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At least 667 records · Page 37

Adaptive Control of a Transport Aircraft Using Differential Thrust

The paper presents an adaptive control technique for a damaged large transport aircraft subject to unknown atmospheric disturbances such as wind gust or turbulence. It is assumed that the damage results in vertical tail loss with no rudder authority, which is replaced with a differential thrust input. The proposed technique uses the adaptive prediction based control design in conjunction with the time scale separation principle, based on the singular perturbation theory. The application of later is necessitated by the fact that the engine response to a throttle command is substantially slow that the angular rate dynamics of the aircraft. It is shown that this control technique guarantees the stability of the closed-loop system and the tracking of a given reference model. The simulation example shows the benefits of the approach.

Stepanyan, Vahram↗

Accommodating Sensor Bias in MRAC for State Tracking

The problem of accommodating unknown sensor bias is considered in a direct model reference adaptive control (MRAC) setting for state tracking using state feedback. Sensor faults can occur during operation, and if the biased state measurements are directly used with a standard MRAC control law, neither closed-loop signal boundedness, nor asymptotic tracking can be guaranteed and the resulting tracking errors may be unbounded or unacceptably large. A modified MRAC law is proposed, which combines a bias estimator with control gain adaptation, and it is shown that signal boundedness can be accomplished, although the tracking error may not go to zero. Further, for the case wherein an asymptotically stable sensor bias estimator is available, an MRAC control law is proposed to accomplish asymptotic tracking and signal boundedness. Such a sensor bias estimator can be designed if additional sensor measurements are available, as illustrated for the case wherein bias is present in the rate gyro and airspeed measurements. Numerical example results are presented to illustrate each of the schemes.

Patre, Parag↗

Full-Scaled Advanced Systems Testbed: Ensuring Success of Adaptive Control Research Through Project Lifecycle Risk Mitigation

The National Aeronautics and Space Administration's Dryden Flight Research Center completed flight testing of adaptive controls research on the Full-Scale Advance Systems Testbed (FAST) in January of 2011. The research addressed technical challenges involved with reducing risk in an increasingly complex and dynamic national airspace. Specific challenges lie with the development of validated, multidisciplinary, integrated aircraft control design tools and techniques to enable safe flight in the presence of adverse conditions such as structural damage, control surface failures, or aerodynamic upsets. The testbed is an F-18 aircraft serving as a full-scale vehicle to test and validate adaptive flight control research and lends a significant confidence to the development, maturation, and acceptance process of incorporating adaptive control laws into follow-on research and the operational environment. The experimental systems integrated into FAST were designed to allow for flexible yet safe flight test evaluation and validation of modern adaptive control technologies and revolve around two major hardware upgrades: the modification of Production Support Flight Control Computers (PSFCC) and integration of two, fourth-generation Airborne Research Test Systems (ARTS). Post-hardware integration verification and validation provided the foundation for safe flight test of Nonlinear Dynamic Inversion and Model Reference Aircraft Control adaptive control law experiments. To ensure success of flight in terms of cost, schedule, and test results, emphasis on risk management was incorporated into early stages of design and flight test planning and continued through the execution of each flight test mission. Specific consideration was made to incorporate safety features within the hardware and software to alleviate user demands as well as into test processes and training to reduce human factor impacts to safe and successful flight test. This paper describes the research configuration, experiment functionality, overall risk mitigation, flight test approach and results, and lessons learned of adaptive controls research of the Full-Scale Advanced Systems Testbed.

Pavlock, Kate M.↗

Input and Output Performance of M-MRAC in the Presence of Bounded Disturbances

This paper presents performance analysis of novel modified model reference adaptive control (M-MRAC) architecture in conjunction with different robust adaptive laws for the uncertain linear systems subject to unknown but bounded disturbances. It is shown that for any robust adaptive law the tracking error of the M-MRAC system can be arbitrarily decreased in transient and in the steady-state by increasing the adaptation rate, without generating high frequency oscillations in the control signal, which are unavoidable in conventional MRAC systems for large adaptation rates. Moreover, the generated adaptive control signal arbitrary closely tracks the ideal control signal when the error feedback gain is simultaneously increased with the adaptation rate, according to derived rule. The results are demonstrated via simulations.

Stepanyan, Vahram↗

Nonlinear Dynamic Inversion Baseline Control Law: Flight-Test Results for the Full-scale Advanced Systems Testbed F/A-18 Airplane

A model reference nonlinear dynamic inversion control law has been developed to provide a baseline controller for research into simple adaptive elements for advanced flight control laws. This controller has been implemented and tested in a hardware-in-the-loop simulation and in flight. The flight results agree well with the simulation predictions and show good handling qualities throughout the tested flight envelope with some noteworthy deficiencies highlighted both by handling qualities metrics and pilot comments. Many design choices and implementation details reflect the requirements placed on the system by the nonlinear flight environment and the desire to keep the system as simple as possible to easily allow the addition of the adaptive elements. The flight-test results and how they compare to the simulation predictions are discussed, along with a discussion about how each element affected pilot opinions. Additionally, aspects of the design that performed better than expected are presented, as well as some simple improvements that will be suggested for follow-on work.

Miller, Christopher J.↗

Adaptive Control Using Residual Mode Filters Applied to Wind Turbines

Many dynamic systems containing a large number of modes can benefit from adaptive control techniques, which are well suited to applications that have unknown parameters and poorly known operating conditions. In this paper, we focus on a model reference direct adaptive control approach that has been extended to handle adaptive rejection of persistent disturbances. We extend this adaptive control theory to accommodate problematic modal subsystems of a plant that inhibit the adaptive controller by causing the open-loop plant to be non-minimum phase. We will augment the adaptive controller using a Residual Mode Filter (RMF) to compensate for problematic modal subsystems, thereby allowing the system to satisfy the requirements for the adaptive controller to have guaranteed convergence and bounded gains. We apply these theoretical results to design an adaptive collective pitch controller for a high-fidelity simulation of a utility-scale, variable-speed wind turbine that has minimum phase zeros.

Frost, Susan A.↗

On Time Delay Margin Estimation for Adaptive Control and Optimal Control Modification

This paper presents methods for estimating time delay margin for adaptive control of input delay systems with almost linear structured uncertainty. The bounded linear stability analysis method seeks to represent an adaptive law by a locally bounded linear approximation within a small time window. The time delay margin of this input delay system represents a local stability measure and is computed analytically by three methods: Pade approximation, Lyapunov-Krasovskii method, and the matrix measure method. These methods are applied to the standard model-reference adaptive control, s-modification adaptive law, and optimal control modification adaptive law. The windowing analysis results in non-unique estimates of the time delay margin since it is dependent on the length of a time window and parameters which vary from one time window to the next. The optimal control modification adaptive law overcomes this limitation in that, as the adaptive gain tends to infinity and if the matched uncertainty is linear, then the closed-loop input delay system tends to a LTI system. A lower bound of the time delay margin of this system can then be estimated uniquely without the need for the windowing analysis. Simulation results demonstrates the feasibility of the bounded linear stability method for time delay margin estimation.

Nguyen, Nhan T.↗

Data Service Provider Cost Estimation Tool

The Data Service Provider Cost Estimation Tool (CET) and Comparables Database (CDB) package provides to NASA s Earth Science Enterprise (ESE) the ability to estimate the full range of year-by-year lifecycle cost estimates for the implementation and operation of data service providers required by ESE to support its science and applications programs. The CET can make estimates dealing with staffing costs, supplies, facility costs, network services, hardware and maintenance, commercial off-the-shelf (COTS) software licenses, software development and sustaining engineering, and the changes in costs that result from changes in workload. Data Service Providers may be stand-alone or embedded in flight projects, field campaigns, research or applications projects, or other activities. The CET and CDB package employs a cost-estimation-by-analogy approach. It is based on a new, general data service provider reference model that provides a framework for construction of a database by describing existing data service providers that are analogs (or comparables) to planned, new ESE data service providers. The CET implements the staff effort and cost estimation algorithms that access the CDB and generates the lifecycle cost estimate for a new data services provider. This data creates a common basis for an ESE proposal evaluator for considering projected data service provider costs.

Fontaine, Kathy↗

Vehicle Integrated Prognostic Reasoner (VIPR) Metric Report

This document outlines a set of metrics for evaluating the diagnostic and prognostic schemes developed for the Vehicle Integrated Prognostic Reasoner (VIPR), a system-level reasoner that encompasses the multiple levels of large, complex systems such as those for aircraft and spacecraft. VIPR health managers are organized hierarchically and operate together to derive diagnostic and prognostic inferences from symptoms and conditions reported by a set of diagnostic and prognostic monitors. For layered reasoners such as VIPR, the overall performance cannot be evaluated by metrics solely directed toward timely detection and accuracy of estimation of the faults in individual components. Among other factors, overall vehicle reasoner performance is governed by the effectiveness of the communication schemes between monitors and reasoners in the architecture, and the ability to propagate and fuse relevant information to make accurate, consistent, and timely predictions at different levels of the reasoner hierarchy. We outline an extended set of diagnostic and prognostics metrics that can be broadly categorized as evaluation measures for diagnostic coverage, prognostic coverage, accuracy of inferences, latency in making inferences, computational cost, and sensitivity to different fault and degradation conditions. We report metrics from Monte Carlo experiments using two variations of an aircraft reference model that supported both flat and hierarchical reasoning.

Cornhill, Dennis↗

Complexity and Pilot Workload Metrics for the Evaluation of Adaptive Flight Controls on a Full Scale Piloted Aircraft

Flight research has shown the effectiveness of adaptive flight controls for improving aircraft safety and performance in the presence of uncertainties. The National Aeronautics and Space Administration's (NASA)'s Integrated Resilient Aircraft Control (IRAC) project designed and conducted a series of flight experiments to study the impact of variations in adaptive controller design complexity on performance and handling qualities. A novel complexity metric was devised to compare the degrees of simplicity achieved in three variations of a model reference adaptive controller (MRAC) for NASA's F-18 (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) Full-Scale Advanced Systems Testbed (Gen-2A) aircraft. The complexity measures of these controllers are also compared to that of an earlier MRAC design for NASA's Intelligent Flight Control System (IFCS) project and flown on a highly modified F-15 aircraft (McDonnell Douglas, now The Boeing Company, Chicago, Illinois). Pilot comments during the IRAC research flights pointed to the importance of workload on handling qualities ratings for failure and damage scenarios. Modifications to existing pilot aggressiveness and duty cycle metrics are presented and applied to the IRAC controllers. Finally, while adaptive controllers may alleviate the effects of failures or damage on an aircraft's handling qualities, they also have the potential to introduce annoying changes to the flight dynamics or to the operation of aircraft systems. A nuisance rating scale is presented for the categorization of nuisance side-effects of adaptive controllers.

pilot workload metrics↗

Airborne Simulation of Launch Vehicle Dynamics

In this paper we present a technique for approximating the short-period dynamics of an exploration-class launch vehicle during flight test with a high-performance surrogate aircraft in relatively benign endoatmospheric flight conditions. The surrogate vehicle relies upon a nonlinear dynamic inversion scheme with proportional-integral feedback to drive a subset of the aircraft states into coincidence with the states of a time-varying reference model that simulates the unstable rigid body dynamics, servodynamics, and parasitic elastic and sloshing dynamics of the launch vehicle. The surrogate aircraft flies a constant pitch rate trajectory to approximate the boost phase gravity-turn ascent, and the aircraft's closed-loop bandwidth is sufficient to simulate the launch vehicle's fundamental lateral bending and sloshing modes by exciting the rigid body dynamics of the aircraft. A novel control allocation scheme is employed to utilize the aircraft's relatively fast control effectors in inducing various failure modes for the purposes of evaluating control system performance. Sufficient dynamic similarity is achieved such that the control system under evaluation is optimized for the full-scale vehicle with no changes to its parameters, and pilot-control system interaction studies can be performed to characterize the effects of guidance takeover during boost. High-fidelity simulation and flight test results are presented that demonstrate the efficacy of the design in simulating the Space Launch System (SLS) launch vehicle dynamics using NASA Dryden Flight Research Center's Full-scale Advanced Systems Testbed (FAST), a modified F/A-18 airplane, over a range of scenarios designed to stress the SLS's adaptive augmenting control (AAC) algorithm.

Gilligan, Eric T.↗

Space Launch System Ascent Flight Control Design

A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. As the SLS configurations represent a potentially significant increase in complexity and performance capability of the integrated flight vehicle, it was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight load relief through the use of a nonlinear observer driven by acceleration measurements, and envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.

VanZwieten, Tannen S.↗

Space Launch System Ascent Flight Control Design

A robust and flexible autopilot architecture for NASA's Space Launch System (SLS) family of launch vehicles is presented. The SLS configurations represent a potentially significant increase in complexity and performance capability when compared with other manned launch vehicles. It was recognized early in the program that a new, generalized autopilot design should be formulated to fulfill the needs of this new space launch architecture. The present design concept is intended to leverage existing NASA and industry launch vehicle design experience and maintain the extensibility and modularity necessary to accommodate multiple vehicle configurations while relying on proven and flight-tested control design principles for large boost vehicles. The SLS flight control architecture combines a digital three-axis autopilot with traditional bending filters to support robust active or passive stabilization of the vehicle's bending and sloshing dynamics using optimally blended measurements from multiple rate gyros on the vehicle structure. The algorithm also relies on a pseudo-optimal control allocation scheme to maximize the performance capability of multiple vectored engines while accommodating throttling and engine failure contingencies in real time with negligible impact to stability characteristics. The architecture supports active in-flight disturbance compensation through the use of nonlinear observers driven by acceleration measurements. Envelope expansion and robustness enhancement is obtained through the use of a multiplicative forward gain modulation law based upon a simple model reference adaptive control scheme.

Orr, Jeb S.↗

Adaptive Control for Linear Uncertain Systems with Unmodeled Dynamics Revisited via Optimal Control Modification

This paper presents the optimal control modification for linear uncertain plants. The Lyapunov analysis shows that the modification parameter has a limiting value depending on the nature of the uncertainty. The optimal control modification exhibits a linear asymptotic property that enables it to be analyzed in a linear time invariant framework for linear uncertain plants. The linear asymptotic property shows that the closed-loop plants in the limit possess a scaled input-output mapping. Using this property, we can derive an analytical closed-loop transfer function in the limit as the adaptive gain tends to infinity. The paper revisits the Rohrs counterexample problem that illustrates the nature of non-robustness of model-reference adaptive control in the presence of unmodeled dynamics. An analytical approach is developed to compute exactly the modification parameter for the optimal control modification that stabilizes the plant in the Rohrs counterexample. The linear asymptotic property is also used to address output feedback adaptive control for non-minimum phase plants with a relative degree 1.

Unmodeled Dynamics↗

In-Flight Suppression of an Unstable F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off-nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using post-flight frequency-domain reconstruction, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

VanZwieten, Tannen S.↗

In-Flight Suppression of a Destabilized F/A-18 Structural Mode Using the Space Launch System Adaptive Augmenting Control System

NASA's Space Launch System (SLS) Flight Control System (FCS) includes an Adaptive Augmenting Control (AAC) component which employs a multiplicative gain update law to enhance the performance and robustness of the baseline control system for extreme off nominal scenarios. The SLS FCS algorithm including AAC has been flight tested utilizing a specially outfitted F/A-18 fighter jet in which the pitch axis control of the aircraft was performed by a Non-linear Dynamic Inversion (NDI) controller, SLS reference models, and the SLS flight software prototype. This paper describes test cases from the research flight campaign in which the fundamental F/A-18 airframe structural mode was identified using frequency-domain reconstruction of flight data, amplified to result in closed loop instability, and suppressed in-flight by the SLS adaptive control system.

Wall, John H.↗

Airborne Simulation of Launch Vehicle Dynamics

In this paper we present a technique for approximating the short-period dynamics of an exploration-class launch vehicle during flight test with a high-performance surrogate aircraft in relatively benign endoatmospheric flight conditions. The surrogate vehicle relies upon a nonlinear dynamic inversion scheme with proportional-integral feedback to drive a subset of the aircraft states into coincidence with the states of a time-varying reference model that simulates the unstable rigid body dynamics, servodynamics, and parasitic elastic and sloshing dynamics of the launch vehicle. The surrogate aircraft flies a constant pitch rate trajectory to approximate the boost phase gravity turn ascent, and the aircraft's closed-loop bandwidth is sufficient to simulate the launch vehicle's fundamental lateral bending and sloshing modes by exciting the rigid body dynamics of the aircraft. A novel control allocation scheme is employed to utilize the aircraft's relatively fast control effectors in inducing various failure modes for the purposes of evaluating control system performance. Sufficient dynamic similarity is achieved such that the control system under evaluation is configured for the full-scale vehicle with no changes to its parameters, and pilot-control system interaction studies can be performed to characterize the effects of guidance takeover during boost. High-fidelity simulation and flight-test results are presented that demonstrate the efficacy of the design in simulating the Space Launch System (SLS) launch vehicle dynamics using the National Aeronautics and Space Administration (NASA) Armstrong Flight Research Center Fullscale Advanced Systems Testbed (FAST), a modified F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois), over a range of scenarios designed to stress the SLS's Adaptive Augmenting Control (AAC) algorithm.

airborne simulation↗

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↗