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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Adaptive control of a Stewart platform-based manipulator

A joint-space adaptive control scheme for controlling noncompliant motion of a Stewart platform-based manipulator (SPBM) was implemented in the Hardware Real-Time Emulator at Goddard Space Flight Center. The six-degrees of freedom SPBM uses two platforms and six linear actuators driven by dc motors. The adaptive control scheme is based on proportional-derivative controllers whose gains are adjusted by an adaptation law based on model reference adaptive control and Liapunov direct method. It is concluded that the adaptive control scheme provides superior tracking capability as compared to fixed-gain controllers.

Nguyen, Charles C.↗
NASA NTRS2019

MRAC with Time-Varying Reference Model from Convex Combination

An extension of model reference adaptive control is presented that accommodates use of a time-varying reference model. Specifically, the reference model is taken to be a time-varying convex combination of two linear, time-invariant models. The design is intended to act as a way to smoothly transition between two different reference models without resorting to a scheduled switch. It also provides the ability to use an interpolated reference model when the plant is operating between design points. The time variation of the combination must satisfy some requirements to ensure stability but is otherwise user choice. Subject to these requirements, bounded tracking error behavior is demonstrated via Lyapunov stability analysis for the single-input, single-output, output feedback case. Tracking error convergence is asymptotic when time variation ceases. The proposed design is demonstrated in simulation of a numerical model.

Hashemi, Kelley E.↗
NASA NTRS1989

CHIMERA II - A real-time multiprocessing environment for sensor-based robot control

A multiprocessing environment for a wide variety of sensor-based robot system, providing the flexibility, performance, and UNIX-compatible interface needed for fast development of real-time code is addressed. The requirements imposed on the design of a programming environment for sensor-based robotic control is outlined. The details of the current hardware configuration are presented, along with the details of the CHIMERA II software. Emphasis is placed on the kernel, low-level interboard communication, user interface, extended file system, user-definable and dynamically selectable real-time schedulers, remote process synchronization, and generalized interprocess communication. A possible implementation of a hierarchical control model, the NASA/NBS standard reference model for telerobot control system is demonstrated.

Stewart, David B.↗
NASA NTRS1990

Experimental study of robustness in adaptive control for large flexible structures

An experimental study is performed to investigate the robustness of model reference adaptive control for the large flexible structures control application. The main nonidealities of concern are unmodeled dynamics, input saturation, and time delay effects (here, actuator and sensor dynamics are lumped into the last item for convenience). This study focuses on the robustness with respect to input saturation and time delay effects, since robustness to unmodeled dynamics is inherent to the basic algorithm and has been demonstrated experimentally elsewhere.

Ih, Che-Hang Charles↗
NASA NTRS1987

Frequency domain synthesis of optimal inputs for adaptive identification and control

The input design problem of selecting appropriate inputs for use in SISO adaptive identification and model reference adaptive control algorithms is considered. Averaging theory is used to characterize the optimal inputs in the frequency domain. The design problem is formulated as an optimization problem which maximizes the smallest eigenvalue of the average information matrix over power constrained signals, and the global optimal solution is obtained using a convergent numerical algorithm. A bound on the frequency search range required in the design algorithm has been determined in terms of the desired performance.

Fu, Li-Chen↗
NASA NTRS1984

Necessary and sufficient conditions for parameter convergence in adaptive control

Consideration is given to the concept of a reference signal which is sufficient to cause the parameter error in an adaptive control system to converge to zero. Simple and necessary conditions for the convergence of the parameter error are established for a model reference adaptive control (MRAC) system having a relative degree of one. The exponential stability of the MRAC under persistent excitation (PE) is also considered. Full proofs of the theoretical arguments are given in a companion paper.

Boyd, S.↗
NASA NTRS2012

On the Robustness Properties of M-MRAC

The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.

Stepanyan, Vahram↗
NASA NTRS1973

The muscle spindle as a feedback element in muscle control

The muscle spindle, the feedback element in the myotatic (stretch) reflex, is a major contributor to muscular control. Therefore, an accurate description of behavior of the muscle spindle during active contraction of the muscle, as well as during passive stretch, is essential to the understanding of muscle control. Animal experiments were performed in order to obtain the data necessary to model the muscle spindle. Spectral density functions were used to identify a linear approximation of the two types of nerve endings from the spindle. A model reference adaptive control system was used on a hybrid computer to optimize the anatomically defined lumped parameter estimate of the spindle. The derived nonlinear model accurately predicts the behavior of the muscle spindle both during active discharge and during its silent period. This model is used to determine the mechanism employed to control muscle movement.

Andrews, L. T.↗
NASA NTRS1995

Genetic Adaptive Control for PZT Actuators

A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

Kim, Jeongwook↗
NASA NTRS2010

Projection Operator: A Step Towards Certification of Adaptive Controllers

One of the major barriers to wider use of adaptive controllers in commercial aviation is the lack of appropriate certification procedures. In order to be certified by the Federal Aviation Administration (FAA), an aircraft controller is expected to meet a set of guidelines on functionality and reliability while not negatively impacting other systems or safety of aircraft operations. Due to their inherent time-variant and non-linear behavior, adaptive controllers cannot be certified via the metrics used for linear conventional controllers, such as gain and phase margin. Projection Operator is a robustness augmentation technique that bounds the output of a non-linear adaptive controller while conforming to the Lyapunov stability rules. It can also be used to limit the control authority of the adaptive component so that the said control authority can be arbitrarily close to that of a linear controller. In this paper we will present the results of applying the Projection Operator to a Model-Reference Adaptive Controller (MRAC), varying the amount of control authority, and comparing controller s performance and stability characteristics with those of a linear controller. We will also show how adjusting Projection Operator parameters can make it easier for the controller to satisfy the certification guidelines by enabling a tradeoff between controller s performance and robustness.

Larchev, Gregory V.↗
NASA NTRS1985

Dynamic modeling and adaptive control for space stations

Of all large space structural systems, space stations present a unique challenge and requirement to advanced control technology. Their operations require control system stability over an extremely broad range of parameter changes and high level of disturbances. During shuttle docking the system mass may suddenly increase by more than 100% and during station assembly the mass may vary even more drastically. These coupled with the inherent dynamic model uncertainties associated with large space structural systems require highly sophisticated control systems that can grow as the stations evolve and cope with the uncertainties and time-varying elements to maintain the stability and pointing of the space stations. The aspects of space station operational properties are first examined, including configurations, dynamic models, shuttle docking contact dynamics, solar panel interaction, and load reduction to yield a set of system models and conditions. A model reference adaptive control algorithm along with the inner-loop plant augmentation design for controlling the space stations under severe operational conditions of shuttle docking, excessive model parameter errors, and model truncation are then investigated. The instability problem caused by the zero-frequency rigid body modes and a proposed solution using plant augmentation are addressed. Two sets of sufficient conditions which guarantee the globablly asymptotic stability for the space station systems are obtained.

Ih, C. H. C.↗
NASA NTRS2005

Reconfigurable Flight Control Design using a Robust Servo LQR and Radial Basis Function Neural Networks

This viewgraph presentation reviews the use of a Robust Servo Linear Quadratic Regulator (LQR) and a Radial Basis Function (RBF) Neural Network in reconfigurable flight control designs in adaptation to a aircraft part failure. The method uses a robust LQR servomechanism design with model Reference adaptive control, and RBF neural networks. During the failure the LQR servomechanism behaved well, and using the neural networks improved the tracking.

Burken, John J.↗
NASA NTRS1986

Design of adaptive control systems by means of self-adjusting transversal filters

The design of closed-loop adaptive control systems based on nonparametric identification was addressed. Implementation is by self-adjusting Least Mean Square (LMS) transversal filters. The design concept is Model Reference Adaptive Control (MRAC). Major issues are to preserve the linearity of the error equations of each LMS filter, and to prevent estimation bias that is due to process or measurement noise, thus providing necessary conditions for the convergence and stability of the control system. The controlled element is assumed to be asymptotically stable and minimum phase. Because of the nonparametric Finite Impulse Response (FIR) estimates provided by the LMS filters, a-priori information on the plant model is needed only in broad terms. Following a survey of control system configurations and filter design considerations, system implementation is shown here in Single Input Single Output (SISO) format which is readily extendable to multivariable forms. In extensive computer simulation studies the controlled element is represented by a second-order system with widely varying damping, natural frequency, and relative degree.

Merhav, S. J.↗
NASA NTRS2009

Pilot Evaluation of Adaptive Control in Motion-Based Flight Simulator

The objective of this work is to assess the strengths, weaknesses, and robustness characteristics of several MRAC (Model-Reference Adaptive Control) based adaptive control technologies garnering interest from the community as a whole. To facilitate this, a control study using piloted and unpiloted simulations to evaluate sensitivities and handling qualities was conducted. The adaptive control technologies under consideration were ALR (Adaptive Loop Recovery), BLS (Bounded Linear Stability), Hybrid Adaptive Control, L1, OCM (Optimal Control Modification), PMRAC (Predictor-based MRAC), and traditional MRAC

Kaneshige, John T.↗
NASA NTRS2016

Adaptive Modal Identification for Flutter Suppression Control

In this paper, we will develop an adaptive modal identification method for identifying the frequencies and damping of a flutter mode based on model-reference adaptive control (MRAC) and least-squares methods. The least-squares parameter estimation will achieve parameter convergence in the presence of persistent excitation whereas the MRAC parameter estimation does not guarantee parameter convergence. Two adaptive flutter suppression control approaches are developed: one based on MRAC and the other based on the least-squares method. The MRAC flutter suppression control is designed as an integral part of the parameter estimation where the feedback signal is used to estimate the modal information. On the other hand, the separation principle of control and estimation is applied to the least-squares method. The least-squares modal identification is used to perform parameter estimation.

Aeroelasticity↗
NASA NTRS2010

Optimal Control Modification Adaptive Law for Time-Scale Separated Systems

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Nguyen, Nhan T.↗
NASA NTRS2009

Optimal Control Modification for Robust Adaptation of Singularly Perturbed Systems with Slow Actuators

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. The model matching conditions in the transformed time coordinate results in increase in the feedback gain and modification of the adaptive law.

Nguyen, Nhan T.↗
NASA NTRS2012

Optimal Control Modification for Time-Scale Separated Systems

Recently a new optimal control modification has been introduced that can achieve robust adaptation with a large adaptive gain without incurring high-frequency oscillations as with the standard model-reference adaptive control. This modification is based on an optimal control formulation to minimize the L2 norm of the tracking error. The optimal control modification adaptive law results in a stable adaptation in the presence of a large adaptive gain. This study examines the optimal control modification adaptive law in the context of a system with a time scale separation resulting from a fast plant with a slow actuator. A singular perturbation analysis is performed to derive a modification to the adaptive law by transforming the original system into a reduced-order system in slow time. A model matching conditions in the transformed time coordinate results in an increase in the actuator command that effectively compensate for the slow actuator dynamics. Simulations demonstrate effectiveness of the method.

Adaptive Control↗