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Results for “time-varying model predictive control”

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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16 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Robot trajectory tracking with self-tuning predicted control

A controller that combines self-tuning prediction and control is proposed for robot trajectory tracking. The controller has two feedback loops: one is used to minimize the prediction error, and the other is designed to make the system output track the set point input. Because the velocity and position along the desired trajectory are given and the future output of the system is predictable, a feedforward loop can be designed for robot trajectory tracking with self-tuning predicted control (STPC). Parameters are estimated online to account for the model uncertainty and the time-varying property of the system. The authors describe the principle of STPC, analyze the system performance, and discuss the simplification of the robot dynamic equations. To demonstrate its utility and power, the controller is simulated for a Stanford arm.

Cui, Xianzhong↗
NASA NTRS2004

GVE-Based Dynamics and Control for Formation Flying Spacecraft

Formation flying is an enabling technology for many future space missions. This paper presents extensions to the equations of relative motion expressed in Keplerian orbital elements, including new initialization techniques for general formation configurations. A new linear time-varying form of the equations of relative motion is developed from Gauss Variational Equations and used in a model predictive controller. The linearizing assumptions for these equations are shown to be consistent with typical formation flying scenarios. Several linear, convex initialization techniques are presented, as well as a general, decentralized method for coordinating a tetrahedral formation using differential orbital elements. Control methods are validated using a commercial numerical propagator.

Breger, Louis↗
NASA NTRS2013

High Resolution Aerosol Data from MODIS Satellite for Urban Air Quality Studies

The Moderate Resolution Imaging Spectroradiometer (MODIS) provides daily global coverage, but the 10 km resolution of its aerosol optical depth (AOD) product is not suitable for studying spatial variability of aerosols in urban areas. Recently, a new Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm was developed for MODIS which provides AOD at 1 km resolution. Using MAIAC data, the relationship between MAIAC AOD and PM(sub 2.5) as measured by the 27 EPA ground monitoring stations was investigated. These results were also compared to conventional MODIS 10 km AOD retrievals (MOD04) for the same days and locations. The coefficients of determination for MOD04 and for MAIAC are R(exp 2) =0.45 and 0.50 respectively, suggested that AOD is a reasonably good proxy for PM(sub 2.5) ground concentrations. Finally, we studied the relationship between PM(sub 2.5) and AOD at the intra-urban scale (10 km) in Boston. The fine resolution results indicated spatial variability in particle concentration at a sub-10 kilometer scale. A local analysis for the Boston area showed that the AOD-PM(sub 2.5) relationship does not depend on relative humidity and air temperatures below approximately 7 C. The correlation improves for temperatures above 7 - 16 C. We found no dependence on the boundary layer height except when the former was in the range 250-500 m. Finally, we apply a mixed effects model approach to MAIAC aerosol optical depth (AOD) retrievals from MODIS to predict PM(sub 2.5) concentrations within the greater Boston area. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations (out-of-sample R(exp 2) of 0.86). Therefore, adjustment for the daily variability in the AOD-PM(sub 2.5) relationship provides a means for obtaining spatially-resolved PM(sub 2.5) concentrations.

remote sensing↗
NASA NTRS2014

Fine Particulate Matter Predictions Using High Resolution Aerosol Optical Depth (AOD) Retrievals

To date, spatial-temporal patterns of particulate matter (PM) within urban areas have primarily been examined using models. On the other hand, satellites extend spatial coverage but their spatial resolution is too coarse. In order to address this issue, here we report on spatial variability in PM levels derived from high 1 km resolution AOD product of Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm developed for MODIS satellite. We apply day-specific calibrations of AOD data to predict PM(sub 2.5) concentrations within the New England area of the United States. To improve the accuracy of our model, land use and meteorological variables were incorporated. We used inverse probability weighting (IPW) to account for nonrandom missingness of AOD and nested regions within days to capture spatial variation. With this approach we can control for the inherent day-to-day variability in the AOD-PM(sub 2.5) relationship, which depends on time-varying parameters such as particle optical properties, vertical and diurnal concentration profiles and ground surface reflectance among others. Out-of-sample "ten-fold" cross-validation was used to quantify the accuracy of model predictions. Our results show that the model-predicted PM(sub 2.5) mass concentrations are highly correlated with the actual observations, with out-of- sample R(sub 2) of 0.89. Furthermore, our study shows that the model captures the pollution levels along highways and many urban locations thereby extending our ability to investigate the spatial patterns of urban air quality, such as examining exposures in areas with high traffic. Our results also show high accuracy within the cities of Boston and New Haven thereby indicating that MAIAC data can be used to examine intra-urban exposure contrasts in PM(sub 2.5) levels.

aerosol optical depth↗
NASA NTRS2010

Ares I-X Flight Evaluation Tasks in Support of Ares I Development

NASA s Constellation Program successfully launched the Ares I-X Flight Test Vehicle on October 28, 2009. The Ares I-X flight was a development flight test that offered a unique opportunity for early engineering data to impact the design and development of the Ares I crew launch vehicle. As the primary customer for flight data from the Ares I-X mission, the Ares Projects Office established a set of 33 flight evaluation tasks to correlate fight results with prospective design assumptions and models. Included within these tasks were direct comparisons of flight data with pre-flight predictions and post-flight assessments utilizing models and modeling techniques being applied to design and develop Ares I. A discussion of the similarities and differences in those comparisons and the need for discipline-level model updates based upon those comparisons form the substance of this paper. The benefits of development flight testing were made evident by implementing these tasks that used Ares I-X data to partially validate tools and methodologies in technical disciplines that will ultimately influence the design and development of Ares I and future launch vehicles. The areas in which partial validation from the flight test was most significant included flight control system algorithms to predict liftoff clearance, ascent, and stage separation; structural models from rollout to separation; thermal models that have been updated based on these data; pyroshock attenuation; and the ability to predict complex flow fields during time-varying conditions including plume interactions.

Huebner, Lawrence D.↗
NASA NTRS1968

Secondary nondestructive instability in medium size liquid fuel rocket engines

Linearized mathematical models of feed-system-coupled combustion instability are summarized and discussed. Following the derivation of sufficient conditions for stability from the simplest bipropellant model, the complications that are imposed on the model by compressible fluids in the feed system, nonrigid feed system structures, and time-varying combustion processes are considered. A specific case of an instability associated with a nonrigid injector is described; it is shown that the instability was eliminated by the method predicted by the model to be most effective for control. A bibliography lists papers dealing with these kinds of stabilities.

R J Fontaine↗
NASA NTRS2010

Adaptive Data-based Predictive Control for Short Take-off and Landing (STOL) Aircraft

Data-based Predictive Control is an emerging control method that stems from Model Predictive Control (MPC). MPC computes current control action based on a prediction of the system output a number of time steps into the future and is generally derived from a known model of the system. Data-based predictive control has the advantage of deriving predictive models and controller gains from input-output data. Thus, a controller can be designed from the outputs of complex simulation code or a physical system where no explicit model exists. If the output data happens to be corrupted by periodic disturbances, the designed controller will also have the built-in ability to reject these disturbances without the need to know them. When data-based predictive control is implemented online, it becomes a version of adaptive control. The characteristics of adaptive data-based predictive control are particularly appropriate for the control of nonlinear and time-varying systems, such as Short Take-off and Landing (STOL) aircraft. STOL is a capability of interest to NASA because conceptual Cruise Efficient Short Take-off and Landing (CESTOL) transport aircraft offer the ability to reduce congestion in the terminal area by utilizing existing shorter runways at airports, as well as to lower community noise by flying steep approach and climb-out patterns that reduce the noise footprint of the aircraft. In this study, adaptive data-based predictive control is implemented as an integrated flight-propulsion controller for the outer-loop control of a CESTOL-type aircraft. Results show that the controller successfully tracks velocity while attempting to maintain a constant flight path angle, using longitudinal command, thrust and flap setting as the control inputs.

Barlow, Jonathan Spencer↗
NASA NTRS2004

Experimentation Toward the Analysis of Gear Noise Sources Controlled by Sliding Friction and Surface Roughness

In helicopters and other rotorcraft, the gearbox is a major source of noise and vibration (N&V). The two N&V excitation mechanisms are the relative displacements between mating gears (transmission errors) and the friction associated with sliding between gear teeth. Historically, transmission errors have been minimized via improved manufacturing accuracies and tooth modifications. Yet, at high torque loads, noise levels are still relatively high though transmission errors might be somewhat minimal. This suggests that sliding friction is indeed a dominant noise source for high power density rotorcraft gearboxes. In reality, friction source mechanism is associated with surface roughness, lubrication regime properties, time-varying friction forces/torques and gear-mesh interface dynamics. Currently, the nature of these mechanisms is not well understood, while there is a definite need for analytical tools that incorporate sliding resistance and surface roughness, and predict their effects on the vibro- acoustic behavior of gears. Toward this end, an experiment was conducted to collect sound and vibration data on the NASA Glenn Gear-Noise Rig. Three iterations of the experiment were accomplished: Iteration 1 tested a baseline set of gears to establish a benchmark. Iteration 2 used a gear-set with low surface asperities to reduce the sliding friction excitation. Iteration 3 incorporated low viscosity oil with the baseline set of gears to examine the effect of lubrication. The results from this experiment will contribute to a two year project in collaboration with the Ohio State University to develop the necessary mathematical and computer models for analyzing geared systems and explain key physical phenomena seen in experiments. Given the importance of sliding friction in the gear dynamic and vibro-acoustic behavior of rotorcraft gearboxes, there is considerable potential for research & developmental activities. Better models and understanding will lead to quiet and reliable gear designs, as well as the selection of optimal manufacturing processes.

Asnani, Vivake M.↗
NASA NTRS1999

The Effects of Partial Mechanical Loading and Ibandronate on Skeletal Tissues in the Adult Rat Hindquarter Suspension Model for Microgravity

We report initial data from a suspended rat model that quantitatively relates chronic partial weightbearing to bone loss. Chronic partial weightbearing is our simulation of the effect of limited artificial gravity aboard spacecraft or reduced planetary gravity. Preliminary analysis of bone by PQCT, histomorphometry, mechanical testing and biochemistry suggest that chronic exposure to half of Earth gravity is insufficient to prevent severe bone loss. The effect of episodic full weightbearing activity (Earth Gravity) on rats otherwise at 50% weightbearing was also explored. This has similarity to treatment by an Earth G-rated centrifuge on a spacecraft that normally maintained artificial gravity at half of Earth G. Our preliminary evidence, using the above techniques to analyze bone, indicate that 2 hours daily of full weightbearing was insufficient to prevent the bone loss observed in 50% weightbearing animals. The effectiveness of partial weightbearing and episodic full weightbearing as potential countermeasures to bone loss in spaceflight was compared with treatment by ibandronate. Ibandronate, a long-acting potent bisphosphonate proved more effective in preventing bone loss and associated functionality based upon structure than our first efforts at mechanical countermeasures. The effectiveness of ibandronate was notable by each of the testing methods we used to study bone from gross structure and strength to tissue and biochemistry. These results appear to be independent of generalized systemic stress imposed by the suspension paradigm. Preliminary evidence does not suggest that blood levels of vitamin D were affected by our countermeasures. Despite the modest theraputic benefit of mechanical countermeasures of partial weightbearing and episodic full weightbearing, we know that some appropriate mechanical signal maintains bone mass in Earth gravity. Moreover, the only mechanism that correctly assigns bone mass and strength to oppose regionally specific force applied to bone is mechanical, a process based upon bone strain. Substantial evidence indicates that the specifics of dynamic loading i.e. time-varying forces are critical. Bone strain history is a predictor of the effect that mechanical conditions have on bone structure mass and strength. Using servo-controlled force plates on suspended rats with implanted strain gauges we manipulated impact forces of ambulation in the frequency (Fourier) domain. Our results indicate that high frequency components of impact forces are particularly potent in producing bone strain independent of the magnitude of the peak force or peak energy applied to the leg. Because a servo-system responds to forces produced by the rat's own muscle activity during ambulation, the direction of ground-reaction loads act on bone through the rat's own musculature. This is in distinction to passive vibration of the floor where forces reach bone through the natural filters of soft tissue and joints. Passive vibration may also be effective, but it may or may not increase bone in the appropriate architectural pattern to oppose the forces of normal ambulatory activity. Effectiveness of high frequency mechanical stimulation in producing regional (muscle directed) bone response will be limited by 1. the sensitivity of bone to a particular range of frequencies and 2. the inertia of the muscles, limiting their response to external forces by increasing tension along insertions. We have begun mathematical modeling of normal ambulatory activity. Effectiveness of high frequency mechanical stimulation in producing regional (muscle directed) bone response will be limited by 1. the sensitivity of bone to a particular range of frequencies and 2. the inertia of the muscles, limiting their response to external forces by increasing tension along insertions. We have begun mathematical modeling of the rat forelimb as a transfer function between impact force and bone strain to predict optimal dynamic loading conditions for this system. We plan additional studies of mechanical counter-measures that incorporate improved dynamic loading, features relevant to anticipated evaluation of artificial gravity, exercise regimens and exposure to Martian gravity, The combination of mechanical countermeasures with ibandronate will also be investigated for signs of synergy.

Schultheis, Lester W.↗
NASA NTRS1978

Prediction, evaluation, and specification of flying qualities by means of step target tracking

A new approach to flying qualities specification and evaluation is presented which coordinates current research in the areas of pilot ratings, pilot-aircraft modeling techniques, and simulation and flight test procedures. A time-domain pilot model is described which can model discontinuous and nonlinear pilot behavior in conjunction with completely general time-varying nonlinear aircraft models to simulate discrete maneuvers. This pilot-aircraft model is applied to an existing set of in-flight simulation data, and calculates tracking error and time-on-target statistics for step target tracking that directly relate to the reported pilot comments and ratings. Predicted step target tracking data for eighteen F-5E flight conditions are presented, and the use of the method for control system design is demonstrated using the YF-17.

Onstott, E. D.↗
NASA NTRS1999

Real-time Adaptive Control Using Neural Generalized Predictive Control

The objective of this paper is to demonstrate the feasibility of a Nonlinear Generalized Predictive Control algorithm by showing real-time adaptive control on a plant with relatively fast time-constants. Generalized Predictive Control has classically been used in process control where linear control laws were formulated for plants with relatively slow time-constants. The plant of interest for this paper is a magnetic levitation device that is nonlinear and open-loop unstable. In this application, the reference model of the plant is a neural network that has an embedded nominal linear model in the network weights. The control based on the linear model provides initial stability at the beginning of network training. In using a neural network the control laws are nonlinear and online adaptation of the model is possible to capture unmodeled or time-varying dynamics. Newton-Raphson is the minimization algorithm. Newton-Raphson requires the calculation of the Hessian, but even with this computational expense the low iteration rate make this a viable algorithm for real-time control.

Haley, Pam↗
NASA NTRS2010

Project Management Using Modern Guidance, Navigation and Control Theory

The idea of control theory and its application to project management is not new, however literature on the topic and real-world applications is not as readily available and comprehensive in how all the principals of Guidance, Navigation and Control (GN&C) apply. This paper will address how the fundamental principals of modern GN&C Theory have been applied to NASA's Constellation Space Suit project and the results in the ability to manage the project within cost, schedule and budget. A s with physical systems, projects can be modeled and managed with the same guiding principles of GN&C as if it were a complex vehicle, system or software with time-varying processes, at times non-linear responses, multiple data inputs of varying accuracy and a range of operating points. With such systems the classic approach could be applied to small and well-defined projects; however with larger, multi-year projects involving multiple organizational structures, external influences and a multitude of diverse resources, then modern control theory is required to model and control the project. The fundamental principals of G N&C stated that a system is comprised of these basic core concepts: State, Behavior, Control system, Navigation system, Guidance and Planning Logic, Feedback systems. The state of a system is a definition of the aspects of the dynamics of the system that can change, such as position, velocity, acceleration, coordinate-based attitude, temperature, etc. The behavior of the system is more of what changes are possible rather than what can change, which is captured in the state of the system. The behavior of a system is captured in the system modeling and if properly done, will aid in accurate system performance prediction in the future. The Control system understands the state and behavior of the system and feedback systems to adjust the control inputs into the system. The Navigation system takes the multiple data inputs and based upon a priori knowledge of the input, will develop a statistical-based weighting of the input to determine where the system currently is located. Guidance and Planning logic of the system with the understanding of where it is (provided by the navigation system) will in turn determine where it needs to be and how to get there. Lastly, the system Feedback system is the right arm of the control system to allow it to affect change in the overall system and therefore it is critical to not only correctly identify the system feedback inputs but also the system response to the feedback inputs. And with any systems project it is critical that the objective of the system be clearly defined for not only planning but to be used to measure performance and to aid in the guidance of the system or project.

Hill, Terry↗
NASA NTRS2010

NASA Tech Briefs, November 2010

Topics covered include: Portable Handheld Optical Window Inspection Device; Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems ; Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry; Browser-Based Application for Telemetry Monitoring of Robotic Assets; Miniature Low-Noise G-Band I-Q Receiver; Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers; Differential Resonant Ring YIG Tuned Oscillator; Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines; Reducing Seal Adhesion in Low Impact Docking Systems; Optimal Flow Control Design; Corrosion-Resistant Container for Molten-Material Processing; Reusable Hot-Wire Cable Cutter; Deployment of a Curved Truss; High-Volume Airborne Fluids Handling Technologies to Fight Wildfires; Modeling of Alkane Oxidation Using Constituents and Species; Fabrication of Lanthanum Telluride 14-1-11 Zintl High-Temperature Thermoelectric Couple; A Computer Model for Analyzing Volatile Removal Assembly; Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature; Optical Sidebands Multiplier; Single Spatial-Mode Room-Temperature-Operated 3.0 to 3.4 micrometer Diode Lasers; Self-Nulling Beam Combiner Using No External Phase Inverter; Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis; Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors; Handheld White Light Interferometer for Measuring Defect Depth in Windows; Decomposition Algorithm for Global Reachability on a Time-Varying Graph; Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids; Efficient Web Services Policy Combination; Using CTX Image Features to Predict HiRISE-Equivalent Rock Density; Isolation of the Paenibacillus phoenicis, a Spore-Forming Bacterium; Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy; Cell Radiation Experiment System; Process to Produce Iron Nanoparticle Lunar Dust Simulant Composite; Inversion Method for Early Detection of ARES-1 Case Breach Failure; Use of ILTV Control Laws for LaNCETS Flight Research;and Evaluating Descent and Ascent Trajectories Near Non-Spherical Bodies.

Source record↗
NASA NTRS2011

Project Management Using Modern Guidance, Navigation and Control Theory

Implementing guidance, navigation, and control (GN&C) theory principles and applying them to the human element of project management and control is not a new concept. As both the literature on the subject and the real-world applications are neither readily available nor comprehensive with regard to how such principles might be applied, this paper has been written to educate the project manager on the "laws of physics" of his or her project (not to teach a GN&C engineer how to become a project manager) and to provide an intuitive, mathematical explanation as to the control and behavior of projects. This paper will also address how the fundamental principles of modern GN&C were applied to the National Aeronautics and Space Administration's (NASA) Constellation Program (CxP) space suit project, ensuring the project was managed within cost, schedule, and budget. A project that is akin to a physical system can be modeled and managed using the same over arching principles of GN&C that would be used if that project were a complex vehicle, a complex system(s), or complex software with time-varying processes (at times nonlinear) containing multiple data inputs of varying accuracy and a range of operating points. The classic GN&C theory approach could thus be applied to small, well-defined projects; yet when working with larger, multiyear projects necessitating multiple organizational structures, numerous external influences, and a multitude of diverse resources, modern GN&C principles are required to model and manage the project. The fundamental principles of a GN&C system incorporate these basic concepts: State, Behavior, Feedback Control, Navigation, Guidance and Planning Logic systems. The State of a system defines the aspects of the system that can change over time; e.g., position, velocity, acceleration, coordinate-based attitude, and temperature, etc. The Behavior of the system focuses more on what changes are possible within the system; this is denoted in the state of the system. The behavior of a system, as captured in the system modeling, when properly done will aid in accurately predicting future system performance. The Feedback Control system understands the state and behavior of the system and uses feedback to adjust control inputs into the system. The feedback, which is the right arm of the Control system, allows change to be affected in the overall system; it therefore is important to not only correctly identify the system feedback inputs, but also the system response to the feedback inputs. The Navigation system takes multiple data inputs and based on a priori knowledge of the inputs, develops a statistically based weighting of the inputs and measurements to determine the system's state. Guidance and Planning Logic of the system, complete with an understanding of where the system is (provided by the Navigation system), will in turn determine where the system needs to be and how to get it there. With any system/project, it is critical that the objective of the system/project be clearly defined -- not only to plan but to measure performance and to aid in guiding the system or the project. The system principles discussed above, which can be and have been applied to the current CxP space suit development project, can also be mapped to real-world constituents, thus allowing project managers to apply systems theories that are well defined in engineering and mathematics to a discipline (i.e., Project Management) that historically has been based in personal experience and intuition. This mapping of GN&C theory to Project Management will, in turn, permit a direct, methodical approach to Project Management, planning and control providing a tool to help predict (and guide) performance and an understanding of the project constraints, how the project can be controlled, and the impacts to external influences and inputs. This approach, to a project manager, flows down to the three bottom-line variables of cost, schedule, and scope ando the needed control of these three variables to successfully perform and complete a project.

Hill, Terry R.↗
NASA NTRS2013

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Architecture and Performance Predictions

A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an F/A-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This paper presents the design and integration of this peak-seeking controller on a modified NASA F/A-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom F/A-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.

performance optimization↗
NASA NTRS2013

Peak-Seeking Optimization of Trim for Reduced Fuel Consumption: Architecture and Performance Predictions

A peak-seeking control approach for real-time trim configuration optimization for reduced fuel consumption has been developed by researchers at the National Aeronautics and Space Administration (NASA) Dryden Flight Research Center to address the goals of the NASA Environmentally Responsible Aviation project to reduce fuel burn and emissions. The peak-seeking control approach is based on a steepest-descent algorithm using a time-varying Kalman filter to estimate the gradient of a performance function of fuel flow versus control surface positions. In real-time operation, deflections of symmetric ailerons, trailing-edge flaps, and leading-edge flaps of an FA-18 airplane (McDonnell Douglas, now The Boeing Company, Chicago, Illinois) are controlled for optimization of fuel flow. This presentation presents the design and integration of this peak-seeking controller on a modified NASA FA-18 airplane with research flight control computers. A research flight was performed to collect data to build a realistic model of the performance function and characterize measurement noise. This model was then implemented into a nonlinear six-degree-of-freedom FA-18 simulation along with the peak-seeking control algorithm. With the goal of eventual flight tests, the algorithm was first evaluated in the improved simulation environment. Results from the simulation predict good convergence on minimum fuel flow with a 2.5-percent reduction in fuel flow relative to the baseline trim of the aircraft.

peak-seeking↗