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All sourcesNASA NTRSDOE OSTI
NASA NTRS1987

Robust time and frequency domain estimation methods in adaptive control

A robust identification method was developed for use in an adaptive control system. The type of estimator is called the robust estimator, since it is robust to the effects of both unmodeled dynamics and an unmeasurable disturbance. The development of the robust estimator was motivated by a need to provide guarantees in the identification part of an adaptive controller. To enable the design of a robust control system, a nominal model as well as a frequency-domain bounding function on the modeling uncertainty associated with this nominal model must be provided. Two estimation methods are presented for finding parameter estimates, and, hence, a nominal model. One of these methods is based on the well developed field of time-domain parameter estimation. In a second method of finding parameter estimates, a type of weighted least-squares fitting to a frequency-domain estimated model is used. The frequency-domain estimator is shown to perform better, in general, than the time-domain parameter estimator. In addition, a methodology for finding a frequency-domain bounding function on the disturbance is used to compute a frequency-domain bounding function on the additive modeling error due to the effects of the disturbance and the use of finite-length data. The performance of the robust estimator in both open-loop and closed-loop situations is examined through the use of simulations.

Lamaire, Richard Orville↗
NASA NTRS1990

Application of stochastic robustness to aircraft control systems

Guaranteeing robustness has long been an important design objective of control system analysis. Stochastic robustness is a simple numerical procedure that can be used to measure and gain insight into robustness properties associated with linear control systems. In the realm of aircraft control systems, problems such as the effects of flight condition perturbations and model-order uncertainties on robustness are easily and effectively analyzed using stochastic robustness. The concept of stochastic robustness is reviewed and examples are presented demonstrating its use in flight control system analysis.

Ryan, Laura E.↗
NASA NTRS1993

Robust on-off pulse control of flexible space vehicles

The on-off reaction jet control system is often used for attitude and orbital maneuvering of various spacecraft. Future space vehicles such as the orbital transfer vehicles, orbital maneuvering vehicles, and space station will extensively use reaction jets for orbital maneuvering and attitude stabilization. The proposed robust fuel- and time-optimal control algorithm is used for a three-mass spacing model of flexible spacecraft. A fuel-efficient on-off control logic is developed for robust rest-to-rest maneuver of a flexible vehicle with minimum excitation of structural modes. The first part of this report is concerned with the problem of selecting a proper pair of jets for practical trade-offs among the maneuvering time, fuel consumption, structural mode excitation, and performance robustness. A time-optimal control problem subject to parameter robustness constraints is formulated and solved. The second part of this report deals with obtaining parameter insensitive fuel- and time- optimal control inputs by solving a constrained optimization problem subject to robustness constraints. It is shown that sensitivity to modeling errors can be significantly reduced by the proposed, robustified open-loop control approach. The final part of this report deals with sliding mode control design for uncertain flexible structures. The benchmark problem of a flexible structure is used as an example for the feedback sliding mode controller design with bounded control inputs and robustness to parameter variations is investigated.

Wie, Bong↗
NASA NTRS1993

Robust tracking control of a magnetically suspended rigid body

This study is an application of H-infinity and microsynthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system, using multivariable robust control approach.

Lim, Kyong B.↗
NASA NTRS1994

Robust tracking control of a magnetically suspended rigid body

This study is an application of H-infinity and micro-synthesis for designing robust tracking controllers for the Large Angle Magnetic Suspension Test Facility. The modeling, design, analysis, simulation, and testing of a control law that guarantees tracking performance under external disturbances and model uncertainties is investigated. The type of uncertainties considered and the tracking performance metric used is discussed. This study demonstrates the tradeoff between tracking performance at low frequencies and robustness at high frequencies. Two sets of controllers were designed and tested. The first set emphasized performance over robustness, while the second set traded off performance for robustness. Comparisons of simulation and test results are also included. Current simulation and experimental results indicate that reasonably good robust tracking performance can be attained for this system using multivariable robust control approach.

Lim, Kyong B.↗
NASA NTRS1997

Hierarchical Modeling and Robust Synthesis for the Preliminary Design of Large Scale Complex Systems

Large-scale complex systems are characterized by multiple interacting subsystems and the analysis of multiple disciplines. The design and development of such systems inevitably requires the resolution of multiple conflicting objectives. The size of complex systems, however, prohibits the development of comprehensive system models, and thus these systems must be partitioned into their constituent parts. Because simultaneous solution of individual subsystem models is often not manageable iteration is inevitable and often excessive. In this dissertation these issues are addressed through the development of a method for hierarchical robust preliminary design exploration to facilitate concurrent system and subsystem design exploration, for the concurrent generation of robust system and subsystem specifications for the preliminary design of multi-level, multi-objective, large-scale complex systems. This method is developed through the integration and expansion of current design techniques: Hierarchical partitioning and modeling techniques for partitioning large-scale complex systems into more tractable parts, and allowing integration of subproblems for system synthesis; Statistical experimentation and approximation techniques for increasing both the efficiency and the comprehensiveness of preliminary design exploration; and Noise modeling techniques for implementing robust preliminary design when approximate models are employed. Hierarchical partitioning and modeling techniques including intermediate responses, linking variables, and compatibility constraints are incorporated within a hierarchical compromise decision support problem formulation for synthesizing subproblem solutions for a partitioned system. Experimentation and approximation techniques are employed for concurrent investigations and modeling of partitioned subproblems. A modified composite experiment is introduced for fitting better predictive models across the ranges of the factors, and an approach for constructing partitioned response surfaces is developed to reduce the computational expense of experimentation for fitting models in a large number of factors. Noise modeling techniques are compared and recommendations are offered for the implementation of robust design when approximate models are sought. These techniques, approaches, and recommendations are incorporated within the method developed for hierarchical robust preliminary design exploration. This method as well as the associated approaches are illustrated through their application to the preliminary design of a commercial turbofan turbine propulsion system. The case study is developed in collaboration with Allison Engine Company, Rolls Royce Aerospace, and is based on the Allison AE3007 existing engine designed for midsize commercial, regional business jets. For this case study, the turbofan system-level problem is partitioned into engine cycle design and configuration design and a compressor modules integrated for more detailed subsystem-level design exploration, improving system evaluation. The fan and low pressure turbine subsystems are also modeled, but in less detail. Given the defined partitioning, these subproblems are investigated independently and concurrently, and response surface models are constructed to approximate the responses of each. These response models are then incorporated within a commercial turbofan hierarchical compromise decision support problem formulation. Five design scenarios are investigated, and robust solutions are identified. The method and solutions identified are verified by comparison with the AE3007 engine. The solutions obtained are similar to the AE3007 cycle and configuration, but are better with respect to many of the requirements.

Koch, Patrick N.↗
NASA NTRS2000

Synthesis Methods for Robust Passification and Control

The research effort under this cooperative agreement has been essentially the continuation of the work from previous grants. The ongoing work has primarily focused on developing passivity-based control techniques for Linear Time-Invariant (LTI) systems. During this period, there has been a significant progress made in the area of passivity-based control of LTI systems and some preliminary results have also been obtained for nonlinear systems, as well. The prior work has addressed optimal control design for inherently passive as well as non- passive linear systems. For exploiting the robustness characteristics of passivity-based controllers the passification methodology was developed for LTI systems that are not inherently passive. Various methods of passification were first proposed in and further developed. The robustness of passification was addressed for multi-input multi-output (MIMO) systems for certain classes of uncertainties using frequency-domain methods. For MIMO systems, a state-space approach using Linear Matrix Inequality (LMI)-based formulation was presented, for passification of non-passive LTI systems. An LMI-based robust passification technique was presented for systems with redundant actuators and sensors. The redundancy in actuators and sensors was used effectively for robust passification using the LMI formulation. The passification was designed to be robust to an interval-type uncertainties in system parameters. The passification techniques were used to design a robust controller for Benchmark Active Control Technology wing under parametric uncertainties. The results on passive nonlinear systems, however, are very limited to date. Our recent work in this area was presented, wherein some stability results were obtained for passive nonlinear systems that are affine in control.

Kelkar, Atul G.↗
NASA NTRS1993

Experimental Robust Control Studies on an Unstable Magnetic Suspension System

This study is an experimental investigation of the robustness of various controllers designed for the Large Angle Magnetic Suspension Test Fixture (LAMSTF). Both analytical and identified nominal models are used for designing controllers along with two different types of uncertainty models. Robustness refers to maintain- ing tracking performance under analytical model errors and dynamically induced eddy currents, while external disturbances are not considered. Results show that incorporating robustness into analytical models gives significantly better results. However, incorporating incorrect uncertainty models may lead to poorer performance than not designing for robustness at all. Designing controllers based on accurate identified models gave the best performance. In fact, incorporating a significant level of robustness into an accurate nominal model resulted in reduced performance. This paper discusses an assortment of experimental results in a consistent manner using robust control theory.

Lim, Kyong B.↗
NASA NTRS2013

Tuning and Robustness Analysis for the Orion Absolute Navigation System

The Orion Multi-Purpose Crew Vehicle (MPCV) is currently under development as NASA's next-generation spacecraft for exploration missions beyond Low Earth Orbit. The MPCV is set to perform an orbital test flight, termed Exploration Flight Test 1 (EFT-1), some time in late 2014. The navigation system for the Orion spacecraft is being designed in a Multi-Organizational Design Environment (MODE) team including contractor and NASA personnel. The system uses an Extended Kalman Filter to process measurements and determine the state. The design of the navigation system has undergone several iterations and modifications since its inception, and continues as a work-in-progress. This paper seeks to show the efforts made to-date in tuning the filter for the EFT-1 mission and instilling appropriate robustness into the system to meet the requirements of manned space ight. Filter performance is affected by many factors: data rates, sensor measurement errors, tuning, and others. This paper focuses mainly on the error characterization and tuning portion. Traditional efforts at tuning a navigation filter have centered around the observation/measurement noise and Gaussian process noise of the Extended Kalman Filter. While the Orion MODE team must certainly address those factors, the team is also looking at residual edit thresholds and measurement underweighting as tuning tools. Tuning analysis is presented with open loop Monte-Carlo simulation results showing statistical errors bounded by the 3-sigma filter uncertainty covariance. The Orion filter design uses 24 Exponentially Correlated Random Variable (ECRV) parameters to estimate the accel/gyro misalignment and nonorthogonality. By design, the time constant and noise terms of these ECRV parameters were set to manufacturer specifications and not used as tuning parameters. They are included in the filter as a more analytically correct method of modeling uncertainties than ad-hoc tuning of the process noise. Tuning is explored for the powered-flight ascent phase, where measurements are scarce and unmodelled vehicle accelerations dominate. On orbit, there are important trade-off cases between process and measurement noise. On entry, there are considerations about trading performance accuracy for robustness. Process Noise is divided into powered flight and coasting ight and can be adjusted for each phase and mode of the Orion EFT-1 mission. Measurement noise is used for the integrated velocity measurements during pad alignment. It is also used for Global Positioning System (GPS) pseudorange and delta- range measurements during the rest of the flight. The robustness effort has been focused on maintaining filter convergence and performance in the presence of unmodeled error sources. These include unmodeled forces on the vehicle and uncorrected errors on the sensor measurements. Orion uses a single-frequency, non-keyed GPS receiver, so the effects due to signal distortion in Earth's ionosphere and troposphere are present in the raw measurements. Results are presented showing the efforts to compensate for these errors as well as characterize the residual effect for measurement noise tuning. Another robustness tool in use is tuning the residual edit thresholds. The trade-off between noise tuning and edit thresholds is explored in the context of robustness to errors in dynamics models and sensor measurements. Measurement underweighting is also presented as a method of additional robustness when processing highly accurate measurements in the presence of large filter uncertainties.

Holt, Greg N.↗
NASA NTRSDate not supplied

Going Beyond Reliability to Robustness and Resilience in Space Life Support Systems

The words reliability, robustness, and resilience are often used interchangeably to describe tough and dependable systems but the distinctions between them suggest how to design more serviceable space systems. Reliability is simply the quality of consistently performing well. A system that dependably meets its design requirements in the specified environment is reliable. The designers may not consider themselves responsible for failures under unanticipated conditions. Robustness is the capability of performing without failure under a wide range of conditions, which can go beyond the expected range to include possible off-nominal conditions. Resilience is the ability to recover from or adapt to unanticipated damaging events, such as failures, accidents, external disruptions, and repurposing. Such changes can invalidate the usual operating assumptions and cause system failure. Reliability, robustness, and resilience describe dependable performance under increasingly difficult conditions, first the specified environment, then a wider possible environment, and finally unanticipated damaging conditions. These three qualities are increasingly desirable and increasingly difficult to achieve. Engineering for resilience would design systems that can ignore or repair failures, survive accidents, and recover from unanticipated disruptions. Increasing the resilience of space systems would greatly increase space crew safety. Improving reliability and robustness requires dealing with known problems, but improving resilience requires implementing a general approach to reducing the impact of unknown future events. The need for robustness and resilience has been stated for decades but little has been done. Systems designers often assume that they understand everything they need to know. The potential failures caused by changes, failures, accidents, unknown environments, and unknown unknowns can be ignored. Such overconfidence can lead to neglect of reliability, robustness, and resilience.

Harry W. Jones↗
NASA NTRSDate not supplied

Going Beyond Reliability to Robustness and Resilience in Space Life Support Systems

The words reliability, robustness, and resilience are often used interchangeably to describe tough and dependable systems but the distinctions between them suggest how to design more serviceable space systems. Reliability is simply the quality of consistently performing well. A system that dependably meets its design requirements in the specified environment is reliable. The designers may not consider themselves responsible for failures under unanticipated conditions. Robustness is the capability of performing without failure under a wide range of conditions, which can go beyond the expected range to include possible off-nominal conditions. Resilience is the ability to recover from or adapt to unanticipated damaging events, such as failures, accidents, external disruptions, and repurposing. Such changes can invalidate the usual operating assumptions and cause system failure. Reliability, robustness, and resilience describe dependable performance under increasingly difficult conditions, first the specified environment, then a wider possible environment, and finally unanticipated damaging conditions. These three qualities are increasingly desirable and increasingly difficult to achieve. Engineering for resilience would design systems that can ignore or repair failures, survive accidents, and recover from unanticipated disruptions. Increasing the resilience of space systems would greatly increase space crew safety. Improving reliability and robustness requires dealing with known problems, but improving resilience requires implementing a general approach to reducing the impact of unknown future events. The need for robustness and resilience has been stated for decades but little has been done. Systems designers often assume that they understand everything they need to know. The potential failures caused by changes, failures, accidents, unknown environments, and unknown unknowns can be ignored. Such overconfidence can lead to neglect of reliability, robustness, and resilience.

Harry W. Jones↗
NASA NTRSDate not supplied

Robust and Mass Efficient Thermal Protection Systems for Future Venus Missions

Several international Venus missions, both orbiter, and in-situ probe are in the works after a prolonged absence. Future missions are expected to be long-duration lander missions and balloon missions to investigate the cloud layer. The entry mass for these in-situ missions will be significantly higher, and the aeroshell will be larger, than previous missions. Two cardinal requirements govern the selection and use of thermal protection systems (TPS), namely, robustness to assure mission safety during entry and mass efficiency so that the useful mass for science is maximized. One cannot trade mission safety for mass when it comes to TPS. The robustness of the TPS is a paramount requirement as it is a single point of system failure. At the same time, TPS mass is carried for the entire mission duration prior to entry, and any excess TPS mass is at the cost of science payload. Future missions will benefit enormously from TPS options with mass and performance benefits far beyond advanced carbon-carbon (ACC) that is currently proposed for the DAVINCI mission. NASA STMD, and SMD jointly invested in the development of 3-D woven thermal protection systems in the last decade, and as a result, the Heat-shield for Extreme Entry Environment Technology (HEEET) TPS has been matured to TRL 6. It is ready for future mission use including Venus. The HEEET project focused on developing a broad technology base, applicable for missions not only to Venus, but also to Saturn, the Ice Giants, and higher speed sample return missions such as Mars Sample Return requiring extreme robustness due to bio-hazards. The dual-layer HEEET (DL-HEEET) is proven to be extremely robust. DL-HEEET performed well in arc jet and laser testing conditions where heritage carbon-phenolic failed. HEEET also proved to be more mass efficient compared to Carbon-Phenolic. Recently, the principal author was invited to present his perspectives to the 2023-2032 Planetary Sciences Decadal Venus subcommittee on the current state of TPS for future Venus missions [1]. In addition to pointing out successful TPS and other developments in the last decade in support of entry systems, the principal author made two findings: 1) importance of and need to sustain TPS capabilities that took nearly a decade to develop and 2) the opportunity to further optimize TPS mass without sacrificing robustness to further enable future in-situ missions. This talk will focus on the above two recommendations and provide the rationale for them. The intent of the talk is to seek advocacy from the VEXAG community for the criticality of TPS sustainment and the benefits of 3D woven TPS optimization. TPS Capability Sustainment: HEEET development was necessitated by the atrophy of heritage carbon-phenolic. Atrophy has impacted other TPS materials as well. Avcoat, the TPS that successfully allowed astronauts to explore the Moon in the 1960s and 70s, took nearly a decade and $10’sM to recover in support of Orion/Artemis. One of the most used TPS materials, SLA 561V, had to be recovered prior to its use on Mars Pathfinder. Phenolic Impregnated Carbon Ablator (PICA), the TPS that replaced SLA 561V on MSL, has undergone multiple replacements and recovery due to constituent rayon changes. Recently, NASA invested in a domestic rayon replacement program and also invested in FMI to consolidate PICA capability for NASA missions, as a result of FMI’s decision to discontinue commercial FiberForm, which is needed for PICA. TPS used for planetary missions are unique and have no other commercial or defense use. In addition, low mission cadence is also a driver for TPS atrophy. Hence, NASA, as the steward, must take steps to ensure and sustain TPS capabilities. In this talk, we outline steps NASA can take to keep abreast of emerging risks and target risk mitigation steps to ensure TPS capability sustainment for Venus and other extreme environment missions. Next Generation of Mass efficient and Robust TPS: NASA invested in an alternate TPS to PICA based on felt-technology called Conformal-PICA which has the potential to save 30% - 50% mass over PICA. The development was discontinued at a Technology Readiness Level (TRL) of ~ 5. 3D Mid-Density Carbon Phenolic (3MDCP) is a single layer variant of HEEET, based on the insulating layer only (SL-HEEET) and currently baselined for the Mars Sample Return Mission Earth Entry System due to its mass efficiency (30% more mass efficient than DL- HEEET). Currently, SL-HEEET is limited to aeroshell diameters of < 1.3m. The SL-HEEET was compared to DL-HEEET in the recent ADVENT flag-ship class mission study in support of the Planetary Science Decadal. SL HEEET was the recommended TPS based on 30% mass savings for both the balloon and lander missions. Given C-PICA and SL-HEEET have superior reliability and mass efficiency, advocacy from VEXAG is sought for completing their further development to TRL 5/6 in this decade so as to enable TPS readiness for future missions.

Thermal Protection Systems↗
NASA NTRS1986

Optimally robust redundancy relations for failure detection in uncertain systems

All failure detection methods are based, either explicitly or implicitly, on the use of redundancy, i.e. on (possibly dynamic) relations among the measured variables. The robustness of the failure detection process consequently depends to a great degree on the reliability of the redundancy relations, which in turn is affected by the inevitable presence of model uncertainties. In this paper the problem of determining redundancy relations that are optimally robust is addressed in a sense that includes several major issues of importance in practical failure detection and that provides a significant amount of intuition concerning the geometry of robust failure detection. A procedure is given involving the construction of a single matrix and its singular value decomposition for the determination of a complete sequence of redundancy relations, ordered in terms of their level of robustness. This procedure also provides the basis for comparing levels of robustness in redundancy provided by different sets of sensors.

Lou, X.-C.↗
NASA NTRS1988

A methodology for the synthesis of robust feedback systems

A new methodology is developed for the synthesis of linear, time-variant (LTI) controllers for multivariable LTI systems. The resulting closed-loop system is nominally stable and exhibits a known level of performance. In addition, robustness of the feedback system is guaranteed, i.e., stability and performance are retained in the presence of multiple unstructured uncertainty blocks located at various points in the feedback loop. The design technique is referred to as the Causality Recovery Methodology (CRM). The CRM relies on the Youla parameterization of all stabilizing compensators to ensure nominal stability of the feedback system. A frequency-domain inequality in terms of the structured singular value mu defines the robustness specification. The optimal compensator, with respect to the mu condition, is shown to be noncausal in general. The aim of the CRM is to find a stable, causal transfer function matrix that approximates the robustness characteristics of the optimal solution. The CRM, via a series of infinite-dimensional convex programs, produces a closed-loop system whose performance robustness is at least as good as that of any initial design. The algorithm is approximated by a finite dimensional process for the purposes of implementation. Two numerical examples confirm the potential viability of the CRM concept; however, the robustness improvement comes at the expense of increased computational burden and compensator complexity.

Milich, David Albert↗
NASA NTRS1988

Robustness margin calculation with dynamic and real parametric uncertainty

The problem of robust stability in feedback control systems with real uncertain parameters and unmodeled dynamics, where the latter takes the form of one complex block dynamic uncertainty, is considered. A robustness margin Tm is defined with respect to such model uncertainty structure and robust stability is characterized in terms of it. An algorithm to calculate Tm and the closely related multivariable stability margin km and structured singular value mu measures of robust stability is developed. It is shown that other control problems, such as robust performance for real parametric uncertainty, can also be handled in this framework.

Sideris, Athanasios↗
NASA NTRS1989

Modern CACSD using the Robust-Control Toolbox

The Robust-Control Toolbox is a collection of 40 M-files which extend the capability of PC/PRO-MATLAB to do modern multivariable robust control system design. Included are robust analysis tools like singular values and structured singular values, robust synthesis tools like continuous/discrete H(exp 2)/H infinity synthesis and Linear Quadratic Gaussian Loop Transfer Recovery methods and a variety of robust model reduction tools such as Hankel approximation, balanced truncation and balanced stochastic truncation, etc. The capabilities of the toolbox are described and illustated with examples to show how easily they can be used in practice. Examples include structured singular value analysis, H infinity loop-shaping and large space structure model reduction.

Chiang, Richard Y.↗
NASA NTRS1992

Aircraft ride quality controller design using new robust root clustering theory for linear uncertain systems

The aspect of controller design for improving the ride quality of aircraft in terms of damping ratio and natural frequency specifications on the short period dynamics is addressed. The controller is designed to be robust with respect to uncertainties in the real parameters of the control design model such as uncertainties in the dimensional stability derivatives, imperfections in actuator/sensor locations and possibly variations in flight conditions, etc. The design is based on a new robust root clustering theory developed by the author by extending the nominal root clustering theory of Gutman and Jury to perturbed matrices. The proposed methodology allows to get an explicit relationship between the parameters of the root clustering region and the uncertainty radius of the parameter space. The current literature available for robust stability becomes a special case of this unified theory. The bounds derived on the parameter perturbation for robust root clustering are then used in selecting the robust controller.

Yedavalli, R. K.↗
NASA NTRS1993

Robustness

Robustness is a buzz word common to all newly proposed space systems design as well as many new commercial products. The image that one conjures up when the word appears is a 'Paul Bunyon' (lumberjack design), strong and hearty; healthy with margins in all aspects of the design. In actuality, robustness is much broader in scope than margins, including such factors as simplicity, redundancy, desensitization to parameter variations, control of parameter variations (environments flucation), and operational approaches. These must be traded with concepts, materials, and fabrication approaches against the criteria of performance, cost, and reliability. This includes manufacturing, assembly, processing, checkout, and operations. The design engineer or project chief is faced with finding ways and means to inculcate robustness into an operational design. First, however, be sure he understands the definition and goals of robustness. This paper will deal with these issues as well as the need for the requirement for robustness.

Ryan, R.↗