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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 1,207 records · Page 67
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

A parallel row-based algorithm with error control for standard-cell replacement on a hypercube multiprocessor

A new row-based parallel algorithm for standard-cell placement targeted for execution on a hypercube multiprocessor is presented. Key features of this implementation include a dynamic simulated-annealing schedule, row-partitioning of the VLSI chip image, and two novel new approaches to controlling error in parallel cell-placement algorithms; Heuristic Cell-Coloring and Adaptive (Parallel Move) Sequence Control. Heuristic Cell-Coloring identifies sets of noninteracting cells that can be moved repeatedly, and in parallel, with no buildup of error in the placement cost. Adaptive Sequence Control allows multiple parallel cell moves to take place between global cell-position updates. This feedback mechanism is based on an error bound derived analytically from the traditional annealing move-acceptance profile. Placement results are presented for real industry circuits and the performance is summarized of an implementation on the Intel iPSC/2 Hypercube. The runtime of this algorithm is 5 to 16 times faster than a previous program developed for the Hypercube, while producing equivalent quality placement. An integrated place and route program for the Intel iPSC/2 Hypercube is currently being developed.

Sargent, Jeff Scott↗
NASA NTRS1985

Piloted simulation of an algorithm for onboard control of time-optimal intercept

A piloted simulation of algorithms for onboard computation of trajectories for time-optimal intercept of a moving target by an F-8 aircraft is described. The algorithms, use singular perturbation techniques, generate commands in the cockpit. By centering the horizontal and vertical needles, the pilot flies an approximation to a time-optimal intercept trajectory. Example simulations are shown and statistical data on the pilot's performance when presented with different display and computation modes are described.

Price, D. B.↗
NASA NTRS2006

Real-Time Feedback Control of Flow-Induced Cavity Tones: Adaptive Control - Part 2

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. Past input-output data and an estimate of the open-loop pulse response sequence are all that is needed to implement the algorithm for application at fixed Mach numbers. Transient measurements made during controller adaptation revealed that the controller coefficients converged to a steady state in the mean, and this implies that adaptation can be turned off at some point with no degradation in control performance. When converged, the control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. However, as in the case of fixed-gain GPC, the adaptive GPC performance was limited by spillover in sidebands around the suppressed Rossiter modes. The algorithm was also able to maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Beyond this range, stable operation of the control algorithm was not possible due to the fixed plant model in the algorithm.

Kegerise, M. A.↗
NASA NTRS1992

Full design of fuzzy controllers using genetic algorithms

This paper examines the applicability of genetic algorithms in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.

Homaifar, Abdollah↗
NASA NTRS2006

Real-Time Feedback Control of Flow-Induced Cavity Tones: Fixed-Gain Control - Part 1

A generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The control algorithm demonstrated multiple Rossiter-mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are collocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible with the present sensor/actuator arrangement. In the control-algorithm development, the cavity dynamics were treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support to that treatment.

Kegerise, M. A.↗
NASA NTRS1989

Input-output oriented computation algorithms for the control of large flexible structures

An overview is given of work in progress aimed at developing computational algorithms addressing two important aspects in the control of large flexible space structures; namely, the selection and placement of sensors and actuators, and the resulting multivariable control law design problem. The issue of sensor/actuator set selection is particularly crucial to obtaining a satisfactory control design, as clearly a poor choice will inherently limit the degree to which good control can be achieved. With regard to control law design, the researchers are driven by concerns stemming from the practical issues associated with eventual implementation of multivariable control laws, such as reliability, limit protection, multimode operation, sampling rate selection, processor throughput, etc. Naturally, the burden imposed by dealing with these aspects of the problem can be reduced by ensuring that the complexity of the compensator is minimized. Our approach to these problems is based on extensions to input/output oriented techniques that have proven useful in the design of multivariable control systems for aircraft engines. In particular, researchers are exploring the use of relative gain analysis and the condition number as a means of quantifying the process of sensor/actuator selection and placement for shape control of a large space platform.

Minto, K. D.↗
NASA NTRS1993

Application of genetic algorithms to tuning fuzzy control systems

Real number genetic algorithms (GA) were applied for tuning fuzzy membership functions of three controller applications. The first application is our 'Fuzzy Pong' demonstration, a controller that controls a very responsive system. The performance of the automatically tuned membership functions exceeded that of manually tuned membership functions both when the algorithm started with randomly generated functions and with the best manually-tuned functions. The second GA tunes input membership functions to achieve a specified control surface. The third application is a practical one, a motor controller for a printed circuit manufacturing system. The GA alters the positions and overlaps of the membership functions to accomplish the tuning. The applications, the real number GA approach, the fitness function and population parameters, and the performance improvements achieved are discussed. Directions for further research in tuning input and output membership functions and in tuning fuzzy rules are described.

Espy, Todd↗
NASA NTRS1992

Full design of fuzzy controllers using genetic algorithms

This paper examines the applicability of genetic algorithms (GA) in the complete design of fuzzy logic controllers. While GA has been used before in the development of rule sets or high performance membership functions, the interdependence between these two components dictates that they should be designed together simultaneously. GA is fully capable of creating complete fuzzy controllers given the equations of motion of the system, eliminating the need for human input in the design loop. We show the application of this new method to the development of a cart controller.

Homaifar, Abdollah↗
NASA NTRS2004

Real-Time Adaptive Control of Flow-Induced Cavity Tones

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. The adaptive control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. The algorithm was also able t o maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are colocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible. In the control-algorithm development, the cavity dynamics are treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support this treatment.

Kegerise, Michael A.↗
NASA NTRS1994

Massively Parallel Algorithms for Real-Time Wavefront Control of a Dense Adaptive Optics System

In this paper massively parallel algorithms and architectures for real-time wavefront control of a dense adaptive optic system (SELENE) are presented. We have already shown that the computation of a near optimal control algorithm for SELENE can be reduced to the solution of a discrete Poisson equation on a regular domain. Although this represents an optimal computation, due the large size of the system and the high sampling rate requirement, the implementation of this control algorithm poses a computationally challenging problem since it demands a sustained computational throughput of the order of 10 GFlops. We develop a novel algorithm, designated as Fast Invariant Imbedding algorithm, which offers a massive degree of parallelism with simple communication and synchronization requirements. Due to these features, our algorithm is significantly more efficient than other Fast Poisson Solvers for implementation on massively parallel architectures.

massively↗
NASA NTRS2009

Orion Guidance and Control Ascent Abort Algorithm Design and Performance Results

During the ascent flight phase of NASA s Constellation Program, the Ares launch vehicle propels the Orion crew vehicle to an agreed to insertion target. If a failure occurs at any point in time during ascent then a system must be in place to abort the mission and return the crew to a safe landing with a high probability of success. To achieve continuous abort coverage one of two sets of effectors is used. Either the Launch Abort System (LAS), consisting of the Attitude Control Motor (ACM) and the Abort Motor (AM), or the Service Module (SM), consisting of SM Orion Main Engine (OME), Auxiliary (Aux) Jets, and Reaction Control System (RCS) jets, is used. The LAS effectors are used for aborts from liftoff through the first 30 seconds of second stage flight. The SM effectors are used from that point through Main Engine Cutoff (MECO). There are two distinct sets of Guidance and Control (G&C) algorithms that are designed to maximize the performance of these abort effectors. This paper will outline the necessary inputs to the G&C subsystem, the preliminary design of the G&C algorithms, the ability of the algorithms to predict what abort modes are achievable, and the resulting success of the abort system. Abort success will be measured against the Preliminary Design Review (PDR) abort performance metrics and overall performance will be reported. Finally, potential improvements to the G&C design will be discussed.

Proud, Ryan W.↗
NASA NTRS1990

A computational algorithm for spacecraft control and momentum management

Developments in the area of nonlinear control theory have shown how coordinate changes in the state and input spaces of a dynamical system can be used to transform certain nonlinear differential equations into equivalent linear equations. These techniques are applied to the control of a spacecraft equipped with momentum exchange devices. An optimal control problem is formulated that incorporates a nonlinear spacecraft model. An algorithm is developed for solving the optimization problem using feedback linearization to transform to an equivalent problem involving a linear dynamical constraint and a functional approximation technique to solve for the linear dynamics in terms of the control. The original problem is transformed into an unconstrained nonlinear quadratic program that yields an approximate solution to the original problem. Two examples are presented to illustrate the results.

Dzielski, John↗
NASA NTRS1987

An analysis of redundancy management algorithms for asynchronous fault tolerant control systems

Redundancy management algorithms, commonly referred to as voters, are algorithms used in fault-tolerant control systems to vote on incoming redundant data, isolate bad signals, and output a single good value. In a synchronous environment, this algorithm is a straightforward signal-to-signal comparison with relatively low complexity. The technology of asynchronous control systems, recently realized in the Ultrareliable Fault Tolerant Control System research program at NASA Ames Research Center, requires more complex algorithms for fault detection and signal selection. A variety of algorithms used for this process, a means of testing them, and their basic performance under a simulated environment of the ultrareliable fault-tolerant control system are presented.

Davis, Gloria J.↗
NASA NTRS1991

Predictive control and estimation algorithms for the NASA/JPL 70-meter antennas

A modified output prediction procedure and a new controller design is presented based on the predictive control law. Also, a new predictive estimator is developed to complement the controller and to enhance system performance. The predictive controller is designed and applied to the tracking control of the Deep Space Network 70 m antennas. Simulation results show significant improvement in tracking performance over the linear quadratic controller and estimator presently in use.

Gawronski, W.↗
DOE OSTI2024

A safe reinforcement learning algorithm for supervisory control of power plants

Traditional control theory-based methods require tailored engineering for each system and constant fine-tuning. In power plant control, one often needs to obtain a precise representation of the system dynamics and carefully design the control scheme accordingly. Model-free Reinforcement learning (RL) has emerged as a promising solution for control tasks due to its ability to learn from trial-and-error interactions with the environment. It eliminates the need for explicitly modeling the environment’s dynamics, which is potentially inaccurate. However, the direct imposition of state constraints in power plant control raises challenges for standard RL methods. To address this, we propose a chance-constrained RL algorithm based on Proximal Policy Optimization for supervisory control. Our method employs Lagrangian relaxation to convert the constrained optimization problem into an unconstrained objective, where trainable Lagrange multipliers enforce the state constraints. In conclusion, our approach achieves the smallest distance of violation and violation rate in a load-follow maneuver for an advanced Nuclear Power Plant design.

constrained optimization↗