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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

Extrapolation limitations of multilayer feedforward neural networks

The limitations of backpropagation used as a function extrapolator were investigated. Four common functions were used to investigate the network's extrapolation capability. The purpose of the experiment was to determine whether neural networks are capable of extrapolation and, if so, to determine the range for which networks can extrapolate. The authors show that neural networks cannot extrapolate and offer an explanation to support this result.

Haley, Pamela J.↗
NASA NTRS1998

Application of Multilayer Feedforward Neural Networks to Precipitation Cell-Top Altitude Estimation

The use of passive 118-GHz O2 observations of rain cells for precipitation cell-top altitude estimation is demonstrated by using a multilayer feed forward neural network retrieval system. Rain cell observations at 118 GHz were compared with estimates of the cell-top altitude obtained by optical stereoscopy. The observations were made with 2 4 km horizontal spatial resolution by using the Millimeter-wave Temperature Sounder (MTS) scanning spectrometer aboard the NASA ER-2 research aircraft during the Genesis of Atlantic Lows Experiment (GALE) and the COoperative Huntsville Meteorological EXperiment (COHMEX) in 1986. The neural network estimator applied to MTS spectral differences between clouds, and nearby clear air yielded an rms discrepancy of 1.76 km for a combined cumulus, mature, and dissipating cell set and 1.44 km for the cumulus-only set. An improvement in rms discrepancy to 1.36 km was achieved by including additional MTS information on the absolute atmospheric temperature profile. An incremental method for training neural networks was developed that yielded robust results, despite the use of as few as 56 training spectra. Comparison of these results with a nonlinear statistical estimator shows that superior results can be obtained with a neural network retrieval system. Imagery of estimated cell-top altitudes was created from 118-GHz spectral imagery gathered from CAMEX, September through October 1993, and from cyclone Oliver, February 7, 1993.

Spina, Michelle S.↗
NASA NTRS1983

Input filter compensation for switching regulators

A novel input filter compensation scheme for a buck regulator that eliminates the interaction between the input filter output impedance and the regulator control loop is presented. The scheme is implemented using a feedforward loop that senses the input filter state variables and uses this information to modulate the duty cycle signal. The feedforward design process presented is seen to be straightforward and the feedforward easy to implement. Extensive experimental data supported by analytical results show that significant performance improvement is achieved with the use of feedforward in the following performance categories: loop stability, audiosusceptibility, output impedance and transient response. The use of feedforward results in isolating the switching regulator from its power source thus eliminating all interaction between the regulator and equipment upstream. In addition the use of feedforward removes some of the input filter design constraints and makes the input filter design process simpler thus making it possible to optimize the input filter. The concept of feedforward compensation can also be extended to other types of switching regulators.

Kelkar, S. S.↗
NASA NTRS1992

Passivity/Lyapunov based controller design for trajectory tracking of flexible joint manipulators

A passivity and Lyapunov based approach for the control design for the trajectory tracking problem of flexible joint robots is presented. The basic structure of the proposed controller is the sum of a model-based feedforward and a model-independent feedback. Feedforward selection and solution is analyzed for a general model for flexible joints, and for more specific and practical model structures. Passivity theory is used to design a motor state-based controller in order to input-output stabilize the error system formed by the feedforward. Observability conditions for asymptotic stability are stated and verified. In order to accommodate for modeling uncertainties and to allow for the implementation of a simplified feedforward compensation, the stability of the system is analyzed in presence of approximations in the feedforward by using a Lyapunov based robustness analysis. It is shown that under certain conditions, e.g., the desired trajectory is varying slowly enough, stability is maintained for various approximations of a canonical feedforward.

Sicard, Pierre↗
DOE OSTI2025

A Reinforcement Learning Approach to Augment Conventional PID Control in Nuclear Power Plant Transient Operation

The ability of nuclear reactors to operate their power conversion cycles more flexibly will enhance their value to energy grids with variable pricing. Current nuclear control systems are typically classical controllers that are often based on proportional-integral-derivative (PID) control. This paper presents a method of augmenting the existing PID control for difficult transient operations in nuclear power plants using a reinforcement learning–derived feedforward signal applied in real time. The agents, which are trained on a test thermal load-following problem, are designed to improve steam generator outlet temperature control for a range of fast load-following scenarios covering ramp rates from 9%/min to 15%/min. Several reinforcement learning algorithms were initially investigated for the training of the feedforward agents with deep Q-learning (DQN) and proximal policy optimization (PPO) networks, which were found to be the most promising. The DQN controllers utilize discrete actions, giving them a better disturbance rejection at steady state but inconsistent response to initial temperature deviations. In contrast, PPO-trained agents, which take continuous actions except for a dead zone around zero, were shown to have the best combination of high disturbance rejection at steady state and good tracking of the desired temperature value. The ability of the PPO agent was also examined, with the average time of decision making found to be on the order of 1 ms. The fault properties of the controller under the loss of the reinforcement learning agent feedforward signal were also examined. The controller showed strong performance in situations of “no-signal” faults. but was less good at handling “stuck-at” faults, where the feedforward signal remains at a set value. In both cases, however, the PID was able to successfully maintain stability, eventually returning the system to a steady state. It is hoped that this work will allow for the proposed control architecture to be examined for more difficult control problems such that it may eventually be used to adapt existing nuclear plants for more aggressive load-following on grids of the future.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS1987

An approach to multivariable control of manipulators

The paper presents simple schemes for multivariable control of multiple-joint robot manipulators in joint and Cartesian coordinates. The joint control scheme consists of two independent multivariable feedforward and feedback controllers. The feedforward controller is the minimal inverse of the linearized model of robot dynamics and contains only proportional-double-derivative (PD2) terms - implying feedforward from the desired position, velocity and acceleration. This controller ensures that the manipulator joint angles track any reference trajectories. The feedback controller is of proportional-integral-derivative (PID) type and is designed to achieve pole placement. This controller reduces any initial tracking error to zero as desired and also ensures that robust steady-state tracking of step-plus-exponential trajectories is achieved by the joint angles. Simple and explicit expressions of computation of the feedforward and feedback gains are obtained based on the linearized model of robot dynamics. This leads to computationally efficient schemes for either on-line gain computation or off-line gain scheduling to account for variations in the linearized robot model due to changes in the operating point. The joint control scheme is extended to direct control of the end-effector motion in Cartesian space. Simulation results are given for illustration.

Seraji, H.↗
NASA NTRS1989

Robust high-performance control for robotic manipulators

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies were merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal componet that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nomical feedforward signal.

Seraji, Homayoun↗
NASA NTRS1991

Robust high-performance control for robotic manipulators

Model-based and performance-based control techniques are combined for an electrical robotic control system. Thus, two distinct and separate design philosophies have been merged into a single control system having a control law formulation including two distinct and separate components, each of which yields a respective signal component that is combined into a total command signal for the system. Those two separate system components include a feedforward controller and a feedback controller. The feedforward controller is model-based and contains any known part of the manipulator dynamics that can be used for on-line control to produce a nominal feedforward component of the system's control signal. The feedback controller is performance-based and consists of a simple adaptive PID controller which generates an adaptive control signal to complement the nominal feedforward signal.

Seraji, Homayoun↗
NASA NTRS1982

Input filter compensation for switching regulators

The problems caused by the interaction between the input filter, output filter, and the control loop are discussed. The input filter design is made more complicated because of the need to avoid performance degradation and also stay within the weight and loss limitations. Conventional input filter design techniques are then dicussed. The concept of pole zero cancellation is reviewed; this concept is the basis for an approach to control the peaking of the output impedance of the input filter and thus mitigate some of the problems caused by the input filter. The proposed approach for control of the peaking of the output impedance of the input filter is to use a feedforward loop working in conjunction with feedback loops, thus forming a total state control scheme. The design of the feedforward loop for a buck regulator is described. A possible implementation of the feedforward loop design is suggested.

Lee, F. C.↗
NASA NTRS1984

Input filter compensation for switching regulators

Problems caused by input filter interaction and conventional input filter design techniques are discussed. The concept of feedforward control is modeled with an input filter and a buck regulator. Experimental measurement and comparison to the analytical predictions is carried out. Transient response and the use of a feedforward loop to stabilize the regulator system is described. Other possible applications for feedforward control are included.

Lee, F. C.↗
NASA NTRS1983

Stability analysis of a buck regulator employing input filter compensation

The interaction between the input filter and the regulator often causes serious degradation of performance. The reduction in loop gain due to input filter interaction can result in system instability. An exact stability analysis of the buck regulator system is presented. The input filter parameter values are varied and system instability is predicted for the case without feedforward. The eigenvalues of the system can be brought back into the unit circle and the system thus stabilized with the addition of the feedforward loop. Measurements made for the cases with and without feedforward confirm the analytical prediction.

Kelkar, S. S.↗
NASA NTRS1991

From biological neural networks to thinking machines: Transitioning biological organizational principles to computer technology

The three-dimensional organization of the vestibular macula is under study by computer assisted reconstruction and simulation methods as a model for more complex neural systems. One goal of this research is to transition knowledge of biological neural network architecture and functioning to computer technology, to contribute to the development of thinking computers. Maculas are organized as weighted neural networks for parallel distributed processing of information. The network is characterized by non-linearity of its terminal/receptive fields. Wiring appears to develop through constrained randomness. A further property is the presence of two main circuits, highly channeled and distributed modifying, that are connected through feedforward-feedback collaterals and biasing subcircuit. Computer simulations demonstrate that differences in geometry of the feedback (afferent) collaterals affects the timing and the magnitude of voltage changes delivered to the spike initiation zone. Feedforward (efferent) collaterals act as voltage followers and likely inhibit neurons of the distributed modifying circuit. These results illustrate the importance of feedforward-feedback loops, of timing, and of inhibition in refining neural network output. They also suggest that it is the distributed modifying network that is most involved in adaptation, memory, and learning. Tests of macular adaptation, through hyper- and microgravitational studies, support this hypothesis since synapses in the distributed modifying circuit, but not the channeled circuit, are altered. Transitioning knowledge of biological systems to computer technology, however, remains problematical.

Ross, Muriel D.↗
NASA NTRS1991

Model reference adaptive control of flexible robots in the presence of sudden load changes

Direct command generator tracker based model reference adaptive control (MRAC) algorithms are applied to the dynamics for a flexible-joint arm in the presence of sudden load changes. Because of the need to satisfy a positive real condition, such MRAC procedures are designed so that a feedforward augmented output follows the reference model output, thus, resulting in an ultimately bounded rather than zero output error. Thus, modifications are suggested and tested that: (1) incorporate feedforward into the reference model's output as well as the plant's output, and (2) incorporate a derivative term into only the process feedforward loop. The results of these simulations give a response with zero steady state model following error, and thus encourage further use of MRAC for more complex flexibile robotic systems.

Steinvorth, Rodrigo↗
NASA NTRS1993

Slewing maneuvers and vibration control of space structures by feedforward/feedback moment-gyro controls

This paper presents a moment-gyro control approach to the maneuver and vibration suppression of a flexible truss arm undergoing a constant slewing motion. The overall slewing motion is triggered by a feedforward input, and a companion feedback controller is employed to augment the feedforward input and subsequently to control vibrations. The feedforward input for the given motion requirement is determined from the combined CMG (Control Momentum Gyro) devices and the desired rigid-body motion. The rigid-body dynamic model has enabled us to identify the attendant CMG momentum saturation constraints. The task for vibration control is carried out in two stages; first in the search of a suitable CMG placement along the beam span for various slewing maneuvers, and subsequently in the development of Liapunov-based control algorithms for CMG spin-stabilization. Both analytical and numerical results are presented to show the effectiveness of the present approach.

Yang, Li-Farn↗