Results for “Control” — Page 95

NASA NTRS2004

Pilots Rate Augmented Generalized Predictive Control for Reconfiguration

The objective of this paper is to report the results from the research being conducted in reconfigurable fight controls at NASA Ames. A study was conducted with three NASA Dryden test pilots to evaluate two approaches of reconfiguring an aircraft's control system when failures occur in the control surfaces and engine. NASA Ames is investigating both a Neural Generalized Predictive Control scheme and a Neural Network based Dynamic Inverse controller. This paper highlights the Predictive Control scheme where a simple augmentation to reduce zero steady-state error led to the neural network predictor model becoming redundant for the task. Instead of using a neural network predictor model, a nominal single point linear model was used and then augmented with an error corrector. This paper shows that the Generalized Predictive Controller and the Dynamic Inverse Neural Network controller perform equally well at reconfiguration, but with less rate requirements from the actuators. Also presented are the pilot ratings for each controller for various failure scenarios and two samples of the required control actuation during reconfiguration. Finally, the paper concludes by stepping through the Generalized Predictive Control's reconfiguration process for an elevator failure.

Soloway, Don↗

NASA NTRS2004

A Flight Control Approach for Small Reentry Vehicles

Flight control of small crew return vehicles during atmospheric reentry will be an important technology in any human space flight mission undertaken in the future. The control system presented in this paper is applicable to small crew return vehicles in which reaction control system (RCS) thrusters are the only actuators available for attitude control. The control system consists of two modules: (i) the attitude controller using the trajectory linearization control (TLC) technique, and (ii) the reaction control system (RCS) control allocation module using a dynamic table-lookup technique. This paper describes the design and implementation of the TLC attitude control and the dynamic table-lookup RCS control allocation for nonimal flight along with design verification test results.

Bevacqoa, Tim↗

NASA NTRS2005

Effects of Control Mode and R-Ratio on the Fatigue Behavior of a Metal Matrix Composite

Composite Because of their high specific stiffness and strength at elevated temperatures, continuously reinforced metal matrix composites (MMC's) are under consideration for a future generation of aeropropulsion systems. Since components in aeropropulsion systems experience substantial cyclic thermal and mechanical loads, the fatigue behavior of MMC's is of great interest. Almost without exception, previous investigations of the fatigue behavior of MMC's have been conducted in a tension-tension, load-controlled mode. This has been due to the fact that available material is typically less than 2.5-mm thick and, therefore, unable to withstand high compressive loads without buckling. Since one possible use of MMC's is in aircraft skins, this type of testing mode may be appropriate. However, unlike aircraft skins, most engine components are thick. In addition, the transient thermal gradients experienced in an aircraft engine will impose tension-compression loading on engine components, requiring designers to understand how the MMC will behave under fully reversed loading conditions. The increased thickness of the MMC may also affect the fatigue life. Traditionally, low-cycle fatigue (LCF) tests on MMC's have been performed in load control. For monolithic alloys, low-cycle fatigue tests are more typically performed in strain control. Two reasons justify this choice: (1) the critical volume from which cracks initiate and grow is generally small and elastically constrained by the larger surrounding volume of material, and (2) load-controlled, low-cycle fatigue tests of monolithics invariably lead to unconstrained ratcheting and localized necking--an undesired material response because the failure mechanism is far more severe than, and unrelated to, the fatigue mechanism being studied. It is unknown if this is the proper approach to composite testing. However, there is a lack of strain-controlled data on which to base any decisions. Consequently, this study addresses the isothermal, LCF behavior of a [0]_32 MMC tested under strain- and load-controlled conditions for both zero-tension and tension-compression loading conditions. These tests were run at 427 C on thick specimens of SiC-reinforced Ti-15-3. For the fully-reversed tests, no difference was observed in the lives between the load- and strain-controlled tests. However, for the zero-tension tests, the strain-controlled tests had longer lives by a factor of 3 in comparison to the load-controlled tests. This was due to the fact that under strain-control the specimens cyclically softened, reducing the cracking potential. In contrast, the load-controlled tests ratcheted toward larger tensile strains leading to an eventual overload of the fibers. Fatigue tests revealed that specimens tested under fully-reversed conditions had lives approximately an order of magnitude longer than for those specimens tested under zero tension. When examined on a strain-range basis, the fully reversed specimens had similar, but still shorter lives than those of the unreinforced matrix material. However, the composite had a strain limitation at short lives because of the limited strain capacity of the brittle ceramic fiber. The composite also suffered at very high lives because of the lack of an apparent fatigue limit in comparison to the unreinforced matrix. The value of adding fibers to the matrix is apparent when the fatigue lives are plotted as a function of stress range. Here, the composite is far superior to the unreinforced matrix because of the additional load-carrying capacity of the fibers.

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NASA NTRS2006

Reconfigurable Control with Neural Network Augmentation for a Modified F-15 Aircraft

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Burken, John J.↗

NASA NTRS2006

Adaptive Control Using Neural Network Augmentation for a Modified F-15 Aircraft

Description of the performance of a simplified dynamic inversion controller with neural network augmentation follows. Simulation studies focus on the results with and without neural network adaptation through the use of an F-15 aircraft simulator that has been modified to include canards. Simulated control law performance with a surface failure, in addition to an aerodynamic failure, is presented. The aircraft, with adaptation, attempts to minimize the inertial cross-coupling effect of the failure (a control derivative anomaly associated with a jammed control surface). The dynamic inversion controller calculates necessary surface commands to achieve desired rates. The dynamic inversion controller uses approximate short period and roll axis dynamics. The yaw axis controller is a sideslip rate command system. Methods are described to reduce the cross-coupling effect and maintain adequate tracking errors for control surface failures. The aerodynamic failure destabilizes the pitching moment due to angle of attack. The results show that control of the aircraft with the neural networks is easier (more damped) than without the neural networks. Simulation results show neural network augmentation of the controller improves performance with aerodynamic and control surface failures in terms of tracking error and cross-coupling reduction.

Burken, John J.↗

NASA NTRS2006

Rate-Based Model Predictive Control of Turbofan Engine Clearance

An innovative model predictive control strategy is developed for control of nonlinear aircraft propulsion systems and sub-systems. At the heart of the controller is a rate-based linear parameter-varying model that propagates the state derivatives across the prediction horizon, extending prediction fidelity to transient regimes where conventional models begin to lose validity. The new control law is applied to a demanding active clearance control application, where the objectives are to tightly regulate blade tip clearances and also anticipate and avoid detrimental blade-shroud rub occurrences by optimally maintaining a predefined minimum clearance. Simulation results verify that the rate-based controller is capable of satisfying the objectives during realistic flight scenarios where both a conventional Jacobian-based model predictive control law and an unconstrained linear-quadratic optimal controller are incapable of doing so. The controller is evaluated using a variety of different actuators, illustrating the efficacy and versatility of the control approach. It is concluded that the new strategy has promise for this and other nonlinear aerospace applications that place high importance on the attainment of control objectives during transient regimes.

DeCastro, Jonathan A.↗

NASA NTRS2007

Contrasting Perspectives Of Junior versus Senior NASA ISS Flight Controllers On Leadership And Cultural Issues

NASA flight controllers have always worked in a very demanding environment, but the International Space Station (ISS) poses even more challenges than prior missions. A recent NASA/Ames survey by Parke and Orasanu of NASA/Johnson flight controllers uncovered concerns about communications problems between American personnel and their international counterparts. To better understand these problems, we interviewed 14 senior and 12 junior ISS flight controllers at NASA/Johnson about leadership and cultural challenges they face and strategies for addressing these challenges. The qualitative interview data were coded and tabulated. Here we present quantitative analyses testing for differences between junior and senior controllers. Based on nonparametric statistical tests comparing responses across groups, the senior controllers were significantly more aware of the impact of working in dispersed teams, the context of constant change, and the upcoming multilateral challenges, while junior controllers were more aware of language and cultural issues. We consider our findings in light of other studies of controllers and other known differences between senior and junior controllers. For example, the fact that senior controllers had their formative early experience controlling pre-ISS short-duration Shuttle missions seems to have both positive and negative aspects, which are supported by our data. Our findings may also reflect gender differences, but we cannot unconfound this effect in our data because all the senior respondents were males. Many of the junior-senior differences are not only due to elapsed time on the job, but also due to a cohort effect. The findings of this study should be used for training curricula tailored differently for junior and senior controllers.

Clement, James L.↗

NASA NTRS2007

Identification and Control of Aircrafts using Multiple Models and Adaptive Critics

We compared two possible implementations of local linear models for control: one approach is based on a self-organizing map (SOM) to cluster the dynamics followed by a set of linear models operating at each cluster. Therefore the gating function is hard (a single local model will represent the regional dynamics). This simplifies the controller design since there is a one to one mapping between controllers and local models. The second approach uses a soft gate using a probabilistic framework based on a Gaussian Mixture Model (also called a dynamic mixture of experts). In this approach several models may be active at a given time, we can expect a smaller number of models, but the controller design is more involved, with potentially better noise rejection characteristics. Our experiments showed that the SOM provides overall best performance in high SNRs, but the performance degrades faster than with the GMM for the same noise conditions. The SOM approach required about an order of magnitude more models than the GMM, so in terms of implementation cost, the GMM is preferable. The design of the SOM is straight forward, while the design of the GMM controllers, although still reasonable, is more involved and needs more care in the selection of the parameters. Either one of these locally linear approaches outperform global nonlinear controllers based on neural networks, such as the time delay neural network (TDNN). Therefore, in essence the local model approach warrants practical implementations. In order to call the attention of the control community for this design methodology we extended successfully the multiple model approach to PID controllers (still today the most widely used control scheme in the industry), and wrote a paper on this subject. The echo state network (ESN) is a recurrent neural network with the special characteristics that only the output parameters are trained. The recurrent connections are preset according to the problem domain and are fixed. In a nutshell, the states of the reservoir of recurrent processing elements implement a projection space, where the desired response is optimally projected. This architecture trades training efficiency by a large increase in the dimension of the recurrent layer. However, the power of the recurrent neural networks can be brought to bear on practical difficult problems. Our goal was to implement an adaptive critic architecture implementing Bellman s approach to optimal control. However, we could only characterize the ESN performance as a critic in value function evaluation, which is just one of the pieces of the overall adaptive critic controller. The results were very convincing, and the simplicity of the implementation was unparalleled.

Principe, Jose C.↗

NASA NTRS1996

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz.

Burdisso, Ricardo↗

NASA NTRS1994

Active control of aircraft engine inlet noise using compact sound sources and distributed error sensors

An active noise control system using a compact sound source is effective to reduce aircraft engine duct noise. The fan noise from a turbofan engine is controlled using an adaptive filtered-x LMS algorithm. Single multi channel control systems are used to control the fan blade passage frequency (BPF) tone and the BPF tone and the first harmonic of the BPF tone for a plane wave excitation. A multi channel control system is used to control any spinning mode. The multi channel control system to control both fan tones and a high pressure compressor BPF tone simultaneously. In order to make active control of turbofan inlet noise a viable technology, a compact sound source is employed to generate the control field. This control field sound source consists of an array of identical thin, cylindrically curved panels with an inner radius of curvature corresponding to that of the engine inlet. These panels are flush mounted inside the inlet duct and sealed on all edges to prevent leakage around the panel and to minimize the aerodynamic losses created by the addition of the panels. Each panel is driven by one or more piezoelectric force transducers mounted on the surface of the panel. The response of the panel to excitation is maximized when it is driven at its resonance; therefore, the panel is designed such that its fundamental frequency is near the tone to be canceled, typically 2000-4000 Hz.

Burdisso, Ricardo↗

NASA NTRS1997

Method for neural network control of motion using real-time environmental feedback

A method of motion control for robotics and other automatically controlled machinery using a neural network controller with real-time environmental feedback. The method is illustrated with a two-finger robotic hand having proximity sensors and force sensors that provide environmental feedback signals. The neural network controller is taught to control the robotic hand through training sets using back- propagation methods. The training sets are created by recording the control signals and the feedback signal as the robotic hand or a simulation of the robotic hand is moved through a representative grasping motion. The data recorded is divided into discrete increments of time and the feedback data is shifted out of phase with the control signal data so that the feedback signal data lag one time increment behind the control signal data. The modified data is presented to the neural network controller as a training set. The time lag introduced into the data allows the neural network controller to account for the temporal component of the robotic motion. Thus trained, the neural network controlled robotic hand is able to grasp a wide variety of different objects by generalizing from the training sets.

Buckley, Theresa M.↗

NASA NTRS2003

Adaptive control system having hedge unit and related apparatus and methods

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

Johnson, Eric Norman↗

NASA NTRS2007

Adaptive control system having hedge unit and related apparatus and methods

The invention includes an adaptive control system used to control a plant. The adaptive control system includes a hedge unit that receives at least one control signal and a plant state signal. The hedge unit generates a hedge signal based on the control signal, the plant state signal, and a hedge model including a first model having one or more characteristics to which the adaptive control system is not to adapt, and a second model not having the characteristic(s) to which the adaptive control system is not to adapt. The hedge signal is used in the adaptive control system to remove the effect of the characteristic from a signal supplied to an adaptation law unit of the adaptive control system so that the adaptive control system does not adapt to the characteristic in controlling the plant.

Johnson, Eric Norman↗

NASA NTRS2007

Emergency Flight Control of a Twin-Jet Commercial Aircraft using Manual Throttle Manipulation

The Department of Homeland Security (DHS) created the PCAR (Propulsion-Controlled Aircraft Recovery) project in 2005 to mitigate the ManPADS (man-portable air defense systems) threat to the commercial aircraft fleet with near-term, low-cost proven technology. Such an attack could potentially cause a major FCS (flight control system) malfunction or other critical system failure onboard the aircraft, despite the extreme reliability of current systems. For the situations in which nominal flight controls are lost or degraded, engine thrust may be the only remaining means for emergency flight control [ref 1]. A computer-controlled thrust system, known as propulsion-controlled aircraft (PCA), was developed in the mid 1990s with NASA, McDonnell Douglas and Honeywell. PCA's major accomplishment was a demonstration of an automatic landing capability using only engine thrust [ref 11. Despite these promising results, no production aircraft have been equipped with a PCA system, due primarily to the modifications required for implementation. A minimally invasive option is TOC (throttles-only control), which uses the same control principles as PCA, but requires absolutely no hardware, software or other aircraft modifications. TOC is pure piloting technique, and has historically been utilized several times by flight crews, both military and civilian, in emergency situations stemming from a loss of conventional control. Since the 1990s, engineers at NASA Dryden Flight Research Center (DFRC) have studied TOC, in both simulation and flight, for emergency flight control with test pilots in numerous configurations. In general, it was shown that TOC was effective on certain aircraft for making a survivable landing. DHS sponsored both NASA Dryden Flight Research Center (Edwards, CA) and United Airlines (Denver, Colorado) to conduct a flight and simulation study of the TOC characteristics of a twin-jet commercial transport, and assess the ability of a crew to control an aircraft down to a survivable runway landing using TOC. The PCAR project objective was a set of pilot procedures for operation of a specific aircraft without hydraulics that (a) have been validated in both simulation and flight by relevant personnel, and (b) mesh well with existing commercial operations, maintenance, and training at a minimum cost. As a result of this study, a procedure has been developed to assist a crew in making a survivable landing using TOC. In a simulation environment, line pilots with little or no previous TOC experience performed survivable runway landings after a few practice TOC approaches. In-flight evaluations put line pilots in a simulated emergency situation where TOC was used to recover the aircraft, maneuver to a landing site, and perform an approach down to 200 feet AGL. The results of this research, including pilot observations, procedure comments, recommendations, future work and lessons learned, will he discussed. Flight data and video footage of TOC approaches may also be shown.

Cole, Jennifer H.↗

NASA NTRS2008

Closing the Certification Gaps in Adaptive Flight Control Software

Over the last five decades, extensive research has been performed to design and develop adaptive control systems for aerospace systems and other applications where the capability to change controller behavior at different operating conditions is highly desirable. Although adaptive flight control has been partially implemented through the use of gain-scheduled control, truly adaptive control systems using learning algorithms and on-line system identification methods have not seen commercial deployment. The reason is that the certification process for adaptive flight control software for use in national air space has not yet been decided. The purpose of this paper is to examine the gaps between the state-of-the-art methodologies used to certify conventional (i.e., non-adaptive) flight control system software and what will likely to be needed to satisfy FAA airworthiness requirements. These gaps include the lack of a certification plan or process guide, the need to develop verification and validation tools and methodologies to analyze adaptive controller stability and convergence, as well as the development of metrics to evaluate adaptive controller performance at off-nominal flight conditions. This paper presents the major certification gap areas, a description of the current state of the verification methodologies, and what further research efforts will likely be needed to close the gaps remaining in current certification practices. It is envisioned that closing the gap will require certain advances in simulation methods, comprehensive methods to determine learning algorithm stability and convergence rates, the development of performance metrics for adaptive controllers, the application of formal software assurance methods, the application of on-line software monitoring tools for adaptive controller health assessment, and the development of a certification case for adaptive system safety of flight.

Jacklin, Stephen A.↗

NASA NTRS2010

Compact, Reliable EEPROM Controller

A compact, reliable controller for an electrically erasable, programmable read-only memory (EEPROM) has been developed specifically for a space-flight application. The design may be adaptable to other applications in which there are requirements for reliability in general and, in particular, for prevention of inadvertent writing of data in EEPROM cells. Inadvertent writes pose risks of loss of reliability in the original space-flight application and could pose such risks in other applications. Prior EEPROM controllers are large and complex and do not provide all reasonable protections (in many cases, few or no protections) against inadvertent writes. In contrast, the present controller provides several layers of protection against inadvertent writes. The controller also incorporates a write-time monitor, enabling determination of trends in the performance of an EEPROM through all phases of testing. The controller has been designed as an integral subsystem of a system that includes not only the controller and the controlled EEPROM aboard a spacecraft but also computers in a ground control station, relatively simple onboard support circuitry, and an onboard communication subsystem that utilizes the MIL-STD-1553B protocol. (MIL-STD-1553B is a military standard that encompasses a method of communication and electrical-interface requirements for digital electronic subsystems connected to a data bus. MIL-STD- 1553B is commonly used in defense and space applications.) The intent was to both maximize reliability while minimizing the size and complexity of onboard circuitry. In operation, control of the EEPROM is effected via the ground computers, the MIL-STD-1553B communication subsystem, and the onboard support circuitry, all of which, in combination, provide the multiple layers of protection against inadvertent writes. There is no controller software, unlike in many prior EEPROM controllers; software can be a major contributor to unreliability, particularly in fault situations such as the loss of power or brownouts. Protection is also provided by a powermonitoring circuit.

Katz, Richard↗

NASA NTRS2010

Design of a Model Reference Adaptive Controller for an Unmanned Air Vehicle

This paper presents the "Adaptive Control Technology for Safe Flight (ACTS)" architecture, which consists of a non-adaptive controller that provides satisfactory performance under nominal flying conditions, and an adaptive controller that provides robustness under off nominal ones. The design and implementation procedures of both controllers are presented. The aim of these procedures, which encompass both theoretical and practical considerations, is to develop a controller suitable for flight. The ACTS architecture is applied to the Generic Transport Model developed by NASA-Langley Research Center. The GTM is a dynamically scaled test model of a transport aircraft for which a flight-test article and a high-fidelity simulation are available. The nominal controller at the core of the ACTS architecture has a multivariable LQR-PI structure while the adaptive one has a direct, model reference structure. The main control surfaces as well as the throttles are used as control inputs. The inclusion of the latter alleviates the pilot s workload by eliminating the need for cancelling the pitch coupling generated by changes in thrust. Furthermore, the independent usage of the throttles by the adaptive controller enables their use for attitude control. Advantages and potential drawbacks of adaptation are demonstrated by performing high fidelity simulations of a flight-validated controller and of its adaptive augmentation.

Crespo, Luis G.↗

NASA NTRS2010

A Framework for Optimal Control Allocation with Structural Load Constraints

Conventional aircraft generally employ mixing algorithms or lookup tables to determine control surface deflections needed to achieve moments commanded by the flight control system. Control allocation is the problem of converting desired moments into control effector commands. Next generation aircraft may have many multipurpose, redundant control surfaces, adding considerable complexity to the control allocation problem. These issues can be addressed with optimal control allocation. Most optimal control allocation algorithms have control surface position and rate constraints. However, these constraints are insufficient to ensure that the aircraft's structural load limits will not be exceeded by commanded surface deflections. In this paper, a framework is proposed to enable a flight control system with optimal control allocation to incorporate real-time structural load feedback and structural load constraints. A proof of concept simulation that demonstrates the framework in a simulation of a generic transport aircraft is presented.

Frost, Susan A.↗