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Bajwa, Anupa

Publications and source records attributed to Bajwa, Anupa.

15 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2018

Design Considerations for a Variable Autonomy Executive for UAS in the NAS

This paper describes research targeted towards an autonomy executive (AOS) for UAS in the National Air Space (NAS). The project goal is to incrementally provide the knowledge and intelligence onboard a UAS to safely fly in the National Air Space, eventually autonomous from remote human ground crews and communicating directly with air traffic control. Longer-term, the goal is to provide the capability for pilotless air vehicles such as air taxis that will be key for new transportation concepts such as air mobility-on-demand. For both of these targeted applications, AOS is incorporating artificial intelligence capabilities that operationally meet human pilot competencies. Even when autonomy is achieved from a remote human ground crew, AOS will have variable degrees of autonomy with respect to air traffic control (ATC), just as human pilots do now. AOS has the capability of interacting in natural language with ATC, as well as through data link protocols. AOS can adapt to varying levels of autonomy and control directed by ATC in standard and relaxed FAA phraseology- from being vectored moment by moment, to accepting broad directives such as following a specified aircraft or sighting and avoiding traffic. AOS can autonomously manage contingencies such as vehicle systems degradations and failures. It incorporates a decision maker that takes information from multiple diagnostic reasoners, disambiguates (if needed) sensor results to specific failures using active mode changes, then projects forward the impact of the degradation on the nominal plan. If the nominal plan is no longer viable, then alternative plans are formulated, and subsequently selected and executed, including abort options.

Lowry, Michael↗
NASA NTRS2017

Autonomy Operating System for UAVs: Pilot-in-a-Box

The Autonomy Operating System (AOS) is an open flight software platform with Artificial Intelligence for smart UAVs. It is built to be extendable with new apps, similar to smartphones, to enable an expanding set of missions and capabilities. AOS has as its foundations NASAs core flight executive and core flight software (cFEcFS). Pilot-in-a-Box (PIB) is an expanding collection of interacting AOS apps that provide the knowledge and intelligence onboard a UAV to safely and autonomously fly in the National Air Space, eventually without a remote human ground crew. Longer-term, the goal of PIB is to provide the capability for pilotless air vehicles such as air taxis that will be key for new transportation concepts such as mobility-on-demand. PIB provides the procedural knowledge, situational awareness, and anticipatory planning (thinking ahead of the plane) that comprises pilot competencies. These competencies together with a natural language interface will enable Pilot-in-a-Box to dialogue directly with Air Traffic Management from takeoff through landing. This paper describes the overall AOS architecture, Artificial Intelligence reasoning engines, Pilot-in-a-box competencies, and selected experimental flight tests to date.

Lowry, Michael↗
NASA NTRS2015

From Diagnosis to Action: An Automated Failure Advisor for Human Deep Space Missions

The major goal of current space system development at NASA is to enable human travel to deep space locations such as Mars and asteroids. At that distance, round trip communication with ground operators may take close to an hour, thus it becomes unfeasible to seek ground operator advice for problems that require immediate attention, either for crew safety or for activities that need to be performed at specific times for the attainment of scientific results. To achieve this goal, major reliance will need to be placed on automation systems capable of aiding the crew in detecting and diagnosing failures, assessing consequences of these failures, and providing guidance in repair activities that may be required. We report here on the most current step in the continuing development of such a system, and that is the addition of a Failure Response Advisor. In simple terms, we have a system in place the Advanced Caution and Warning System (ACAWS) to tell us what happened (failure diagnosis) and what happened because that happened (failure effects). The Failure Response Advisor will tell us what to do about it, how long until something must be done and why its important that something be done and will begin to approach the complex reasoning that is generally required for an optimal approach to automated system health management. This advice is based on the criticality and various timing elements, such as durations of activities and of component repairs, failure effects delay, and other factors. The failure advice is provided to operators (crew and mission controllers) together with the diagnostic and effects information. The operators also have the option to drill down for more information about the failure and the reasons for any suggested priorities.

spacecraft health maintenance↗
NASA NTRS2015

LADEE Preparations for Contingency Operations for the Lunar Orbit Insertion Maneuver

The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft was launched on September 7, 2013 UTC, and completed its mission on April 17, 2014 UTC with a directed impact to the Lunar Surface. Its primary goals were to examine the lunar atmosphere, measure lunar dust, and to demonstrate high rate laser communications. The mission objectives, much of which can be attributed to careful LADEE mission was a resounding success, achieving all planning and preparation. This paper discusses the specific preparations for fault conditions that could occur during a highly-critical phase of the mission, the Lunar Orbit Insertion (LOI). highly critical phase of the mission.

failure analysis↗
NASA NTRS2015

LADEE Preparations for Contingency Operations for the Lunar Orbit Insertion Maneuver

The Lunar Atmosphere and Dust Environment Explorer (LADEE) spacecraft was launched on September 6, 2013, and completed its mission on April 17, 2014 with a directed impact to the Lunar Surface. Its primary goals were to examine the lunar atmosphere, measure lunar dust, and to demonstrate high rate laser communications. The LADEE mission was a resounding success, achieving all mission objectives, much of which can be attributed to careful planning and preparation. This paper discusses the specific preparations for fault conditions that could occur during a highly-critical phase of the mission. To get to the Moon, the spacecraft traversed multiple phasing loops around the Earth, and then executed a breaking maneuver to achieve lunar orbit. This Lunar Orbit Insertion (LOI) maneuver was perhaps the most time-critical phase of the entire mission. The LOI maneuver had to occur within a twenty minute window in order to achieve lunar orbit with an acceptable amount of propellant remaining. Missing this window would have likely resulted in a loss of the entire mission. An additional challenge of the maneuver was that spacecraft was out of view for approximately one hour prior to the main thruster burn, with the burn needing to occur within five minutes after coming into view. These conditions resulted in unique challenges for ground operations and the fault management system. Early in the planning stages of the mission, the criticality and challenges of this maneuver were evident to the system designers. The major concern was that any triggering of the on-board fault management system, whether it is in response to a true fault or a false positive, would result in an unacceptable delay to the burn. Therefore the flight software was designed with a flexible fault management system, such that any or all of the fault management responses could be disabled for the lead up and execution of the maneuver. Later, a triage was conducted to develop a list of fault responses, mapped to various parts of the timeline of the maneuver. Some of these contingency responses were solely ground-based if the time to detect, diagnose, and respond were adequate. Other responses were automated on-board if the response time from the ground would have been inadequate. For instance, in order to recover from a system reboot, on-board automation would have automatically reconfigured the spacecraft for the burn and reoriented the spacecraft to the burn attitude.These contingency responses were practiced, over and over, during numerous rehearsals. Although the LOI maneuver was executed without having to use any of these contingencies, the LADEE team was adequately prepared for this highly critical phase of the mission.

Cannon, Howard↗
NASA NTRS2011

Parametric Testing of Launch Vehicle FDDR Models

For the safe operation of a complex system like a (manned) launch vehicle, real-time information about the state of the system and potential faults is extremely important. The on-board FDDR (Failure Detection, Diagnostics, and Response) system is a software system to detect and identify failures, provide real-time diagnostics, and to initiate fault recovery and mitigation. The ERIS (Evaluation of Rocket Integrated Subsystems) failure simulation is a unified Matlab/Simulink model of the Ares I Launch Vehicle with modular, hierarchical subsystems and components. With this model, the nominal flight performance characteristics can be studied. Additionally, failures can be injected to see their effects on vehicle state and on vehicle behavior. A comprehensive test and analysis of such a complicated model is virtually impossible. In this paper, we will describe, how parametric testing (PT) can be used to support testing and analysis of the ERIS failure simulation. PT uses a combination of Monte Carlo techniques with n-factor combinatorial exploration to generate a small, yet comprehensive set of parameters for the test runs. For the analysis of the high-dimensional simulation data, we are using multivariate clustering to automatically find structure in this high-dimensional data space. Our tools can generate detailed HTML reports that facilitate the analysis.

Schumann, Johann↗
NASA NTRS2010

Inversion Method for Early Detection of ARES-1 Case Breach Failure

A document describes research into the problem of detecting a case breach formation at an early stage of a rocket flight. An inversion algorithm for case breach allocation is proposed and analyzed. It is shown how the case breach can be allocated at an early stage of its development by using the rocket sensor data and the output data from the control block of the rocket navigation system. The results are simulated with MATLAB/Simulink software. The efficiency of an inversion algorithm for a case breach location is discussed. The research was devoted to the analysis of the ARES-l flight during the first 120 seconds after the launch and early prediction of case breach failure. During this time, the rocket is propelled by its first-stage Solid Rocket Booster (SRB). If a breach appears in SRB case, the gases escaping through it will produce the (side) thrust directed perpendicular to the rocket axis. The side thrust creates torque influencing the rocket attitude. The ARES-l control system will compensate for the side thrust until it reaches some critical value, after which the flight will be uncontrollable. The objective of this work was to obtain the start time of case breach development and its location using the rocket inertial navigation sensors and GNC data. The algorithm was effective for the detection and location of a breach in an SRB field joint at an early stage of its development.

Mackey, Ryan M.↗
NASA NTRS2005

Instrumentation and Control Needs for Reliable Operation of Lunar Base Surface Nuclear Power Systems

As one of the near-term goals of the President's Vision for Space Exploration, establishment of a multi-person lunar base will require high-endurance power systems which are independent of the sun, and can operate without replenishment for several years. These requirements may be obtained using nuclear power systems specifically designed for use on the lunar surface. While it is envisioned that such a system will generally be supervised by humans, some of the evolutions required maybe semi or fully autonomous. The entire base complement for near-term missions may be less than 10 individuals, most or all of which may not be qualified nuclear plant operators and may be off-base for extended periods thus, the need for power system autonomous operation. Startup, shutdown, and load following operations will require the application of advanced control and health management strategies with an emphasis on robust, supervisory, coordinated control of, for example, the nuclear heat source, energy conversion plant (e.g., Brayton Energy Conversion units), and power management system. Autonomous operation implies that, in addition to being capable of automatic response to disturbance input or load changes, the system is also capable of assessing the status of the integrated plant, determining the risk associated with the possible actions, and making a decision as to the action that optimizes system performance while minimizing risk to the mission. Adapting the control to deviations from design conditions and degradation due to component failures will be essential to ensure base inhabitant safety and mission success. Intelligent decisions will have to be made to choose the right set of sensors to provide the data needed to do condition monitoring and fault detection and isolation because of liftoff weight and space limitations, it will not be possible to have an extensive set of instruments as used for earth-based systems. Advanced instrumentation and control technologies will be needed to enable this critical functionality of autonomous operation. It will be imperative to consider instrumentation and control requirements in parallel to system configuration development so as to identify control-related, as well as integrated system-related, problem areas early to avoid potentially expensive work-arounds . This paper presents an overview of the enabling technologies necessary for the development of reliable, autonomous lunar base nuclear power systems with an emphasis on system architectures and off-the-shelf algorithms rather than hardware. Autonomy needs are presented in the context of a hypothetical lunar base nuclear power system. The scenarios and applications presented are hypothetical in nature, based on information from open-literature sources, and only intended to provoke thought and provide motivation for the use of autonomous, intelligent control and diagnostics.

Turso, James↗
NASA NTRS2005

A Survey of Intelligent Control and Health Management Technologies for Aircraft Propulsion Systems

Intelligent Control and Health Management technology for aircraft propulsion systems is much more developed in the laboratory than in practice. With a renewed emphasis on reducing engine life cycle costs, improving fuel efficiency, increasing durability and life, etc., driven by various government programs, there is a strong push to move these technologies out of the laboratory and onto the engine. This paper describes the existing state of engine control and on-board health management, and surveys some specific technologies under development that will enable an aircraft propulsion system to operate in an intelligent way--defined as self-diagnostic, self-prognostic, self-optimizing, and mission adaptable. These technologies offer the potential for creating extremely safe, highly reliable systems. The technologies will help to enable a level of performance that far exceeds that of today s propulsion systems in terms of reduction of harmful emissions, maximization of fuel efficiency, and minimization of noise, while improving system affordability and safety. Technologies that are discussed include various aspects of propulsion control, diagnostics, prognostics, and their integration. The paper focuses on the improvements that can be achieved through innovative software and algorithms. It concentrates on those areas that do not require significant advances in sensors and actuators to make them achievable, while acknowledging the additional benefit that can be realized when those technologies become available. The paper also discusses issues associated with the introduction of some of the technologies.

Litt, Jonathan S.↗
NASA NTRS2005

Addressing the Real-World Challenges in the Development of Propulsion IVHM Technology Experiment (PITEX)

The Propulsion IVHM Technology Experiment (PITEX) has been an on-going research effort conducted over several years. PITEX has developed and applied a model-based diagnostic system for the main propulsion system of the X-34 reusable launch vehicle, a space-launch technology demonstrator. The application was simulation-based using detailed models of the propulsion subsystem to generate nominal and failure scenarios during captive carry, which is the most safety-critical portion of the X-34 flight. Since no system-level testing of the X-34 Main Propulsion System (MPS) was performed, these simulated data were used to verify and validate the software system. Advanced diagnostic and signal processing algorithms were developed and tested in real-time on flight-like hardware. In an attempt to expose potential performance problems, these PITEX algorithms were subject to numerous real-world effects in the simulated data including noise, sensor resolution, command/valve talkback information, and nominal build variations. The current research has demonstrated the potential benefits of model-based diagnostics, defined the performance metrics required to evaluate the diagnostic system, and studied the impact of real-world challenges encountered when monitoring propulsion subsystems.

Maul, William A.↗
NASA NTRS2004

Transient Region Coverage in the Propulsion IVHM Technology Experiment

Over the last several years researchers at NASA Glenn and Ames Research Centers have developed a real-time fault detection and isolation system for propulsion subsystems of future space vehicles. The Propulsion IVHM Technology Experiment (PITEX), as it is called follows the model-based diagnostic methodology and employs Livingstone, developed at NASA Ames, as its reasoning engine. The system has been tested on,flight-like hardware through a series of nominal and fault scenarios. These scenarios have been developed using a highly detailed simulation of the X-34 flight demonstrator main propulsion system and include realistic failures involving valves, regulators, microswitches, and sensors. This paper focuses on one of the recent research and development efforts under PITEX - to provide more complete transient region coverage. It describes the development of the transient monitors, the corresponding modeling methodology, and the interface software responsible for coordinating the flow of information between the quantitative monitors and the qualitative, discrete representation Livingstone.

Balaban, Edward↗
NASA NTRS2003

The Livingstone Model of a Main Propulsion System

Livingstone is a discrete, propositional logic-based inference engine that has been used for diagnosis of physical systems. We present a component-based model of a Main Propulsion System (MPS) and say how it is used with Livingstone (L2) in order to implement a diagnostic system for integrated vehicle health management (IVHM) for the Propulsion IVHM Technology Experiment (PITEX). We start by discussing the process of conceptualizing such a model. We describe graphical tools that facilitated the generation of the model. The model is composed of components (which map onto physical components), connections between components and constraints. A component is specified by variables, with a set of discrete, qualitative values for each variable in its local nominal and failure modes. For each mode, the model specifies the component's behavior and transitions. We describe the MPS components' nominal and fault modes and associated Livingstone variables and data structures. Given this model, and observed external commands and observations from the system, Livingstone tracks the state of the MPS over discrete time-steps by choosing trajectories that are consistent with observations. We briefly discuss how the compiled model fits into the overall PITEX architecture. Finally we summarize our modeling experience, discuss advantages and disadvantages of our approach, and suggest enhancements to the modeling process.

Bajwa, Anupa↗
NASA NTRS2003

Lessons Learned from using a Livingstone Model to Diagnose a Main Propulsion System

NASA researchers have demonstrated that qualitative, model-based reasoning can be used for fault detection in a Main Propulsion System (MPS), a complex, continuous system. At the heart of this diagnostic system is Livingstone, a discrete, propositional logic-based inference engine. Livingstone comprises a language for specifying a discrete model of the system and a set of algorithms that use the model to track the system's state. Livingstone uses the model to test assumptions about the state of a component - observations from the system are compared with values predicted by the model. The intent of this paper is to summarize some advantages of Livingstone seen through our modeling experience: for instance, flexibility in modeling, speed and maturity. We also describe some shortcomings we perceived in the implementation of Livingstone, such as modeling continuous dynamics and handling of transients. We list some upcoming enhancements to the next version of Livingstone that may resolve some of the current limitations.

Sweet, Adam↗
NASA NTRS2001

NASA IVHM Technology Experiment for X-vehicles (NITEX)

The purpose of the NASA IVHM Technology Experiment for X-vehicles (NITEX) is to advance the development of selected IVHM technologies in a flight environment and to demonstrate the potential for reusable launch vehicle ground processing savings. The technologies to be developed and demonstrated include system-level and detailed diagnostics for real-time fault detection and isolation, prognostics for fault prediction, automated maintenance planning based on diagnostic and prognostic results, and a microelectronics hardware platform. Complete flight The Evolution of Flexible Insulation as IVHM consists of advanced sensors, distributed data acquisition, data processing that includes model-based diagnostics, prognostics and vehicle autonomy for control or suggested action, and advanced data storage. Complete ground IVHM consists of evolved control room architectures, advanced applications including automated maintenance planning and automated ground support equipment. This experiment will advance the development of a subset of complete IVHM.

Sandra, Hayden↗