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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Experimental implementation of adaptive control for flexible space structures

On-going research at The Aerospace Corporation studying the feasibility of applying adaptive control methodologies to the control of flexible space structures is described. A laboratory testbed was established to test system identification and control approaches. The laboratory set-up and controller design approach are discussed. The ARX least squares parameter estimation technique is analyzed in terms of frequency domain transfer function bias error. This analysis approach enables the determination of the effects of sampling rate, sensor type, and data prefiltering on the estimation performance. The ability to identify space structure dynamics over a range of frequencies is shown to be heavily dependent on these factors.

Mcgraw, Gary A.↗
NASA NTRS1985

The experimental results of a self tuning adaptive controller using online frequency identification

A fourth-order laboratory dynamic system featuring very low structural damping and a noncolocated actuator-sensor pair has been used to test a novel real-time adaptive controller, implemented in a minicomputer, which consists of a state estimator, a set of state feedback gains, and a frequency-locked loop for real-time parameter identification. The adaptation algorithm employed can correct controller error and stabilize the system for more than 50 percent variation in the plant's natural frequency, compared with a 10 percent stability margin in frequency variation for a fixed gain controller having the same performance as the nominal plant condition. The very rapid convergence achievable by this adaptive system is demonstrated experimentally, and proven with simple, root-locus methods.

Chiang, W.-W.↗
NASA NTRS1976

Digital adaptive control laws for the F-8

NASA is conducting a flight control research program in digital fly-by-wire technology using a modified F-8C aircraft. The first phase of this program used Apollo hardware to demonstrate the practicality of digital fly-by-wire in an actual test vehicle. For the second phase, conventional aircraft sensors and a large floating point digital computer are being utilized to test advanced control laws and redundancy concepts. As part of NASA's research in digital fly-by-wire technology, Honeywell developed digital adaptive flight control laws for flight test in the F-8C. Adaptation of the control laws was to be based on information sensed from conventional aircraft sensors excluding air data. The control laws were constrained to use only existing elevator, rudder, and ailerons as control effectors, each powered by existing actuators. Three adaptive control laws were successfully designed using maximum likelihood estimation, a Liapunov stable model tracker and a self-excited limit cycle concept. The maximum likelihood estimation design was selected as the most promising because of its capability to identify more than surface effectiveness parameters. The adaptive concepts, the control laws and comparisons of predicted performance are described.

Hartmann, G. L.↗
NASA NTRS1993

Neural self-tuning adaptive control of non-minimum phase system

The motivation of this research came about when a neural network direct adaptive control scheme was applied to control the tip position of a flexible robotic arm. Satisfactory control performance was not attainable due to the inherent non-minimum phase characteristics of the flexible robotic arm tip. Most of the existing neural network control algorithms are based on the direct method and exhibit very high sensitivity, if not unstable, closed-loop behavior. Therefore, a neural self-tuning control (NSTC) algorithm is developed and applied to this problem and showed promising results. Simulation results of the NSTC scheme and the conventional self-tuning (STR) control scheme are used to examine performance factors such as control tracking mean square error, estimation mean square error, transient response, and steady state response.

Ho, Long T.↗
NASA NTRS2018

Demonstration of the Space Launch System Augmenting Adaptive Control Algorithm on Pole-Cart Platform

NASA's baseline Space Launch System (SLS) ight control system (FCS) includes an adaptive augmenting control (AAC) portion in addition to the ight-heritage nominal classical controller. The AAC algorithm is intended to improve the robustness and performance of the classical controller. Over the past several years, the AAC algorithm developed at NASA Marshall Space Flight Center (MSFC) has matured significantly through extensive simulation, rigorous analytical proofs, and a series of successful ight tests on a F18 aircraft. This study was part of a SLS program and NASA Engineering and Safety Center (NESC) joint e ort to further increase the confidence level of the AAC algorithm by demonstrating its key functionalities on a classroom type of example, the pole-cart sys- tem, at the NASA Langley Research Center (LaRC) dynamics and control laboratory. The fundamental dynamics behind balancing an inverted pendulum is similar to controlling an aerodynamically unstable rocket. Both systems are inherently open-loop unstable and requires feedback control for attitude stabilization. The principles behind the AAC algorithm is applicable to a wide range of conditionally stable dynamical systems. Hence, the outcomes from this simple and inexpensive exercise has provided the SLS program with additional confidence into the AAC design, operation, robustness, and application.

Pei, Jing↗
NASA NTRS1988

A forward method for optimal stochastic nonlinear and adaptive control

A computational approach is taken to solve the optimal nonlinear stochastic control problem. The approach is to systematically solve the stochastic dynamic programming equations forward in time, using a nested stochastic approximation technique. Although computationally intensive, this provides a straightforward numerical solution for this class of problems and provides an alternative to the usual dimensionality problem associated with solving the dynamic programming equations backward in time. It is shown that the cost degrades monotonically as the complexity of the algorithm is reduced. This provides a strategy for suboptimal control with clear performance/computation tradeoffs. A numerical study focusing on a generic optimal stochastic adaptive control example is included to demonstrate the feasibility of the method.

Bayard, David S.↗
NASA NTRS1991

Adaptive control of interface by temperature and interface profile feedback in transparent multi-zone crystal growth furnace

The objective of this research is to control the dynamics of multizone programmable crystal growth furnaces. Due to the inevitable heat exchange among different heating zones and the transient nature of the process, the dynamics of multizone furnaces is time varying, distributed, and therefore complex in nature. Electrical power to heating zones and the translational speed of the ampoule are employed as inputs to control the dynamics. Structural properties of the crystal is the ultimate aim of this adaptive control system. These properties can be monitored in different ways. Following an order of complexity, these may include: (1) on line measurement of the material optical properties such as the refractive index of crystal; (2) on line x-ray imaging of the interface topology; (3) on line optical quantification of the interface profile such as the determination of concavity or convexity of the interface shape; and (4) on line temperature measurement at points closest to the material such as measurements of the ampoule's outside and inside surface temperatures. The research performed makes use of the temperature and optical measurements, specified in (3) and (4) as the outputs of furnace dynamics. However, if the instrumentation is available, the proposed control methodology can be extended to the measurements listed in (1) and (2).

Batur, Celal↗
NASA NTRS2010

Flight Test of an L(sub 1) Adaptive Controller on the NASA AirSTAR Flight Test Vehicle

This paper presents results of a flight test of the L-1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are for piloted tasks performed during the flight test.

Gregory, Irene M.↗
NASA NTRS2011

LaPlace Transform1 Adaptive Control Law in Support of Large Flight Envelope Modeling Work

This paper presents results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented are in support of nonlinear aerodynamic modeling and instrumentation calibration.

Gregory, Irene M.↗
NASA NTRS1992

Discrete-time entropy formulation of optimal and adaptive control problems

The discrete-time version of the entropy formulation of optimal control of problems developed by G. N. Saridis (1988) is discussed. Given a dynamical system, the uncertainty in the selection of the control is characterized by the probability distribution (density) function which maximizes the total entropy. The equivalence between the optimal control problem and the optimal entropy problem is established, and the total entropy is decomposed into a term associated with the certainty equivalent control law, the entropy of estimation, and the so-called equivocation of the active transmission of information from the controller to the estimator. This provides a useful framework for studying the certainty equivalent and adaptive control laws.

Tsai, Yweting A.↗
NASA NTRS1986

Inherent robustness of discrete-time adaptive control systems

Global stability robustness with respect to unmodeled dynamics, arbitrary bounded internal noise, as well as external disturbance is shown to exist for a class of discrete-time adaptive control systems when the regressor vectors of these systems are persistently exciting. Although fast adaptation is definitely undesirable, so far as attaining the greatest amount of global stability robustness is concerned, slow adaptation is shown to be not necessarily beneficial. The entire analysis in this paper holds for systems with slowly varying return difference matrices; the plants in these systems need not be slowly varying.

Ma, C. C. H.↗
NASA NTRS1992

Fault-tolerant adaptive control for load-following in static space nuclear power systems

The possible use of a dual-loop model-based adaptive control system for load following in static space nuclear power systems is investigated. The proposed approach has thus far been applied only to a thermoelectric space nuclear power system but is equally applicable to other static space nuclear power systems such as thermionic systems.

Parlos, Alexander G.↗
NASA NTRS2011

Flight Test of L1 Adaptive Control Law: Offset Landings and Large Flight Envelope Modeling Work

This paper presents new results of a flight test of the L1 adaptive control architecture designed to directly compensate for significant uncertain cross-coupling in nonlinear systems. The flight test was conducted on the subscale turbine powered Generic Transport Model that is an integral part of the Airborne Subscale Transport Aircraft Research system at the NASA Langley Research Center. The results presented include control law evaluation for piloted offset landing tasks as well as results in support of nonlinear aerodynamic modeling and real-time dynamic modeling of the departure-prone edges of the flight envelope.

Gregory, Irene M.↗
NASA NTRS1984

Adaptive control with variable dead-zone nonlinearities

It has been found that fixed error dead-zones as defined in the existing literature result in serious degradation of performance, due to the conservativeness which characterizes the determination of their width. In the present paper, variable width dead-zones are derived for the adaptive control of plants with unmodeled dynamics. The derivation makes use of information available about the unmodeled dynamics both a priori as well as during the adaptation process, so as to stabilize the adaptive loop and at the same time overcome the conservativeness and performance limitations of fixed-dead zone adaptive or fixed gain controllers.

Orlicki, D.↗
NASA NTRS2008

Stability Metrics for Simulation and Flight-Software Assessment and Monitoring of Adaptive Control Assist Compensators

Due to a need for improved reliability and performance in aerospace systems, there is increased interest in the use of adaptive control or other nonlinear, time-varying control designs in aerospace vehicles. While such techniques are built on Lyapunov stability theory, they lack an accompanying set of metrics for the assessment of stability margins such as the classical gain and phase margins used in linear time-invariant systems. Such metrics must both be physically meaningful and permit the user to draw conclusions in a straightforward fashion. We present in this paper a roadmap to the development of metrics appropriate to nonlinear, time-varying systems. We also present two case studies in which frozen-time gain and phase margins incorrectly predict stability or instability. We then present a multi-resolution analysis approach that permits on-line real-time stability assessment of nonlinear systems.

Hodel, A. S.↗
NASA NTRS1979

Identification and dual adaptive control of a turbojet engine

The objective of this paper is to utilize the design methods of modern control theory to realize a 'dual-adaptive' feedback control unit for a highly non-linear single spool airbreathing turbojet engine. Using a very detailed and accurate simulation of the non-linear engine as the data source, linear operating point models of unspecified dimension are identified. Feedback control laws are designed at each operating point for a prespecified set of sampling rates using sampled-data output regulator theory. The control system sampling rate is determined by an adaptive sampling algorithm in correspondence with turbojet engine performance. The result is a 'dual-adpative' control law that is functionally dependent upon the sampling rate selected and environmental operating conditions. Simulation transients demonstrate the utility of the dual-adaptive design to improve on-board computer utilization while maintaining acceptable levels of engine performance.

Merrill, W.↗
NASA NTRS1990

Adaptive-Control Experiments On A Large Flexible Structure

Antennalike flexible structure built for research in advanced technology including suppression of vibrations and control of initial deflections. Structure instrumented with sensors and actuators connected to digital electronic control system, programmed with control algorithms to be tested. Particular attention in this research focused on direct model-reference adaptive-control algorithm based on command generator tracker theory. Built to exhibit multiple vibrational modes, low modal frequencies, and low structural damping. Made three-dimensional so complicated interactions among components of structure and control system investigated.

Ih, Che-Hang C.↗
NASA NTRS1991

Adaptive control of space based robot manipulators

For space based robots in which the base is free to move, motion planning and control is complicated by uncertainties in the inertial properties of the manipulator and its load. A new adaptive control method is presented for space based robots which achieves globally stable trajectory tracking in the presence of uncertainties in the inertial parameters of the system. A partition is made of the fifteen degree of freedom system dynamics into two parts: a nine degree of freedom invertible portion and a six degree of freedom noninvertible portion. The controller is then designed to achieve trajectory tracking of the invertible portion of the system. This portion consist of the manipulator joint positions and the orientation of the base. The motion of the noninvertible portion is bounded, but unpredictable. This portion consist of the position of the robot's base and the position of the reaction wheel.

Walker, Michael W.↗