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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 847 records · Page 47

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Robust Adaptive Decentralized Dynamic State Estimation with Unknown Control Inputs using Field PMU Measurements

This paper proposes a robust adaptive decentralized dynamic state estimation method for power system with unknown inputs of the highly detailed synchronous machine model. The temporal and spatial correlations among the unknown inputs are used to derive a vector auto-regressive model. The latter is further integrated together with state transition and measurement models for joint state and unknown inputs estimation. Thanks to the consideration of implicit cross-correlations between the states and the unknown inputs, only generator terminal voltage and current phasors are needed. Test results on the US WECC system using the field PMU measurements show that the proposed method is able to track both the system dynamic states and unknown controller inputs. These information could significantly benefit the validation and calibration of generator controller parameters.

Zhao, Junbo↗

NASA NTRS1985

A Study on the Control of Third Generation Spacecraft

An overview of some studies which have recently been carried out on the control of third generation spcecraft, as modelled by the MSAT space vehicle configuration, is made. This spacecraft is highly nonsymmetrical and has appendages which cannot in general be assumed to be rigid. In particular, it is desired to design a controller for MSAT which stabilizes the system and satisfies certain attitude control, shape control, and possibly stationkeeping requirements; in addition, it is desired that the resultant controller should be robust and avoid any undesirable spill over effects. In addition, the controller obtained should have minimum complexity. The method of solution adopted to solve this class of problems is to formulate the problem as a robust servomechanism problem, and thence to obtain existence conditions and a controller characterization to solve the problem. The final controller obtained for MSAT has a distributed control configuration and appears to be quite satisfactory.

Davison, E. J.↗

DOE OSTI2021

Biocatalytic Yarn for Peroxide Decomposition with Controlled Liquid Transport

In this study, a robust biocatalytic yarn with controllable liquid transport properties is created by coating thin layers of chitosan containing catalase onto a cellulosic yarn. The resulting material integrates enzyme catalytic functionality with protective coating properties of chitosan and structural functionality of the textile. Mild immobilization conditions and good affinity between the two polysaccharides minimize enzyme inactivation during the preparation steps and prevent enzyme from leaching during peroxide decomposition testing and washing, providing a novel and versatile enzyme immobilization strategy. The catalytic efficiency of enzymes in a reaction containing solid, liquid, and gas phases is facilitated when dissolved enzyme substrate is transported by liquid flowing through the coated textile structure. The flow-through configuration decomposes at least two times more peroxide in a twenty-times smaller reaction zone volume compared to a stirred tank configuration. Liquid transport through the yarn and liquid spatial distribution within the yarn are investigated by in situ neutron radiography and neutron computed tomography, revealing a constrained wicking mechanism that benefits biocatalytic yarn performance. This new class of sustainable and flexible biocatalytic textile matrices has beneficial multifunctional properties, not previously described, that are applicable for numerous small- and large-scale applications including controlled flow reactors and reactive filtration.

36 MATERIALS SCIENCE↗

NASA NTRS1992

Self-learning fuzzy controllers based on temporal back propagation

This paper presents a generalized control strategy that enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near-optimal manner. This methodology, termed temporal back propagation, is model-insensitive in the sense that it can deal with plants that can be represented in a piecewise-differentiable format, such as difference equations, neural networks, GMDH structures, and fuzzy models. Regardless of the numbers of inputs and outputs of the plants under consideration, the proposed approach can either refine the fuzzy if-then rules if human experts, or automatically derive the fuzzy if-then rules obtained from human experts are not available. The inverted pendulum system is employed as a test-bed to demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired fuzzy controller.

Jang, Jyh-Shing R.↗

NASA NTRS2000

Robust Inversion and Data Compression in Control Allocation

We present an off-line computational method for control allocation design. The control allocation function delta = F(z)tau = delta (sub 0) (z) mapping commanded body-frame torques to actuator commands is implicitly specified by trim condition delta (sub 0) (z) and by a robust pseudo-inverse problem double vertical line I - G(z) F(z) double vertical line less than epsilon (z) where G(z) is a system Jacobian evaluated at operating point z, z circumflex is an estimate of z, and epsilon (z) less than 1 is a specified error tolerance. The allocation function F(z) = sigma (sub i) psi (z) F (sub i) is computed using a heuristic technique for selecting wavelet basis functions psi and a constrained least-squares criterion for selecting the allocation matrices F (sub i). The method is applied to entry trajectory control allocation for a reusable launch vehicle (X-33).

Hodel, A. Scottedward↗

NASA NTRS1990

Active flutter and gust response control

After a short recall concerning the aeroelastic equations, active control law based on optimal stochastic control theory is synthesized for a wing flutter and gust response. Robustness of the control system due to structured and unstructured uncertainties is considered. Robustness recovery technique is applied to improve the stability margin.

Oli, Muluneh↗

NASA NTRS1987

Active stability augmentation of large space structures: A stochastic control problem

A problem in SCOLE is that of slewing an offset antenna on a long flexible beam-like truss attached to the space shuttle, with rather stringent pointing accuracy requirements. The relevant methodology aspects in robust feedback-control design for stability augmentation of the beam using on-board sensors is examined. It is framed as a stochastic control problem, boundary control of a distributed parameter system described by partial differential equations. While the framework is mathematical, the emphasis is still on an engineering solution. An abstract mathematical formulation is developed as a nonlinear wave equation in a Hilbert space. That the system is controllable is shown and a feedback control law that is robust in the sense that it does not require quantitative knowledge of system parameters is developed. The stochastic control problem that arises in instrumenting this law using appropriate sensors is treated. Using an engineering first approximation which is valid for small damping, formulas for optimal choice of the control gain are developed.

Balakrishnan, A. V.↗

NASA NTRS1993

Robust fuel- and time-optimal control of uncertain flexible space structures

The problem of computing open-loop, fuel- and time-optimal control inputs for flexible space structures in the face of modeling uncertainty is investigated. Robustified, fuel- and time-optimal pulse sequences are obtained by solving a constrained optimization problem subject to robustness constraints. It is shown that 'bang-off-bang' pulse sequences with a finite number of switchings provide a practical tradeoff among the maneuvering time, fuel consumption, and performance robustness of uncertain flexible space structures.

Wie, Bong↗

NASA NTRS1991

Investigation of air transportation technology at Princeton University, 1990-1991

The Air Transportation Technology Program at Princeton University is a program that emphasizes graduate and undergraduate student research. The program proceeded along six avenues during the past year: microburst hazards to aircraft, intelligent failure tolerant control, computer-aided heuristics for piloted flight, stochastic robustness of flight control systems, neural networks for flight control, and computer-aided control system design.

Stengel, Robert F.↗

NASA NTRS2005

Instrumentation and Control Needs for Reliable Operation of Lunar Base Surface Nuclear Power Systems

As one of the near-term goals of the President's Vision for Space Exploration, establishment of a multi-person lunar base will require high-endurance power systems which are independent of the sun, and can operate without replenishment for several years. These requirements may be obtained using nuclear power systems specifically designed for use on the lunar surface. While it is envisioned that such a system will generally be supervised by humans, some of the evolutions required maybe semi or fully autonomous. The entire base complement for near-term missions may be less than 10 individuals, most or all of which may not be qualified nuclear plant operators and may be off-base for extended periods thus, the need for power system autonomous operation. Startup, shutdown, and load following operations will require the application of advanced control and health management strategies with an emphasis on robust, supervisory, coordinated control of, for example, the nuclear heat source, energy conversion plant (e.g., Brayton Energy Conversion units), and power management system. Autonomous operation implies that, in addition to being capable of automatic response to disturbance input or load changes, the system is also capable of assessing the status of the integrated plant, determining the risk associated with the possible actions, and making a decision as to the action that optimizes system performance while minimizing risk to the mission. Adapting the control to deviations from design conditions and degradation due to component failures will be essential to ensure base inhabitant safety and mission success. Intelligent decisions will have to be made to choose the right set of sensors to provide the data needed to do condition monitoring and fault detection and isolation because of liftoff weight and space limitations, it will not be possible to have an extensive set of instruments as used for earth-based systems. Advanced instrumentation and control technologies will be needed to enable this critical functionality of autonomous operation. It will be imperative to consider instrumentation and control requirements in parallel to system configuration development so as to identify control-related, as well as integrated system-related, problem areas early to avoid potentially expensive work-arounds . This paper presents an overview of the enabling technologies necessary for the development of reliable, autonomous lunar base nuclear power systems with an emphasis on system architectures and off-the-shelf algorithms rather than hardware. Autonomy needs are presented in the context of a hypothetical lunar base nuclear power system. The scenarios and applications presented are hypothetical in nature, based on information from open-literature sources, and only intended to provoke thought and provide motivation for the use of autonomous, intelligent control and diagnostics.

Turso, James↗

DOE OSTI2020

Optimal Eco-Driving Control of Connected and Autonomous Vehicles Through Signalized Intersections

This article focuses on the speed planning problem for connected and automated vehicles (CAVs) communicating to traffic lights. The uncertainty of traffic signal timing for signalized intersections on the road is considered. The eco-driving problem is formulated as a data-driven chance-constrained robust optimization problem. Effective red-light duration (ERD) is defined as a random variable, and describes the feasible passing time through the signalized intersections. Usually, the true probability distribution for ERD is unknown. Consequently, a data-driven approach is adopted to formulate chance constraints based on empirical sample data. This incorporates robustness into the eco-driving control problem with respect to uncertain signal timing. Dynamic programming (DP) is employed to solve the optimization problem. The simulation results demonstrate that the proposed method can generate optimal speed reference trajectories with 40% less vehicle fuel consumption, while maintaining the arrival time at a similar level compared to a modified intelligent driver model (IDM). The proposed control approach significantly improves the controller's robustness in the face of uncertain signal timing, without requiring to know the distribution of the random variable a priori.

33 ADVANCED PROPULSION SYSTEMS↗

NASA NTRS1993

Using manufacturing message specification for monitor and control at Venus

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying interprocessor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCC's) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment. The architecture is robust enough to meet current operational needs and flexible enough to provide a migration path for new subsystems. This paper will describe the architecture of the Venus M&C system, discuss how MMS was used and the requirements this imposed on other parts of the system, and provide results from systems and operational testing at the Venus site.

Heuser, W. Randy↗

NASA NTRS1992

Preliminary assessment of the robustness of dynamic inversion based flight control laws

Dynamic-inversion-based flight control laws present an attractive alternative to conventional gain-scheduled designs for high angle-of-attack maneuvering, where nonlinearities dominate the dynamics. Dynamic inversion is easily applied to the aircraft dynamics requiring a knowledge of the nonlinear equations of motion alone, rather than an extensive set of linearizations. However, the robustness properties of the dynamic inversion are questionable especially when considering the uncertainties involved with the aerodynamic database during post-stall flight. This paper presents a simple analysis and some preliminary results of simulations with a perturbed database. It is shown that incorporating integrators into the control loops helps to improve the performance in the presence of these perturbations.

Snell, S. A.↗

NASA NTRS2019

Modeling, Simulation, and Robust Design of the TSIS Pointing Controller for ISS Deployment

To ensure high quality TSIS science measurements, stringent requirements were levied on the pointing system performance. Several factors complicated the design of the pointing system controller including uncertainty in knowledge of the ISS base motion jitter, the use of direct drive brushless DC motors for the gimbal system, and the presence of TSIS structure low frequency modes. This paper will describe the modeling, simulation, analysis, and robust design techniques employed to reduce risk resulting in a pointing system that met requirements on-orbit.

Engelmann, Andrew↗

DOE OSTI2020

Optimal PV Inverter Control in Distribution Systems via Data-Driven Distributionally Robust Optimization

Distribution systems with high penetration of uncertain solar generation call for advanced control strategies of photovoltaics (PVs) inverters. This paper proposes a data-driven distributionally robust optimization (DDDRO) approach to optimally controlling the PV inverters to improve the system operation performance under solar power uncertainties. In the proposed DDDRO approach, a Wasserstein ball-based method is proposed to construct the distributional ambiguity set to model the uncertainties of PV generation through partial observations of historical data without knowing exact probability distributions. We further reformulate the computationally intractable DDDRO model to a mixed integer second order cone programming (MISOCP) problem. The effectiveness and out-of-sample performance of the proposed approach have been demonstrated on a modified IEEE 33-node system. We conduct a comparative study to compare the proposed method with traditional chance constrained programming (CCP). It shows that the proposed DDDRO approach can provide a less conservative yet robust solution to minimize the worse-case expectation of the total network loss while maintaining nodal voltages in a secure range.

Xue, Yaosuo↗

DOE OSTI2025

Enhancing Autonomous Control of Microreactors Using Multi-Agent Reinforcement Learning

In order for microreactors to be economically competitive, operation costs will need to be minimized through some degree of autonomous control. Previous work has demonstrated the effectiveness of reinforcement learning (RL) for load-following control in a drum-controlled microreactor. This study extends that work by exploring the potential of RL to independently control each of the reactor’s drums. We compare a single-agent RL approach with a multi-agent RL (MARL) framework, testing them for generalization across different load-following power profiles and control timescales, and for robustness in cases of randomly disabled control drums. Since the point kinetics simulation environment used in this study cannot resolve spatial effects, we assume that in the absence of spatially localized disturbances, optimal drum movements should be symmetrical. We demonstrate that single-agent RL is able to achieve accurate performance only when symmetric actions are ignored; otherwise, it fails to train a useful controller. Meanwhile, the MARL framework performs symmetric actions by design and trains a robust, accurate agent, as evidenced by mean absolute errors in power matching of 0.41% for the training power profile, 0.68% for a profile with half the drums disabled, and 0.21% for a profile on a realistic load-following time horizon.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1993

Using Manufacturing Message Specification for Monitor and Control at Venus

The flexibility and robustness of a monitor and control (M&C) system are a direct result of the underlying inter-processor communications architecture. A new architecture for M&C at the Deep Space Communications Complexes (DSCCs) has been developed based on the Manufacturing Message Specification (MMS) process control standard of the Open System Interconnection (OSI) suite of protocols. This architecture has been tested both in a laboratory environment and under operational conditions at the Deep Space Network (DSN) experimental Venus station (DSS-13). The Venus experience in the application of OSI standards to support M&C has been extremely successful. MMS meets the functional needs of the station and provides a level of flexibility and responsiveness previously unknown in that environment...

Stockett, Michael H.↗

NASA NTRS1983

Fractional representation theory - Robustness results with applications to finite dimensional control of a class of linear distributed systems

This paper reviews and extends the fractional representation theory. In particular, new and powerful robustness results are presented. This new theory is utilized to develop a preliminary design methodology for finite dimensional control of a class of linear evolution equations on a Banach space. The design is for stability in an input-output sense, but particular attention is paid to internal stability as well.

Nett, C. N.↗