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At least 19 records

The Use of Software Agents for Autonomous Control of a DC Space Power System

In order to enable manned deep-space missions, the spacecraft must be controlled autonomously using on-board algorithms. A control architecture is proposed to enable this autonomous operation for an spacecraft electric power system and then implemented using a highly distributed network of software agents. These agents collaborate and compete with each other in order to implement each of the control functions. A subset of this control architecture is tested against a steadystate power system simulation and found to be able to solve a constrained optimization problem with competing objectives using only local information.

autonomous control

A Risk-Informed Approach to Trustworthiness Assessment in Digital Twins-Based Autonomous Control

In autonomous control systems, digital twins (DTs) are used to perform diagnostic and prognostic functions. The trustworthiness of these DTs is dependent on quality and coverage of the training data, model accuracy and integrity of sensor data. This work introduces a methodology to determine the trustworthiness of a DT system given faulty sensor data using a risk informed approach. Bayesian Belief Networks (BBNs) are used to propagate uncertainties and determine the probability of trustable recommendations. The decision to trust the control action provided by the DT is based on the DT output, expert opinion, and severity of problems. The performance of DTs is reliant on the data they are trained on. When they encounter out of distribution data, the trustworthiness of the recommendations decreases. To address this issue, we include an expert component that provides input on sensor degradation. For this, we utilize a generative artificial intelligence (AI) model, such as Generative Pretrained Transformer (GPT). The GPT functions as an expert with broad knowledge. The GPT is fine-tuned to understand and discriminate sensor degradation scenarios using manufactured data. This methodology is demonstrated through a case study on a Nearly Autonomous Management and Control System (NAMAC) during a steady state scenario. Various sensor degradation types with different severity levels are considered. Degraded sensor data is processed by the DT system and the fine-tuned GPT. Finally, using the BBN, we combine the GPT information and the DT output with its sources of uncertainty. This provides an output regarding the trustworthiness of the DT recommendation.

22 - GENERAL STUDIES OF NUCLEAR REACTORS

Development of a Commercially Viable, Modular Autonomous Robotic Systems for Converting any Vehicle to Autonomous Control

A Modular Autonomous Robotic System (MARS), consisting of a modular autonomous vehicle control system that can be retrofit on to any vehicle to convert it to autonomous control and support a modular payload for multiple applications is being developed. The MARS design is scalable, reconfigurable, and cost effective due to the use of modern open system architecture design methodologies, including serial control bus technology to simplify system wiring and enhance scalability. The design is augmented with modular, object oriented (C++) software implementing a hierarchy of five levels of control including teleoperated, continuous guidepath following, periodic guidepath following, absolute position autonomous navigation, and relative position autonomous navigation. The present effort is focused on producing a system that is commercially viable for routine autonomous patrolling of known, semistructured environments, like environmental monitoring of chemical and petroleum refineries, exterior physical security and surveillance, perimeter patrolling, and intrafacility transport applications.

guidepath position navigation control system

The MDS autonomous control architecture

We describe the autonomous control architecture for the JPL Mission Data System (MDS). MDS is a comprehensive new software infrastructure for supporting unmanned space exploration. The autonomous control architecture is one component of MDS designed to enable autonomous operations.

MDS autonomous control unmanned space exploration

An introduction to autonomous control systems

The functions, characteristics, and benefits of autonomous control are outlined. An autonomous control functional architecture for future space vehicles that incorporates the concepts and characteristics described is presented. The controller is hierarchical, with an execution level (the lowest level), coordination level (middle level), and management and organization level (highest level). The general characteristics of the overall architecture, including those of the three levels, are explained, and an example to illustrate their functions is given. Mathematical models for autonomous systems, including 'logical' discrete event system models, are discussed. An approach to the quantitative, systematic modeling, analysis, and design of autonomous controllers is also discussed. It is a hybrid approach since it uses conventional analysis techniques based on difference and differential equations and new techniques for the analysis of the systems described with a symbolic formalism such as finite automata. Some recent results from the areas of planning and expert systems, machine learning, artificial neural networks, and the area restructurable controls are briefly outlined.

Antsaklis, Panos J.

Robust control of multi-jointed arm with a decentralized autonomous control mechanism

A decentralized autonomous control mechanism applied to the control of three dimensional manipulators and its robustness to partial damage was assessed by computer simulation. Decentralized control structures are believed to be quite robust to time delay between the operator and the target system. A 10-jointed manipulator based on our control mechanism was able to continue its positioning task in three-dimensional space without revision of the control program, even after some of its joints were damaged. These results suggest that this control mechanism can be effectively applied to space telerobots, which are associated with serious time delay between the operator and the target system, and which cannot be easily repaired after being partially damaged.

Kimura, Shinichi

Integrated System for Health Management and Autonomous Control (ISHM-AC): Development and Application

Autonomous control systems represent a technological barrier from manual and automated operated control systems in an industry wide application. An increase in energy-efficient storage, transfer and use of cryogens and cryogenic propellants on Earth and in space has been observed in space related industries between NASA, government and commercial programs. An increase in efficiency of cryogenic systems demands an increase in the capabilities of the control and monitoring system that manages them. As new technologies are developed for cryogenic systems, complexity and capability increases. The increase in complexities are a natural drive to develop better and more capable health monitoring and control system management. Current research and development efforts lead the Cryogenics Test Laboratory at the Kennedy Space Center to improve its automated control and health monitoring system from a Programmable Logic Control (PLC) based-only system to a fully Integrated System for Health Management (ISHM) - Autonomous Control (AC) capable of performing autonomous operations on a cryogenic propellant transfer system. This ISHM-AC system has been developed and tested by controlling a complete simulated propellant transfer operation. The capabilities and test results of this fully integrated autonomous system for cryogenics propellant transfer operation will be presented in this paper.

Toro, Jaime A.

Ground Operations Autonomous Control and Integrated Health Management

An intelligent autonomous control capability has been developed and is currently being validated in ground cryogenic fluid management operations. The capability embodies a physical architecture consistent with typical launch infrastructure and control systems, augmented by a higher level autonomous control (AC) system enabled to make knowledge-based decisions. The AC system is supported by an integrated system health management (ISHM) capability that detects anomalies, diagnoses causes, determines effects, and could predict future anomalies. AC is implemented using the concept of programmed sequences that could be considered to be building blocks of more generic mission plans. A sequence is a series of steps, and each executes actions once conditions for the step are met (e.g. desired temperatures or fluid state are achieved). For autonomous capability, conditions must consider also health management outcomes, as they will determine whether or not an action is executed, or how an action may be executed, or if an alternative action is executed instead. Aside from health, higher level objectives can also drive how a mission is carried out. The capability was developed using the G2 software environment (www.gensym.com) augmented by a NASA Toolkit that significantly shortens time to deployment. G2 is a commercial product to develop intelligent applications. It is fully object oriented. The core of the capability is a Domain Model of the system where all elements of the system are represented as objects (sensors, instruments, components, pipes, etc.). Reasoning and decision making can be done with all elements in the domain model. The toolkit also enables implementation of failure modes and effects analysis (FMEA), which are represented as root cause trees. FMEA's are programmed graphically, they are reusable, as they address generic FMEA referring to classes of subsystems or objects and their functional relationships. User interfaces for integrated awareness by operators have been created.

Figueroa, Fernando

Autonomous control systems - Architecture and fundamental issues

A hierarchical functional autonomous controller architecture is introduced. In particular, the architecture for the control of future space vehicles is described in detail; it is designed to ensure the autonomous operation of the control system and it allows interaction with the pilot and crew/ground station, and the systems on board the autonomous vehicle. The fundamental issues in autonomous control system modeling and analysis are discussed. It is proposed to utilize a hybrid approach to modeling and analysis of autonomous systems. This will incorporate conventional control methods based on differential equations and techniques for the analysis of systems described with a symbolic formalism. In this way, the theory of conventional control can be fully utilized. It is stressed that autonomy is the design requirement and intelligent control methods appear at present, to offer some of the necessary tools to achieve autonomy. A conventional approach may evolve and replace some or all of the `intelligent' functions. It is shown that in addition to conventional controllers, the autonomous control system incorporates planning, learning, and FDI (fault detection and identification).

Antsaklis, P. J.

Development of Predictive Models for Advanced Reactor Autonomous Control

Advanced reactor designs including microreactors and small modular reactors will contribute to the clean production of cheap energy, and autonomous control for advanced reactors is an appealing option for reducing cost. However, there is a lack of industry experience applying autonomous control for advanced nuclear reactors. To accelerate the development and industry acceptance of autonomous control software for nuclear reactors, we aim to demonstrate autonomous control of the Purdue University research reactor (PUR-1) using INL-developed model predictive control (MPC) methods. To prepare for this demonstration, data-driven predictive models based on process data collected from PUR-1 have been developed and integrated with MPC and used to control a physics-based model of PUR-1. A data-driven dynamics model and a gated recurrent unit (GRU) network were both trained on process data from PUR-1. The dynamics model was shown to effectively control the reactor model with MPC when provided reactivity as a control variable but failed to control the model through the control rod positions. The GRU network produced more accurate predictions than the dynamics model when evaluated on operational data, and future work will include the evaluation of the GRU network in the controller.

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Ground Operations Autonomous Control and Integrated Health Management

The Ground Operations Autonomous Control and Integrated Health Management plays a key role for future ground operations at NASA. The software that is integrated into this system is called G2 2011 Gensym. The purpose of this report is to describe the Ground Operations Autonomous Control and Integrated Health Management with the use of the G2 Gensym software and the G2 NASA toolkit for Integrated System Health Management (ISHM) which is a Computer Software Configuration Item (CSCI). The decision rationale for the use of the G2 platform is to develop a modular capability for ISHM and AC. Toolkit modules include knowledge bases that are generic and can be applied in any application domain module. That way, there's a maximization of reusability, maintainability, and systematic evolution, portability, and scalability. Engine modules are generic, while application modules represent the domain model of a specific application. Furthermore, the NASA toolkit, developed since 2006 (a set of modules), makes it possible to create application domain models quickly, using pre-defined objects that include sensors and components libraries for typical fluid, electrical, and mechanical systems.

Computer Programs

Experiments in teleoperator and autonomous control of space robotic vehicles

A research program and strategy are described which include fundamental teleoperation issues and autonomous-control issues of sensing and navigation for satellite robots. The program consists of developing interfaces for visual operation and studying the consequences of interface designs as well as developing navigation and control technologies based on visual interaction. A space-robot-vehicle simulator is under development for use in virtual-environment teleoperation experiments and neutral-buoyancy investigations. These technologies can be utilized in a study of visual interfaces to address tradeoffs between head-tracking and manual remote cameras, panel-mounted and helmet-mounted displays, and stereoscopic and monoscopic display systems. The present program can provide significant data for the development of control experiments for autonomously controlled satellite robots.

Alexander, Harold L.

Integrated System for Health Management and Autonomous Control (ISHM-AC) for Cryogenic Operations on the Simulated Propellant Loading System

Autonomous control systems represent a technological barrier from manual and automated operated control systems in an industry wide application. An increase in energy-efficient storage, transfer and use of cryogens and cryogenic propellants on Earth and in space has been observed in space related industries between NASA, government and commercial programs. An increase in efficiency of cryogenic systems demands an increase in the capabilities of the control and monitoring system that manages them. As new technologies are developed for cryogenic systems, complexity and capability increases. The increase in complexities are a natural drive to develop better and more capable health monitoring and control system management. Current research and development efforts lead the Cryogenics Test Laboratory at the Kennedy Space Center to improve its automated control and health monitoring system from a Programmable Logic Control (PLC) based-only system to a fully Integrated System for Health Management (ISHM) - Autonomous Control (AC) capable of performing autonomous operations on a cryogenic propellant transfer system. This ISHM-AC system has been developed and tested by controlling a complete simulated propellant transfer operation. The capabilities and test results of this fully integrated autonomous system for cryogenics propellant transfer operation will be presented in this paper.

Toro Medina, Jaime A.

The relationship of motion sickness susceptibility to learned autonomic control for symptom suppression

Twenty-four men were randomly assigned to four equal groups matched in terms of their Coriolis Sickness Susceptibility Index (CSSI). Two groups of subjects were highly susceptible to motion sickness, and two groups were moderately susceptible. All subjects were given six C551 tests at 5-d intervals. Treatment Groups I (highly susceptible) and II (moderately susceptible) were taught to control their autonomic responses, using a training method called autogenic-feedback training (AFT) before the third, fourth, and fifth CSSI tests. Control groups III (highly susceptible) and IV (moderately susceptible) received no treatment. Results showed that both treatment groups significantly improved performance on CSSI tests after training; neither of the control groups changed significantly. Highly and moderately susceptible subjects in the two treatment groups improved at comparable rates. Highly susceptible control group subjects did not habituate across tests as readily as the moderately susceptible controls.

Cowings, P. S.

Autonomous-Control Concept For Instrument Pointing System

Integrated payload articulation and identification system (IPAIDS) is conceptual system to control aiming of instruments aboard spacecraft of proposed Earth Observation System (EOS). Principal features of concept include advanced control strategies intended to assure robustness of performance over wide range of uncertainties in characteristics of spacecraft and instrument system. Intended originally for application to spacecraft system, has potential utility on Earth for automatic control of autonomous (robotic) vehicles or of remote sensing systems.

Mettler, Edward

G2 Autonomous Control for Cryogenic Delivery Systems

The Independent System Health Management-Autonomous Control (ISHM-AC) application development for cryogenic delivery systems is intended to create an expert system that will require minimal operator involvement and ultimately allow for complete autonomy when fueling a space vehicle in the time prior to launch. The G2-Autonomous Control project is the development of a model, simulation, and ultimately a working application that will control and monitor the cryogenic fluid delivery to a rocket for testing purposes. To develop this application, the project is using the programming language/environment Gensym G2. The environment is an all-inclusive application that allows development, testing, modeling, and finally operation of the unique application through graphical and programmatic methods. We have learned G2 through training classes and subsequent application development, and are now in the process of building the application that will soon be used to test on cryogenic loading equipment here at the Kennedy Space Center Cryogenics Test Laboratory (CTL). The G2 ISHM-AC application will bring with it a safer and more efficient propellant loading system for the future launches at Kennedy Space Center and eventually mobile launches from all over the world.

cryogenic fluids

Intelligent Surrogate Model Development: Boosting Computational Efficiency for Autonomous Control of Advanced Reactors

Advanced reactors promise enhanced safety, greater efficiency, and waste reductions. To fully realize these benefits, it is crucial to address the need for autonomous or semi-autonomous control systems that require fewer operators. This research primarily supports the MARVEL autonomous control system, which requires real-time operation. However, the current RELAP5 reactor thermal hydraulic transient simulation is excessively time-consuming. Therefore, this study aims to leverage deep learning techniques to develop a surrogate model, providing a more efficient and accurate alternative for real-time performance. The model was trained using a combination of one-timestep prediction and scheduled sampling. It was then used for recursive prediction of the reactor state. This developed surrogate model significantly improves computational efficiency, achieving a 12 times acceleration.

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