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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 1,765 records · Page 98
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Computation-Efficient Algorithm for Distributed Feedback Optimization of Distribution Grids

Feedback-based optimization algorithms use real-time measurements to update the optimal control for the underlying system which may not be fully identified. Recently, we have developed a distributed feedback-based algorithm [1] that avoids the requirement of fast communication between central computing and local actuator/sensor agents. This paper extends the work by greatly reducing the number of copies of variables involved in the distributed feedback-based algorithm, which results in faster convergence and lower communication requirement. The main idea is to leverage the specific structural properties of the admittance matrix for distribution systems with tree network topology. We also show the effectiveness of the proposed algorithm in simulations.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Electricity Pricing aware Deep Reinforcement Learning based Intelligent HVAC Control

Recently, deep reinforcement learning (DRL) based intelligent control of Heating, Ventilation, and Air Conditioning (HVAC) has gained a lot of attention due to DRL's ability to optimally control HVAC for minimizing operational cost while maintaining resident's comfort. The success of such DRL-based techniques largely depends on the articulation of the problem in terms of states, actions, and reward function. Inclusion of the electricity pricing information in the problem formulation can play an important role in saving the cost of HVAC operation. However, less attention has been given in the literature on formulating well-crafted state features based on electricity pricing. In this work, we propose an approach for training the DRL model with a specific focus on feature engineering based on electricity pricing. During training, we generate random but sufficiently realistic electricity price signals so that the pre-trained DRL model is robust and adaptive to the dynamic and variable electricity prices. The validation results are encouraging and show the potential of ≈12%-15% savings in the one day cost of HVAC operation, proving the usefulness of including electricity pricing related features as state features.

Kurte, Kuldeep↗
NASA NTRS1973

The preview control problem with application to man-machine system analysis

The preview control problem is formulated in a general form and its solution is obtained. The analytical tool used is discrete stochastic optimal control theory. Aiming the application to manual control situations with preview, time delay, observation noise, motor noise, etc. were included in formulating the problem. Manual preview control experiments were performed to qualitatively check the validity of the model, and it was found that the mechanism of the manual control problem was explained by the developed model.

Tomizuka, M.↗
NASA NTRS1988

International Conference on Advances in Communication and Control Systems, 1st, Washington, DC, June 18-20, 1987, Proceedings

Theoretical models of communication and control systems are discussed in reviews and reports. Topics addressed include smoothing and identification for random fields, the information and coding capacities of mismatched Gaussian channels, recursive least-squares estimation and Kalman filtering by systolic arrays, Kemp echo digital filters, a periodic test-scheduling scheme for communication and queuing processes, and receivers for direct-sequence systems. Consideration is given to a distributed-parameter model for detecting cracks in rotors, active control of aeroelastic systems governed by functional differential equations, robust multivariable control of large space structures, finite-rank relatively bounded perturbations of semigroup generators, and sensitivity analysis of convex optimal-control problems.

Declaris, Nicholas↗
NASA NTRS1989

Optimal aeroassisted guidance using Loh's term approximations

This paper presents three guidance algorithms for aerocapture and/or aeroassisted orbital transfer with plane change. All three algorithms are based on the approximate solution of an optimal control problem at each guidance update. The chief assumption is that Loh's term may be modeled as a function of the independent variable only. The first two algorithms maximize exit speed for fixed exit altitude, flight path angle and heading angle. The third minimizes, in one sense, the control effort for fixed exit altitude, flight path angle, heading angle and speed. Results are presented which indicate the near optimality of the solutions generated by the first two algorithms. Results are also presented which indicate the performance of the third algorithm in a simulation with unmodeled atmospheric density disturbances.

Mceneaney, W. M.↗
NASA NTRS2002

Direct Fault Tolerant RLV Altitude Control: A Singular Perturbation Approach

In this paper, we present a direct fault tolerant control (DFTC) technique, where by "direct" we mean that no explicit fault identification is used. The technique will be presented for the attitude controller (autopilot) for a reusable launch vehicle (RLV), although in principle it can be applied to many other applications. Any partial or complete failure of control actuators and effectors will be inferred from saturation of one or more commanded control signals generated by the controller. The saturation causes a reduction in the effective gain, or bandwidth of the feedback loop, which can be modeled as an increase in singular perturbation in the loop. In order to maintain stability, the bandwidth of the nominal (reduced-order) system will be reduced proportionally according to the singular perturbation theory. The presented DFTC technique automatically handles momentary saturations and integrator windup caused by excessive disturbances, guidance command or dispersions under normal vehicle conditions. For multi-input, multi-output (MIMO) systems with redundant control effectors, such as the RLV attitude control system, an algorithm is presented for determining the direction of bandwidth cutback using the method of minimum-time optimal control with constrained control in order to maintain the best performance that is possible with the reduced control authority. Other bandwidth cutback logic, such as one that preserves the commanded direction of the bandwidth or favors a preferred direction when the commanded direction cannot be achieved, is also discussed. In this extended abstract, a simplistic example is proved to demonstrate the idea. In the final paper, test results on the high fidelity 6-DOF X-33 model with severe dispersions will be presented.

Zhu, J. J.↗
DOE OSTI2024

A Transfer Learning Strategy for Improving the Data Efficiency of Deep Reinforcement Learning Control in Smart Buildings

Reinforcement learning (RL) is a powerful tool that has shown promising results in many domains such as robotics and game-playing. Because RL algorithms learn optimal control policies by continuously interacting with their environments, these algorithms require a lot of data to learn, which limits their application to a wide range of domains. For this reason, there is an immense need for improving the training and data efficiency of RL. Towards addressing this research gap, this paper proposes a transfer learning (TL) approach to improve the efficiency of the RL algorithms by reducing data need and, thus, reducing training time. To demonstrate the proposed approach, a knowledge transfer from a set of buildings to another building was conducted. The results show that the proposed TL approach is a promising method that can efficiently harness the information from similar RL tasks and reduce the data needs of RL algorithms.

Amasyali, Kadir↗
NASA NTRS1978

The 14th Annual Conference on Manual Control

Human operator dynamics during actual manual control or while monitoring the automatic control systems involved in air-to-air tracking, automobile driving, the operator of undersea vehicles, and remote handling are examined. Optimal control models and the use of mathematical theory in representing man behavior in complex man machine system tasks are discussed with emphasis on eye/head tracking and scanning; perception and attention allocation; decision making; and motion simulation and effects.

Source record↗
NASA NTRS1989

An optimal momentum management controller for the Space Station

This paper presents a new sequential design procedure for determining an optimal CMG (control moment gyro) momentum management and attitude control system for the Space Station Freedom. First, the Space Station equations of motion are linearized and uncoupled, and the associated state space equations are defined. Next, a new sequential procedure is used for the development of a continuous quadratic regulator with eigenvalue placement in a specified region of the complex plane. The regional pole assignment method is utilized since it is best suited for tradeoffs between eigenvalue locations and robustness with respect to parameter variations, sensor failures, implementation accuracies and gain reductions. The matrix sign function is used for solving the Riccati equations which appear in the design procedure. Simulation results are given which show that the resultant design provides desired system performance.

Sunkel, J. W.↗
NASA NTRS1990

Kinematically redundant arm formulations for coordinated multiple arm implementations

Although control laws for kinematically redundant robotic arms were presented as early as 1969, redundant arms have only recently become recognized as viable solutions to limitations inherent to kinematically sufficient arms. The advantages of run-time control optimization and arm reconfiguration are becoming increasingly attractive as the complexity and criticality of robotic systems continues to progress. A generalized control law for a spatial arm with 7 or more degrees of freedom (DOF) based on Whitney's resolved rate formulation is given. Results from a simulation implementation utilizing this control law are presented. Furthermore, results from a two arm simulation are presented to demonstrate the coordinated control of multiple arms using this formulation.

Robert W Bailey↗
NASA NTRS1992

Canonical transformations for space trajectory optimization

Canonical transformations are developed between the Cartesian coordinates, equinoctial elements, trajectory variables, and orbital elements for coplanar space trajectory optimization problems. The canonical transformations permit the state and adjoint or their solution, transversality conditions, the optimal control, and integrals of the motion, to be transformed between any of the common sets of coordinates for planar space trajectory optimization problems. Variations on the canonical transformations shown are straightforward to develop given the group properties of the canonical transformations.

Haissig, Christine M.↗
NASA NTRS1991

The minimum control authority of a system of actuators with applications to Gravity Probe-B

The forcing capabilities of systems composed of many actuators are analyzed in this paper. Multiactuator systems can generate higher forces in some directions than in others. Techniques are developed to find the force in the weakest direction. This corresponds to the worst-case output and is defined as the 'minimum control authority'. The minimum control authority is a function of three things: the actuator configuration, the actuator controller and the way in which the output of the system is limited. Three output limits are studied: (1) fuel-flow rate, (2) power, and (3) actuator output. The three corresponding actuator controllers are derived. These controllers generate the desired force while minimizing either fuel flow rate, power or actuator output. It is shown that using the optimal controller can substantially increase the minimum control authority. The techniques for calculating the minimum control authority are applied to the Gravity Probe-B spacecraft thruster system. This example shows that the minimum control authority can be used to design the individual actuators, choose actuator configuration, actuator controller, and study redundancy.

Wiktor, Peter↗
NASA NTRS1997

Simulation of the Predictive Control Algorithm for Container Crane Operation using Matlab Fuzzy Logic Tool Box

This research has investigated the use of fuzzy logic, via the Matlab Fuzzy Logic Tool Box, to design optimized controller systems. The engineering system for which the controller was designed and simulate was the container crane. The fuzzy logic algorithm that was investigated was the 'predictive control' algorithm. The plant dynamics of the container crane is representative of many important systems including robotic arm movements. The container crane that was investigated had a trolley motor and hoist motor. Total distance to be traveled by the trolley was 15 meters. The obstruction height was 5 meters. Crane height was 17.8 meters. Trolley mass was 7500 kilograms. Load mass was 6450 kilograms. Maximum trolley and rope velocities were 1.25 meters per sec. and 0.3 meters per sec., respectively. The fuzzy logic approach allowed the inclusion, in the controller model, of performance indices that are more effectively defined in linguistic terms. These include 'safety' and 'cargo swaying'. Two fuzzy inference systems were implemented using the Matlab simulation package, namely the Mamdani system (which relates fuzzy input variables to fuzzy output variables), and the Sugeno system (which relates fuzzy input variables to crisp output variable). It is found that the Sugeno FIS is better suited to including aspects of those plant dynamics whose mathematical relationships can be determined.

Richardson, Albert O.↗
NASA NTRS2005

Motion Cueing Algorithm Development: Human-Centered Linear and Nonlinear Approaches

While the performance of flight simulator motion system hardware has advanced substantially, the development of the motion cueing algorithm, the software that transforms simulated aircraft dynamics into realizable motion commands, has not kept pace. Prior research identified viable features from two algorithms: the nonlinear "adaptive algorithm", and the "optimal algorithm" that incorporates human vestibular models. A novel approach to motion cueing, the "nonlinear algorithm" is introduced that combines features from both approaches. This algorithm is formulated by optimal control, and incorporates a new integrated perception model that includes both visual and vestibular sensation and the interaction between the stimuli. Using a time-varying control law, the matrix Riccati equation is updated in real time by a neurocomputing approach. Preliminary pilot testing resulted in the optimal algorithm incorporating a new otolith model, producing improved motion cues. The nonlinear algorithm vertical mode produced a motion cue with a time-varying washout, sustaining small cues for longer durations and washing out large cues more quickly compared to the optimal algorithm. The inclusion of the integrated perception model improved the responses to longitudinal and lateral cues. False cues observed with the NASA adaptive algorithm were absent. The neurocomputing approach was crucial in that the number of presentations of an input vector could be reduced to meet the real time requirement without degrading the quality of the motion cues.

Houck, Jacob A.↗
NASA NTRS1973

Some optimal considerations in attitude control systems

The conventional six-engine reaction control jet relay attitude control law with deadband is shown to be a good linear approximation to a weighted time-fuel optimal control law. Techniques for evaluating the value of the relative weighting between time and fuel for a particular relay control law is studied along with techniques to interrelate other parameters for the two control laws. Vehicle attitude control laws employing control moment gyros are then investigated. Steering laws obtained from the expression for the reaction torque of the gyro configuration are compared to a total optimal attitude control law that is derived from optimal linear regulator theory. This total optimal attitude control law has computational disadvantages in the solving of the matrix Riccati equation. Several computational algorithms for solving the matrix Riccati equation are investigated with respect to accuracy, computational storage requirements, and computational speed.

Boland, J. S., III↗