several robustness theorems were derived. In connection with the current investigation a slightly more general approach based on Nyquist's theorem is given in a fundamental robustness theorem from which various robustness tests may be obtained. A fundamental characterization of robustness is considered, and important tools from matrix theory are introduced. Attention is given to robustness tests and unstructured model error, and a robustness analysis for linear systems with structured model error.

Lehtomaki, N. A.↗
NASA NTRS1992

Flexible body control using neural networks

Progress is reported on the control of Control Structures Interaction suitcase demonstrator (a flexible structure) using neural networks and fuzzy logic. It is concluded that while control by neural nets alone (i.e., allowing the net to design a controller with no human intervention) has yielded less than optimal results, the neural net trained to emulate the existing fuzzy logic controller does produce acceptible system responses for the initial conditions examined. Also, a neural net was found to be very successful in performing the emulation step necessary for the anticipatory fuzzy controller for the CSI suitcase demonstrator. The fuzzy neural hybrid, which exhibits good robustness and noise rejection properties, shows promise as a controller for practical flexible systems, and should be further evaluated.

Mccullough, Claire L.↗
NASA NTRS1994

Learning to train neural networks for real-world control problems

Over the past three years, our group has concentrated on the application of neural network methods to the training of controllers for real-world systems. This presentation describes our approach, surveys what we have found to be important, mentions some contributions to the field, and shows some representative results. Topics discussed include: (1) executing model studies as rehearsal for experimental studies; (2) the importance of correct derivatives; (3) effective training with second-order (DEKF) methods; (4) the efficacy of time-lagged recurrent networks; (5) liberation from the tyranny of the control cycle using asynchronous truncated backpropagation through time; and (6) multistream training for robustness. Results from model studies of automotive idle speed control serve as examples for several of these topics.

Feldkamp, Lee A.↗
DOE OSTI2026

Adaptive Reinforcement Learning Control for Power Distribution in Multi-Output Resonant Converters

This paper presents an adaptive reinforcement learning (ARL)-based control framework for efficient power distribution in a multi-output resonant converter for UAV applications. The proposed system is based on a high-frequency isolated resonant architecture, where a single energy source supplies multiple propulsion loads through independently controlled output rectifiers, addressing the need for coordinated multi-motor power management. The ARL framework dynamically allocates output power by learning optimal phase-shift control actions under varying load demands and operating conditions. The agent autonomously determines control parameters that maximize conversion efficiency while ensuring accurate power sharing among multiple outputs. In addition, the proposed approach enables adaptive operation without requiring detailed system modeling or manual tuning. Experimental results demonstrate stable and efficient performance over a wide range of operating conditions, confirming the effectiveness and robustness of the learning-based control strategy for multi-output resonant converter system.

Asa, Erdem [ORNL] (ORCID:0000000190884812)↗
NASA NTRS1994

A software architecture for hard real-time execution of automatically synthesized plans or control laws

The design of a flexible, real-time software architecture for trajectory planning and automatic control of redundant manipulators is described. Emphasis is placed on a technique of designing control systems that are both flexible and robust yet have good real-time performance. The solution presented involves an artificial intelligence algorithm that dynamically reprograms the real-time control system while planning system behavior.

Schoppers, Marcel↗
NASA NTRS2009

Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC

Kaneshige, John T.↗
NASA NTRS1991

Dynamic dissipative compensator design for large space structures

Control system design is considered for attitude control and vibration suppression of flexible space structures. The problem addressed is that of controlling both the zero-frequency rigid-body modes and the elastic modes. Model-based compensators, which employ observers tuned to the plant parameters, are first investigated. Such compensators are shown to generally exhibit high sensitivity to the knowledge of the parameters, especially the elastic mode frequencies. To overcome this problem a class of dynamic dissipative compensators is next proposed, which robustly stabilize the plant in the presence of unmodeled dynamics and parametric uncertainties. An analytical proof of robust stability is given, and a method of implementing the controller as a strictly proper compensator is given. Methods of designing such controllers to obtain optimal performance and robust stability are presented. Numerical and experimental results of application of the methods are presented, which indicate that dynamic dissipative controllers can simultaneously provide excellent performance and robustness.

Joshi, S. M.↗
NASA NTRS2011

The Effects of Propellant Slosh Dynamics on the Solar Dynamics Observatory

The Solar Dynamics Observatory (SDO) mission, which is part of the Living With a Star program, was successfully launched and deployed from its Atlas V launch vehicle on February 11, 2010. SDO is an Explorer-class mission now operating in a geosynchronous orbit (GEO). The basic mission is to observe the Sun for a very high percentage of the 5-year mission (10-year goal) with long stretches of uninterrupted observations and with constant, high-data-rate transmission to a dedicated ground station located in White Sands, New Mexico. A significant portion of SDO's launch mass was propellant, contained in two large tanks. To ensure performance with this level of propellant, a slosh analysis was performed. This paper provides an overview of the SDO slosh analysis, the on-orbit experience, and the lessons learned. SDO is a three-axis controlled, single fault tolerant spacecraft. The attitude sensor complement includes sixteen coarse Sun sensors, a digital Sun sensor, three two-axis inertial reference units, two star trackers, and four guide telescopes. Attitude actuation is performed either using four reaction wheels or eight thrusters, depending on the control mode, along with single main engine which nominally provides velocity-change thrust. The attitude control software has five nominal control modes: three wheel-based modes and two thruster-based modes. A wheel-based Safehold running in the Attitude Control Electronics (ACE) box improves the robustness of the system as a whole. All six modes are designed on the same basic proportional-integral-derivative attitude error structure, with more robust modes setting their integral gains to zero. To achieve and maintain a geosynchronous orbit for a 2974-kilogram spacecraft in a cost effective manner, the SDO team designed a high-efficiency propulsive system. This bi-propellant design includes a 100-pound-force main engine and eight 5-pound-force attitude control thrusters. The main engine provides high specific impulse for the maneuvers to attain GEO, while the smaller Attitude Control System (ACS) thrusters manage the disturbance torques of the larger main engine and provide the capability for much smaller orbit adjustment burns. SDO's large solar profile produces a large solar torque disturbance and momentum buildup. This buildup drives the frequency of momentum unloads via ACS thrusters. SDO requires 1409 kilograms (which is approximately half the launch mass) of propellant to achieve and maintain the GEO orbit while performing the momentum unloads for 10 years.

Mason, Paul↗
NASA NTRS2006

Controlling Attitude of a Solar-Sail Spacecraft Using Vanes

A paper discusses a concept for controlling the attitude and thrust vector of a three-axis stabilized Solar Sail spacecraft using only four single degree-of-freedom articulated spar-tip vanes. The vanes, at the corners of the sail, would be turned to commanded angles about the diagonals of the square sail. Commands would be generated by an adaptive controller that would track a given trajectory while rejecting effects of such disturbance torques as those attributable to offsets between the center of pressure on the sail and the center of mass. The controller would include a standard proportional + derivative part, a feedforward part, and a dynamic component that would act like a generalized integrator. The controller would globally track reference signals, and in the presence of such control-actuator constraints as saturation and delay, the controller would utilize strategies to cancel or reduce their effects. The control scheme would be embodied in a robust, nonlinear algorithm that would allocate torques among the vanes, always finding a stable solution arbitrarily close to the global optimum solution of the control effort allocation problem. The solution would include an acceptably small angle, slow limit-cycle oscillation of the vanes, while providing overall thrust vector pointing stability and performance.

Mettler, Edward↗
NASA NTRS1989

Stability analysis of multiple-robot control systems

In a space telerobotic service scenario, cooperative motion and force control of multiple robot arms are of fundamental importance. Three paradigms to study this problem are proposed. They are distinguished by the set of variables used for control design. They are joint torques, arm tip force vectors, and an accelerated generalized coordinate set. Control issues related to each case are discussed. The latter two choices require complete model information, which presents practical modeling, computational, and robustness problems. Therefore, focus is on the joint torque control case to develop relatively model independent motion and internal force control laws. The rigid body assumption allows the motion and force control problems to be independently addressed. By using an energy motivated Lyapunov function, a simple proportional derivative plus gravity compensation type of motion control law is always shown to be stabilizing. The asymptotic convergence of the tracing error to zero requires the use of a generalized coordinate with the contact constraints taken into account. If a non-generalized coordinate is used, only convergence to a steady state manifold can be concluded. For the force control, both feedforward and feedback schemes are analyzed. The feedback control, if proper care has been taken, exhibits better robustness and transient performance.

Wen, John T.↗
NASA NTRS2011

Simulation of Grid-Fin Control Surfaces

Conference poster using previously disclosed techniques and methods (see ARC 16210 & 16212). We present simulations of grid-fin control surfaces to demonstrate geometric complexity and numerical robustness. These results have relevance to high-performance computing and performance of grid-fin-based control systems.

Aftosmis, Michael J.↗
DOE OSTI2021

Stacked Low-Inertia Converter or Solid-State Transformer: Modeling and Model Predictive Priority-Shifting Control for Voltage Balance

This paper presents control challenges of stacked low-inertia converter (SLIC) or cascaded reduced dc-link solid-state transformer (SST) and proposes a novel model predictive priority-shifting (MPPS) control with implicit modulator and a discrete-time large-signal model for voltage balancing and dc-link regulation. Low-inertia converters, featuring small electrolytic capacitor-less dc links, dramatically reduce cost, size, and weight compared to conventional solutions. However, without a large dc-link buffer, the input and output are tightly coupled, leading to significant control challenges. The control becomes even more challenging with these converters stacked input-series output-parallel (ISOP) for medium-voltage (MV) grid, which causes coupling between the modules besides the coupling within each module. This paper analyzes the multi-objective, multi-degree of freedom control problem, using the modular soft-switching solid-state transformer (M-S4T) as an example of the SLIC. First, distribution of control efforts under controller saturation is critical because multiple control objectives can be conflicting, especially when the module voltages are unbalanced and are being restored. The MPPS can shift the priorities to address this issue. Second, due to the low inertia and high dc-link ripple, classic space vector pulse-width modulation (SVPWM), average model with small-ripple assumption, and control design based on small-signal model cannot accurately modulate, model, and control the nonlinear reduced dc link. Therefore, a discrete-time large-signal model of the M-S4T is established to derive the predictive control in the MPPS. The MPPS and the PI control are compared in MV simulations to show the issue of applying the PI to the SLIC and the effectiveness of the MPPS for voltage balancing and dc-link regulation in a deadbeat manner. Finally, the proposed control is tested on a 5 kV ISOP SiC SST prototype to verify priority shifting to address controller saturation issue and fast and robust voltage balancing.

14 SOLAR ENERGY↗
DOE OSTI2021

Uniaxial Néel vector control in perovskite oxide thin films by anisotropic strain engineering

Antiferromagnetic (AF) thin films typically exhibit a multidomain state, and control of the AF Néel vector is challenging, as AF materials are robust to magnetic perturbations. In this paper, uniaxial Néel vector control is demonstrated by relying on anisotropic strain engineering of epitaxial thin films of the prototypical AF material LaFeO 3 (LFO). Orthorhombic (011)- and (101)-oriented DyScO 3 , GdScO 3 , and NdGaO 3 substrates are used to engineer different anisotropic in-plane strain states. The anisotropic in-plane strain stabilizes structurally monodomain monoclinic LFO thin films. The uniaxial Néel vector is found along the tensile strained b axis, contrary to bulk LFO having the Néel vector along the shorter a axis, and no magnetic domains are found. Hence, anisotropic strain engineering is a viable tool for designing unique functional responses, further enabling AF materials for mesoscopic device technology.

36 MATERIALS SCIENCE↗
NASA NTRS1994

Neural network controller development for a magnetically suspended flywheel energy storage system

A neural network controller has been developed to accommodate disturbances and nonlinearities and improve the robustness of a magnetically suspended flywheel energy storage system. The controller is trained using the back propagation-through-time technique incorporated with a time-averaging scheme. The resulting nonlinear neural network controller improves system performance by adapting flywheel stiffness and damping based on operating speed. In addition, a hybrid multi-layered neural network controller is developed off-line which is capable of improving system performance even further. All of the research presented in this paper was implemented via a magnetic bearing computer simulation. However, careful attention was paid to developing a practical methodology which will make future application to the actual bearing system fairly straightforward.

Fittro, Roger L.↗
DOE OSTI2025

Heterobinuclear Molecular Precursors Direct the Formation of Supported Subnanometer Cu–M Clusters with Tunable Catalytic Behavior

Subnanometer bimetallic clusters hold great promise for catalytic applications due to their unique electronic properties and high surface-to-volume ratios. However, precise control over their composition and size remains a major challenge, particularly for immiscible metal pairs. Here, we report a surface-anchored molecular approach for synthesizing ∼0.7–0.8 nm Cu–M (M = Ru, Mo, W, Fe) bimetallic clusters on mesoporous silica supports, using heterobinuclear N-heterocyclic carbene (NHC)-based complexes as precursors. The NHC ligand functionalized with an alkoxysilane anchor enables robust grafting to the silica interface. Controlled calcination and reduction lead to subnanometer clusters with tunable composition, dictated by the metal–metal bond stability in the precursor. In situ transmission electron microscopy reveals cluster growth proceeds via sintering of adjacent surface-bound units, while elevated temperatures above 300 °C triggering diffusion and phase separation. Catalytic testing in ethylene hydrogenation demonstrates composition-dependent activity and kinetics, with CuRu and CuW clusters exhibiting lower apparent activation energy barriers compared with monometallic Cu nanoparticles. This study establishes a generalizable strategy for the interfacial synthesis of alloyed clusters from molecular precursors and provides mechanistic insight into how precursor design governs nanostructure formation and catalytic behavior.

N-heterocyclic carbene↗
NASA NTRS1991

Fuzzy Logic Path Planning System for Collision Avoidance by an Autonomous Rover Vehicle

Systems already developed at JSC have shown the benefits of applying fuzzy logic control theory to space related operations. Four major issues are addressed that are associated with developing an autonomous collision avoidance subsystem within a path planning system designed for application in a remote, hostile environment that does not lend itself well to remote manipulation of the vehicle involved through Earth-based telecommunication. A good focus for this is unmanned exploration of the surface of Mars. The uncertainties involved indicate that robust approaches such as fuzzy logic control are particularly appropriate. The four major issues addressed are: (1) avoidance of a single fuzzy moving obstacle; (2) back off from a dead end in a static obstacle environment; (3) fusion of sensor data to detect obstacles; and (4) options for adaptive learning in a path planning system.

Murphy, Michael G.↗