Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “intelligent control”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
NASA NTRS2006

Lessons Learned and Flight Results from the F15 Intelligent Flight Control System Project

A viewgraph presentation on the lessons learned and flight results from the F15 Intelligent Flight Control System (IFCS) project is shown. The topics include: 1) F-15 IFCS Project Goals; 2) Motivation; 3) IFCS Approach; 4) NASA F-15 #837 Aircraft Description; 5) Flight Envelope; 6) Limited Authority System; 7) NN Floating Limiter; 8) Flight Experiment; 9) Adaptation Goals; 10) Handling Qualities Performance Metric; 11) Project Phases; 12) Indirect Adaptive Control Architecture; 13) Indirect Adaptive Experience and Lessons Learned; 14) Gen II Direct Adaptive Control Architecture; 15) Current Status; 16) Effect of Canard Multiplier; 17) Simulated Canard Failure Stab Open Loop; 18) Canard Multiplier Effect Closed Loop Freq. Resp.; 19) Simulated Canard Failure Stab Open Loop with Adaptation; 20) Canard Multiplier Effect Closed Loop with Adaptation; 21) Gen 2 NN Wts from Simulation; 22) Direct Adaptive Experience and Lessons Learned; and 23) Conclusions

Bosworth, John↗
NASA NTRS1984

An intelligent robotics control scheme

The problem of robot control is viewed at the level of communicating high-level commands produced by intelligent algorithms to the actuator/sensor controllers. Four topics are considered in the design of an integrated control and communications scheme for an intelligent robotic system: the use of abstraction spaces, hierarchical versus heterarchical control, distributed processing, and the interleaving of the steps of plan creation and plan execution. A scheme is presented for an n-level distributed hierarchical/heterarchical control system that effectively interleaves intelligent planning, execution, and sensory feedback. A three-level version of this scheme has been successfully implemented in the Intelligent Systems Research Lab at NASA Langley Research Center. This implementation forms the control structure for DAISIE (Distributed Artificially Intelligent System for Interacting with the Environment), a testbed system integrating AI software with robotics hardware.

Orlando, N. E.↗
NASA NTRS1991

Transportation technology: Earth-to-orbit propulsion

The topics presented are covered in viewgraph form and include the following: (1) sensor autodiagnosis and autocalibration; (2) autodiagnostic and autocalibration program; (3) plume diagnostics; (4) plume diagnostics program; (5) failure modeling; (6) mass data storage and retrieval; (7) fiber optic instrumentation bus; (8) model based diagnostics; (9) safety monitoring system (SMS); (10) control and real time diagnostics; (11) current intelligent controls program; (12) augumented intelligent controls program; (13) current real time diagnostics program; (14) augumented RT diagnostics program; and (15) control and diagnostic system hardware.

Gorland, S.↗
NASA NTRS1992

Intelligent fuzzy controller for event-driven real time systems

Most of the known linguistic models are essentially static, that is, time is not a parameter in describing the behavior of the object's model. In this paper we show a model for synchronous finite state machines based on fuzzy logic. Such finite state machines can be used to build both event-driven, time-varying, rule-based systems and the control unit section of a fuzzy logic computer. The architecture of a pipelined intelligent fuzzy controller is presented, and the linguistic model is represented by an overall fuzzy relation stored in a single rule memory. A VLSI integrated circuit implementation of the fuzzy controller is suggested. At a clock rate of 30 MHz, the controller can perform 3 MFLIPS on multi-dimensional fuzzy data.

Grantner, Janos↗
NASA NTRS2003

An Adaptive Critic Approach to Reference Model Adaptation

Neural networks have been successfully used for implementing control architectures for different applications. In this work, we examine a neural network augmented adaptive critic as a Level 2 intelligent controller for a C- 17 aircraft. This intelligent control architecture utilizes an adaptive critic to tune the parameters of a reference model, which is then used to define the angular rate command for a Level 1 intelligent controller. The present architecture is implemented on a high-fidelity non-linear model of a C-17 aircraft. The goal of this research is to improve the performance of the C-17 under degraded conditions such as control failures and battle damage. Pilot ratings using a motion based simulation facility are included in this paper. The benefits of using an adaptive critic are documented using time response comparisons for severe damage situations.

Krishnakumar, K.↗
NASA NTRS2004

The Intelligent Flight Control Program (IFCS)

This is the closeout report for the Research Cooperative Agreement NCC4-00130 of accomplishments for the Intelligent Flight Control System (IFCS) Project. It has been a pleasure working with NASA and NASA partners as we strive to meet the goals of this research initiative. ISR was engaged in this Research Cooperative Agreement beginning 01 January 2003 and ending 31 January 2004. During this time ISR conducted efforts towards development of the ARTS II Computer Software Configuration Item (CSCI) version 4.0 by performing or developing the following: 1) Requirements Definition; 2) Software Design and Development; 3) Hardware In the Loop Simulation; 4) Unit Level testing; 5) Documentation.

Source record↗
NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
NASA NTRS2007

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
NASA NTRS2008

Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

Bosworth, John T.↗
NASA NTRS2010

Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

Bosworth, John T.↗
NASA NTRS2009

The Case for Intelligent Propulsion Control for Fast Engine Response

Damaged aircraft have occasionally had to rely solely on thrust to maneuver as a consequence of losing hydraulic power needed to operate flight control surfaces. The lack of successful landings in these cases inspired research into more effective methods of utilizing propulsion-only control. That research demonstrated that one of the major contributors to the difficulty in landing is the slow response of the engines as compared to using traditional flight control. To address this, research is being conducted into ways of making the engine more responsive under emergency conditions. This can be achieved by relaxing controller limits, adjusting schedules, and/or redesigning the regulators to increase bandwidth. Any of these methods can enable faster response at the potential expense of engine life and increased likelihood of stall. However, an example sensitivity analysis revealed a complex interaction of the limits and the difficulty in predicting the way to achieve the fastest response. The sensitivity analysis was performed on a realistic engine model, and demonstrated that significantly faster engine response can be achieved compared to standard Bill of Material control. However, the example indicates the need for an intelligent approach to controller limit adjustment in order for the potential to be fulfilled.

Litt, Jonathan S.↗
NASA NTRS2003

The Intelligent Flight Control Program (IFCS)

Institute for Scientific Research, Inc. (ISR) is pleased to submit this closeout report for the Research Cooperative Agreement NCC4-00128 of accomplishments for the Intelligent Flight Control System (IFCS) Project. It has been a pleasure working with NASA and NASA partners as we strive to meet the goals of this research initiative. ISR was engaged in this Research Cooperative Agreement beginning March 3, 2001 and ending March 31, 2003. During this time, a great deal has been accomplished and plans have been solidified for the continued success of this program. Our primary areas of involvement include the following: 1) ARTS II Master Test Plan; 2) ARTS II Hardware Design and Development; 3) ARTS II Software Design and Development; 4) IFCS PID/BLNN/OLNN Development; 5) Performed Preliminary and Formal Testing; 6) Documentation and Reporting.

Source record↗
NASA NTRS1993

A neural based intelligent flight control system for the NASA F-15 flight research aircraft

A flight control concept that can identify aircraft stability properties and continually optimize the aircraft flying qualities has been developed by McDonnell Aircraft Company under a contract with the NASA-Dryden Flight Research Facility. This flight concept, termed the Intelligent Flight Control System, utilizes Neural Network technology to identify the host aircraft stability and control properties during flight, and use this information to design on-line the control system feedback gains to provide continuous optimum flight response. This self-repairing capability can provide high performance flight maneuvering response throughout large flight envelopes, such as needed for the National Aerospace Plane. Moreover, achieving this response early in the vehicle's development schedule will save cost.

Urnes, James M.↗
NASA NTRS1990

Intelligent pipelined control architecture for remote robotic applications

A new pipelined architecture for autonomous and semiautonomous space robotics systems is described. The architecture uses new concepts which significantly facilitate the overall system performance and leads to an effective functional partitioning between base and remote parts of the system. The base system which is based on a set of parameterized primitives, provides detailed planning and the remote site provides final command binding and resource management. The primitives are then directed to the intelligent manipulation controllers that perform the required manipulation. A proof-of-principle implementation at the JPL Telerobotic laboratory demonstrated the practical efficiency of the pipelined architecture in the context of supervised autonomous robotics operations.

Lokshin, A.↗
NASA NTRS2007

Telerobotic Surgery: An Intelligent Systems Approach to Mitigate the Adverse Effects of Communication Delay

An extremely innovative approach has been presented, which is to have the surgeon operate through a simulator running in real-time enhanced with an intelligent controller component to enhance the safety and efficiency of a remotely conducted operation. The use of a simulator enables the surgeon to operate in a virtual environment free from the impediments of telecommunication delay. The simulator functions as a predictor and periodically the simulator state is corrected with truth data. Three major research areas must be explored in order to ensure achieving the objectives. They are: simulator as predictor, image processing, and intelligent control. Each is equally necessary for success of the project and each of these involves a significant intelligent component in it. These are diverse, interdisciplinary areas of investigation, thereby requiring a highly coordinated effort by all the members of our team, to ensure an integrated system. The following is a brief discussion of those areas. Simulator as a predictor: The delays encountered in remote robotic surgery will be greater than any encountered in human-machine systems analysis, with the possible exception of remote operations in space. Therefore, novel compensation techniques will be developed. Included will be the development of the real-time simulator, which is at the heart of our approach. The simulator will present real-time, stereoscopic images and artificial haptic stimuli to the surgeon. Image processing: Because of the delay and the possibility of insufficient bandwidth a high level of novel image processing is necessary. This image processing will include several innovative aspects, including image interpretation, video to graphical conversion, texture extraction, geometric processing, image compression and image generation at the surgeon station. Intelligent control: Since the approach we propose is in a sense predictor based, albeit a very sophisticated predictor, a controller, which not only optimizes end effector trajectory but also avoids error, is essential. We propose to investigate two different approaches to the controller design. One approach employs an optimal controller based on modern control theory; the other one involves soft computing techniques, i.e. fuzzy logic, neural networks, genetic algorithms and hybrids of these.

Cardullo, Frank M.↗
NASA NTRS2002

Using CONFIG for Simulation of Operation of Water Recovery Subsystems for Advanced Control Software Evaluation

A hybrid discrete/continuous simulation tool, CONFIG, has been developed to support evaluation of the operability life support systems. CON FIG simulates operations scenarios in which flows and pressures change continuously while system reconfigurations occur as discrete events. In simulations, intelligent control software can interact dynamically with hardware system models. CONFIG simulations have been used to evaluate control software and intelligent agents for automating life support systems operations. A CON FIG model of an advanced biological water recovery system has been developed to interact with intelligent control software that is being used in a water system test at NASA Johnson Space Center

Malin, Jane T.↗
NASA NTRS1989

Applications of graphics to support a testbed for autonomous space vehicle operations

Researchers describe their experience using graphics tools and utilities while building an application, AUTOPS, that uses a graphical Machintosh (TM)-like interface for the input and display of data, and animation graphics to enhance the presentation of results of autonomous space vehicle operations simulations. AUTOPS is a test bed for evaluating decisions for intelligent control systems for autonomous vehicles. Decisions made by an intelligent control system, e.g., a revised mission plan, might be displayed to the user in textual format or he can witness the effects of those decisions via out of window graphics animations. Although a textual description conveys essentials, a graphics animation conveys the replanning results in a more convincing way. Similarily, iconic and menu-driven screen interfaces provide the user with more meaningful options and displays. Presented here are experiences with the SunView and TAE Plus graphics tools used for interface design, and the Johnson Space Center Interactive Graphics Laboratory animation graphics tools used for generating out out of the window graphics.

Schmeckpeper, K. R.↗
NASA NTRS1991

Architectures for intelligent machines

The theory of intelligent machines has been recently reformulated to incorporate new architectures that are using neural and Petri nets. The analytic functions of an intelligent machine are implemented by intelligent controls, using entropy as a measure. The resulting hierarchical control structure is based on the principle of increasing precision with decreasing intelligence. Each of the three levels of the intelligent control is using different architectures, in order to satisfy the requirements of the principle: the organization level is moduled after a Boltzmann machine for abstract reasoning, task planning and decision making; the coordination level is composed of a number of Petri net transducers supervised, for command exchange, by a dispatcher, which also serves as an interface to the organization level; the execution level, include the sensory, planning for navigation and control hardware which interacts one-to-one with the appropriate coordinators, while a VME bus provides a channel for database exchange among the several devices. This system is currently implemented on a robotic transporter, designed for space construction at the CIRSSE laboratories at the Rensselaer Polytechnic Institute. The progress of its development is reported.

Saridis, George N.↗