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Mechanical design, and environmental and functional testing of advanced telemetry system flight package with adaptive capability
It is expected that space systems for the future will evolve to structures of unprecedented size with associated extreme control requirements. A method is necessary that is sufficiently general to initiate stable control of a vehicle and subsequently learn the true nature of the structure. It is suggested that a suitable constructed expert system (ES) would be capable of learning by appending observations to a knowledge base. To verify that an ES can control a large space structure, numerical simulations of a simple structure subjected to periodic vibrations and the performance of a classical controllers were performed. The ES was then exercised to show its ability to truthfully mimic nominal control and to demonstrate its superiority to the classical controller, given sensor failures. An ES generating software package, The Intelligent Machine Model, was employed. It uses the pattern matching technique. Results of this program are discussed.
As technology evolves and improves within the science of composite materials, new fiber/ resin systems are being developed for improved properties given certain loading and environmental scenarios. Improving the room temperature damage tolerance capabilities has long been one of the goals in the carbon fiber/polymer composite industry. Recently a new fiber/epoxy system has been introduced that is claimed to have superior damage tolerance capabilities. To examine if this new carbon fiber/epoxy composite material would be of benefit to a program to manufacture a Payload Adapter Fitting (PAF) for NASA’s Space Launch System (SLS) rocket, the question was asked as to just how much damage tolerance could be realized if this new system were used. Compression after impact (CAI) strength of sandwich structure is one of the leading metrics being used to evaluate materials for the PAF program. As a result, a comparison of this new fiber/resin system with a very common (and planned baseline) fiber/resin system with respect to CAI was considered in this study. While it was already known that the older, baseline carbon fiber structure would not have as good damage tolerance characteristics as the newer carbon fiber system, the quantitative difference in damage tolerance was sought in this study since no other CAI data could be found in open literature on sandwich structures made with this new fiber/resin system.
Stable adaptive control design for linear time- invariant system with same number of inputs as outputs, considering disturbance effect
As NASA software systems continue to innovate, becoming more complex and nondeterministic, the need for the NASA IV&V Program to become systemically adaptive to ensure mission success is paramount. To ensure adaptability within resource constraints, IV&V has developed an agile, risk-based approach to identify, characterize, scope, focus, and prioritize mission assurance activities. This risk based adaptive framework has been applied to trends such as increased reliance on data driven algorithms for safety and mission critical software behavior, use of MBSE in system design, and application of agile principles to embedded software development. The framework is enabled by continuous innovation of new approaches such as software only test beds, assurance design tools, and initiatives that augment IV&V assurance methods with artificial intelligence and machine learning techniques. This presentation will highlight the trends the NASA IV&V Program is seeing, the innovative steps it is taking to address those challenges, and how it is postured to address evolving risk and constantly changing and new technologies.
This presentation presents the testing approach and initial laboratory test results of the Adaptive Optics (AO) Subassembly (AOS) for the Low-Cost Optical Terminal (LCOT), a low-cost and flexible optical communications ground terminal. Leveraging commercial components and subassemblies wherever possible, LCOT is being developed by the NASA Goddard Space Flight Center (GSFC) Advanced Communications Capabilities for Exploration and Science Systems (ACCESS) project. An economical ground terminal allows NASA to create a global optical terminal network and enables the expansion of direct-to-Earth (DTE) optical communications. Located at the Goddard Geophysical and Astronomical Observatory (GGAO), LCOT is in the development phase and will receive first light during initial testing beginning in 2023. This new optical terminal includes a 700 mm Ritchey-Chretien commercial telescope, able to track Low Earth Orbit (LEO) spacecraft, receive instruments specified from 1500 - 1600 nm, and an uplink transmit optical system. Demodulation of optical coherent modulation formats requires downlink signal coupling into single-mode fiber. Due to atmospheric turbulence, signals experience wavefront distortions creating speckle patterns larger than the fiber core and high jitter requiring precise beam steering. AO is necessary to correct atmospheric turbulence effects and allow efficient coupling of received signals. In 2020, GSFC contracted with General Atomics to provide the LCOT AO system. This system has been delivered to GSFC in September 2021 and has been tested in laboratory to evaluate performance. This paper describes the laboratory testing approach, turbulence phase plate design, test results, and the AO field testing plan when installed on the LCOT telescope.
The paper is concerned with the on-line identification of system Markov parameters using observers. Two types of parameters are sought: the forward system parameters, which provide estimates of the outputs for given inputs, and inverse system parameters, which provide estimates of inputs for given outputs. A procedure is proposed which uses the inverse system to generate commands that produce a desired system response. The feasibility of the procedure is demonstrated using test results from an implementation of a truss structure fitted with piezoelectric actuators and collocated strain gauges.
The paper considers the problem of designing a learning control system (LCS) that is capable of meeting design requirements over many possible operating conditions of the plant by adjusting, in a prescribed manner, the feedforward and feedback gains of the plant. The approach utilizes the best features of two methods, gain scheduling and adaptive control. The LCS was implemented using two models, one representing the longitudinal dynamics and the other the lateral dynamics of the simulated plant. A block diagram illustrating the functional organization of an LCS is presented.
To the first order, the localization precision and angular resolution of a cylindrical, time-encoded imaging (c-TEI) system is governed by the geometry of the system. Improving either measure requires increasing the mask radius or decreasing the detector diameter, both of which are undesirable. Here, we propose an alternative option of repositioning the detector within the mask to increase the detector-to-mask distance in the direction of a source, thereby improving the localization precision and angular resolution in that direction. Since the detector-to-mask distance only increases for a small portion of the field of view (FOV), we propose implementing adaptive imaging where one leverages data collected during the measurement to optimize the system configuration. This article utilizes both simulations and experiments to set upper bounds on the potential gain from adaptive detector movements for one and two sources in the FOV. When only one source is present, adaptive detector movements can improve the localization precision and angular resolution by 20% for a source at 90 cm and by 32% for a far-field source. When two sources are present, adaptive detector movements can improve localization precision and angular resolution by up to 50% for sources that are ~10° apart (90 cm from the system). We experimentally verify these results through maximum likelihood estimation of the source position(s) and image reconstruction of point sources that are close together. As a demonstration of an adaptive imaging algorithm, we image a complex arrangement of special nuclear material at the Zero Power Physics Reactor facility at Idaho National Laboratory.
The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) is used to test and develop these algorithms. Modifications to this airplane include adding canards and changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals include demonstration of revolutionary control approaches that can efficiently optimize aircraft performance in both normal and failure conditions and advancement of neural-network-based flight control technology for new aerospace system designs. This report presents an overview of the processes utilized to develop adaptive controller algorithms during a flight-test program, including a description of initial adaptive controller concepts and a discussion of modeling formulation and performance testing. Design finalization led to integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness; these are also discussed.
This report presents the success merits, logic design details, and test plans for adaptive protection schemes for microgrids, secondary distribution networks, and radial distribution feeders. Success merits are presented in terms of challenges and issues which should be mitigated. The challenges and issues were identified during site-specific simulations and analysis presented in a prior report. The adaptive protection logic designs are presented in a vendor-neutral manner to make them readily adaptable to site--specific protection relays and controllers which support custom logic design. Vendor-specific implementations of the logic for the adaptive protection laboratory tests are also presented. The final section of the report presents details of the testing methodology, plans, and documentation for each of the three adaptive protection schemes.
Common practice in the development of simulation systems is meeting all user requirements within a single instantiation. The Joint Polar Satellite System (JPSS) presents a unique challenge to establish a simulation environment that meets the needs of a diverse user community while also spanning a multi-mission environment over decades of operation. In response, the JPSS Flight Vehicle Test Suite (FVTS) is architected with an extensible infrastructure that supports the operation of multiple observatory simulations for a single mission and multiple mission within a common system perimeter. For the JPSS-1 satellite, multiple fidelity flight observatory simulations are necessary to support the distinct user communities consisting of the Common Ground System development team, the Common Ground System Integration & Test team, and the Mission Rehearsal Team/Mission Operations Team. These key requirements present several challenges to FVTS development. First, the FVTS must ensure all critical user requirements are satisfied by at least one fidelity instance of the observatory simulation. Second, the FVTS must allow for tailoring of the system instances to function in diverse operational environments from the High-security operations environment at NOAA Satellite Operations Facility (NSOF) to the ground system factory floor. Finally, the FVTS must provide the ability to execute sustaining engineering activities on a subset of the system without impacting system availability to parallel users. The FVTS approach of allowing for multiple fidelity copies of observatory simulations represents a unique concept in simulator capability development and corresponds to the JPSS Ground System goals of establishing a capability that is flexible, extensible, and adaptable.
Adaptive notch filter, using modulation techniques for reversed phase noise signal
High-workload, fast-paced, and degraded sensory environments are the likeliest candidates to benefit from multimodal information presentation. For example, during EVA (Extra-Vehicular Activity) and telerobotic operations, the sensory restrictions associated with a space environment provide a major challenge to maintaining the situation awareness (SA) required for safe operations. Multimodal displays hold promise to enhance situation awareness and task performance by utilizing different sensory modalities and maximizing their effectiveness based on appropriate interaction between modalities. During EVA, the visual and auditory channels are likely to be the most utilized with tasks such as monitoring the visual environment, attending visual and auditory displays, and maintaining multichannel auditory communications. Previous studies have shown that compared to unimodal displays (spatial auditory or 2D visual), bimodal presentation of information can improve operator performance during simulated extravehicular activity on planetary surfaces for tasks as diverse as orientation, localization or docking, particularly when the visual environment is degraded or workload is increased. Tactile displays offer a third sensory channel that may both offload information processing effort and provide a means to capture attention when urgently required. For example, recent studies suggest that including tactile cues may result in increased orientation and alerting accuracy, improved task response time and decreased workload, as well as provide self-orientation cues in microgravity on the ISS (International Space Station). An important overall issue is that context-dependent factors like task complexity, sensory degradation, peripersonal vs. extrapersonal space operations, workload, experience level, and operator fatigue tend to vary greatly in complex real-world environments and it will be difficult to design a multimodal interface that performs well under all conditions. As a possible solution, adaptive systems have been proposed in which the information presented to the user changes as a function of taskcontext-dependent factors. However, this presupposes that adequate methods for detecting andor predicting such factors are developed. Further, research in adaptive systems for aviation suggests that they can sometimes serve to increase workload and reduce situational awareness. It will be critical to develop multimodal display guidelines that include consideration of smart systems that can select the best display method for a particular contextsituation.The scope of the current work is an analysis of potential multimodal display technologies for long duration missions and, in particular, will focus on their potential role in EVA activities. The review will address multimodal (combined visual, auditory andor tactile) displays investigated by NASA, industry, and DoD (Dept. of Defense). It also considers the need for adaptive information systems to accommodate a variety of operational contexts such as crew status (e.g., fatigue, workload level) and task environment (e.g., EVA, habitat, rover, spacecraft). Current approaches to guidelines and best practices for combining modalities for the most effective information displays are also reviewed. Potential issues in developing interface guidelines for the Exploration Information System (EIS) are briefly considered.
The National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) is conducting ongoing flight research using adaptive controller algorithms. A highly modified McDonnell-Douglas NF-15B airplane called the F-15 Intelligent Flight Control System (IFCS) was used for these algorithms. This airplane has been modified by the addition of canards and by changing the flight control systems to interface a single-string research controller processor for neural network algorithms. Research goals included demonstration of revolutionary control approaches that can efficiently optimize aircraft performance for both normal and failure conditions, and to advance neural-network-based flight control technology for new aerospace systems designs. Before the NF-15B IFCS airplane was certified for flight test, however, certain processes needed to be completed. This paper presents an overview of these processes, including a description of the initial adaptive controller concepts followed by a discussion of modeling formulation and performance testing. Upon design finalization, the next steps are: integration with the system interfaces, verification of the software, validation of the hardware to the requirements, design of failure detection, development of safety limiters to minimize the effect of erroneous neural network commands, and creation of flight test control room displays to maximize human situational awareness.
The use of adaptive system to stabilize a launch vehicle with sloshable fuel is discussed. The adaptive system is based on a laser sensor to measure fluid displacement in the tank, a recursive-least-squares estimator to assess the natural frequency of the sloshing fuel, and a linear filter to stabilize the unstable fuel slosh. The method is found to be promising for a pitch-plane, single pendulum model.
This paper describes CLIPS-R, a theory revision system for the revision of CLIPS rule-bases. CLIPS-R may be used for a variety of knowledge-base revision tasks, such as refining a prototype system, adapting an existing system to slightly different operating conditions, or improving an operational system that makes occasional errors. We present a description of how CLIPS-R revises rule-bases, and an evaluation of the system on three rule-bases.