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At least 811 records · Page 45

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NASA NTRS1992

Evaluation of fuzzy inference systems using fuzzy least squares

Efforts to develop evaluation methods for fuzzy inference systems which are not based on crisp, quantitative data or processes (i.e., where the phenomenon the system is built to describe or control is inherently fuzzy) are just beginning. This paper suggests that the method of fuzzy least squares can be used to perform such evaluations. Regressing the desired outputs onto the inferred outputs can provide both global and local measures of success. The global measures have some value in an absolute sense, but they are particularly useful when competing solutions (e.g., different numbers of rules, different fuzzy input partitions) are being compared. The local measure described here can be used to identify specific areas of poor fit where special measures (e.g., the use of emphatic or suppressive rules) can be applied. Several examples are discussed which illustrate the applicability of the method as an evaluation tool.

Barone, Joseph M.↗

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 NTRS1992

Some problems with the design of self-learning management systems

In this paper some problems in the design of management systems for complex objects are discussed. Considering the absence of adequate models and the fact that human expertise in the management of non-stationary objects becomes obsolete quickly, the use of self-learning together with a two-step optimization of on-line control rules is suggested. To prepare for the object analysis, a set of definitions has been proposed. Traditional and fuzzy sets approaches are used in the analysis. To decrease the reaction time of the control system, we propose the development of control rules without feedback.

Flikop, Ziny↗

NASA NTRS1992

A neural fuzzy controller learning by fuzzy error propagation

In this paper, we describe a procedure to integrate techniques for the adaptation of membership functions in a linguistic variable based fuzzy control environment by using neural network learning principles. This is an extension to our work. We solve this problem by defining a fuzzy error that is propagated back through the architecture of our fuzzy controller. According to this fuzzy error and the strength of its antecedent each fuzzy rule determines its amount of error. Depending on the current state of the controlled system and the control action derived from the conclusion, each rule tunes the membership functions of its antecedent and its conclusion. By this we get an unsupervised learning technique that enables a fuzzy controller to adapt to a control task by knowing just about the global state and the fuzzy error.

Nauck, Detlef↗

NASA NTRS1992

Comparison between the performance of two classes of fuzzy controllers

This paper presents an application comparison between two classes of fuzzy controllers: the Clearness Transformation Fuzzy Controller (CTFC) and the CRI-based Fuzzy Controller. The comparison is performed by studying the application of the controllers to simulation examples of nonlinear systems. The CTFC is a new approach for the organization of fuzzy controllers based on a cognitive model of parameter driven control, the notion of fuzzy patterns to represent fuzzy knowledge and the Clearness Transformation Rule of Inference (CTRI) for approximate reasoning. The approach facilitates the implementation of the basic modules of the controller: the fuzzifier, defuzzifier, and the control protocol in a rule-based architecture. The CTRI scheme for approximate reasoning does not require the formation of fuzzy relation matrices yielding improved performance in comparison with the traditional organization of fuzzy controllers.

Janabi, T. H.↗

NASA NTRS1992

Genetic algorithms in adaptive fuzzy control

Researchers at the U.S. Bureau of Mines have developed adaptive process control systems in which genetic algorithms (GA's) are used to augment fuzzy logic controllers (FLC's). GA's are search algorithms that rapidly locate near-optimum solutions to a wide spectrum of problems by modeling the search procedures of natural genetics. FLC's are rule based systems that efficiently manipulate a problem environment by modeling the 'rule-of-thumb' strategy used in human decision making. Together, GA's and FLC's possess the capabilities necessary to produce powerful, efficient, and robust adaptive control systems. To perform efficiently, such control systems require a control element to manipulate the problem environment, an analysis element to recognize changes in the problem environment, and a learning element to adjust fuzzy membership functions in response to the changes in the problem environment. Details of an overall adaptive control system are discussed. A specific computer-simulated chemical system is used to demonstrate the ideas presented.

Karr, C. Lucas↗

NASA NTRS1993

Enhancements to the Engine Data Interpretation System (EDIS)

The Engine Data Interpretation System (EDIS) expert system project assists the data review personnel at NASA/MSFC in performing post-test data analysis and engine diagnosis of the Space Shuttle Main Engine (SSME). EDIS uses knowledge of the engine, its components, and simple thermodynamic principles instead of, and in addition to, heuristic rules gathered from the engine experts. EDIS reasons in cooperation with human experts, following roughly the pattern of logic exhibited by human experts. EDIS concentrates on steady-state static faults, such as small leaks, and component degradations, such as pump efficiencies. The objective of this contract was to complete the set of engine component models, integrate heuristic rules into EDIS, integrate the Power Balance Model into EDIS, and investigate modification of the qualitative reasoning mechanisms to allow 'fuzzy' value classification. The results of this contract is an operational version of EDIS. EDIS will become a module of the Post-Test Diagnostic System (PTDS) and will, in this context, provide system-level diagnostic capabilities which integrate component-specific findings provided by other modules.

Hofmann, Martin O.↗

NASA NTRS1991

The best-fit universe

Inflation provides very strong motivation for a flat Universe, Harrison-Zel'dovich (constant-curvature) perturbations, and cold dark matter. However, there are a number of cosmological observations that conflict with the predictions of the simplest such model: one with zero cosmological constant. They include the age of the Universe, dynamical determinations of Omega, galaxy-number counts, and the apparent abundance of large-scale structure in the Universe. While the discrepancies are not yet serious enough to rule out the simplest and most well motivated model, the current data point to a best-fit model with the following parameters: Omega(sub B) approximately equal to 0.03, Omega(sub CDM) approximately equal to 0.17, Omega(sub Lambda) approximately equal to 0.8, and H(sub 0) approximately equal to 70 km/(sec x Mpc) which improves significantly the concordance with observations. While there is no good reason to expect such a value for the cosmological constant, there is no physical principle that would rule out such.

Turner, Michael S.↗

NASA NTRS1992

Enhancements to the Design Manager's Aide for Intelligent Decomposition (DeMAID)

This paper discusses the addition of two new enhancements to the program Design Manager's Aide for Intelligent Decomposition (DeMAID). DeMAID is a knowledge-based tool used to aid a design manager in understanding the interactions among the tasks of a complex design problem. This is done by ordering the tasks to minimize feedback, determining the participating subsystems, and displaying them in an easily understood format. The two new enhancements include (1) rules for ordering a complex assembly process and (2) rules for determining which analysis tasks must be re-executed to compute the output of one task based on a change in input to that or another task.

Rogers, James L.↗

NASA NTRS1993

High-cycle fatigue characterization of titanium 5Al-2.5Sn alloy

High-cycle fatigue behavior of titanium 5Al 2.5Sn alloy at room temperature has been studied. S-N curve characterization is performed at different stress ratios ranging from 0 to 0.9 on a subsized fatigue specimen. Both two-stress and three-stress level tests are conducted at different stress ratios to study the cumulative fatigue damage. Life prediction techniques of linear damage rule, double linear damage rule and damage curve approaches are applied, and results are compared with the experimental data. The agreement between prediction and experiment is found to be excellent.

Mahfuz, H.↗

NASA NTRS1992

Self-learning fuzzy controllers based on temporal back propagation

This paper presents a generalized control strategy that enhances fuzzy controllers with self-learning capability for achieving prescribed control objectives in a near-optimal manner. This methodology, termed temporal back propagation, is model-insensitive in the sense that it can deal with plants that can be represented in a piecewise-differentiable format, such as difference equations, neural networks, GMDH structures, and fuzzy models. Regardless of the numbers of inputs and outputs of the plants under consideration, the proposed approach can either refine the fuzzy if-then rules if human experts, or automatically derive the fuzzy if-then rules obtained from human experts are not available. The inverted pendulum system is employed as a test-bed to demonstrate the effectiveness of the proposed control scheme and the robustness of the acquired fuzzy controller.

Jang, Jyh-Shing R.↗

NASA NTRS1992

Expert systems for automated maintenance of a Mars oxygen production system

Application of expert system concepts to a breadboard Mars oxygen processor unit have been studied and tested. The research was directed toward developing the methodology required to enable autonomous operation and control of these simple chemical processors at Mars. Failure detection and isolation was the key area of concern, and schemes using forward chaining, backward chaining, knowledge-based expert systems, and rule-based expert systems were examined. Tests and simulations were conducted that investigated self-health checkout, emergency shutdown, and fault detection, in addition to normal control activities. A dynamic system model was developed using the Bond-Graph technique. The dynamic model agreed well with tests involving sudden reductions in throughput. However, nonlinear effects were observed during tests that incorporated step function increases in flow variables. Computer simulations and experiments have demonstrated the feasibility of expert systems utilizing rule-based diagnosis and decision-making algorithms.

Huang, Jen-Kuang↗

NASA NTRS1991

An implicit method for the nonlinear modelling and simulation of piezoceramic actuators displaying hysteresis

Experiments have shown that piezoceramic materials display a nonlinear relationship between the applied electric field and the actuation strain. This relationship also displays a substantial hysteresis upon reversal of the applied field. In this paper, piezoceramic actuator models are incorporated into the structural equations of motion to arrive at a set of nonlinear actively controlled structural equations of motion. A new implicit algorithm for determining the time history of the actively controlled structure is presented. The algorithm employs the trapezoidal rule for stepping the equations forward in time. The algorithm is compared to an explicit algorithm and is shown to provide greater numerical accuracy. In addition, the numerical stability and convergence characteristics are presented via example. The new algorithm displays convergence and stability properties that are comparable to the standard trapezoidal rule used for dynamic systems without hysteresis.

Leigh, Timothy D.↗

NASA NTRS1993

The use of linked lists in the simulation of controller-structure interaction

An algorithm for the computer simulation of large space structures under active control is considered. Linked lists are used in a matrix data structure to implement the trapezoidal rule on system differential equations. The use of the trapezoidal rule ensures that the numerical stability is equivalent to the system stability, which is essential for this type of simulation. The sparsity of the system matrices is exploited by the linked lists, and the algorithm efficiently steps through the lists in an orderly fashion. Results of simulations on a NASA large space structure experiment are reported.

Quan, R.↗

NASA NTRS1992

Decision fusion with reliabilities in multisource data classification

In this paper, a new multisource classifier which is based on a fusion of the class decisions of each separate data set is proposed. Each data set is separately fed into the local classifier and a final classification is performed by summarizing these local class decisions. An optimum decision fusion rule based on the minimum expected cost is derived. This new decision fusion rule can handle not only data set reliabilities but also classwise reliabilities of each data set. Classification experiments with two remotely sensed Thematic Mapper (TM) data sets show promising improvement over conventional multisource classification algorithms.

Jeon, Byeungwoo↗

NASA NTRS1993

WNN 92; Proceedings of the 3rd Workshop on Neural Networks: Academic/Industrial/NASA/Defense, Auburn Univ., AL, Feb. 10-12, 1992 and South Shore Harbour, TX, Nov. 4-6, 1992

The present conference discusses such neural networks (NN) related topics as their current development status, NN architectures, NN learning rules, NN optimization methods, NN temporal models, NN control methods, NN pattern recognition systems and applications, biological and biomedical applications of NNs, VLSI design techniques for NNs, NN systems simulation, fuzzy logic, and genetic algorithms. Attention is given to missileborne integrated NNs, adaptive-mixture NNs, implementable learning rules, an NN simulator for travelling salesman problem solutions, similarity-based forecasting, NN control of hypersonic aircraft takeoff, NN control of the Space Shuttle Arm, an adaptive NN robot manipulator controller, a synthetic approach to digital filtering, NNs for speech analysis, adaptive spline networks, an anticipatory fuzzy logic controller, and encoding operations for fuzzy associative memories.

Padgett, Mary L.↗

NASA NTRS1993

A simple fuzzy logic real-time camera tracking system

A fuzzy logic control of camera pan and tilt has been implemented to provide real-time camera tracking of a moving object. The user clicks a mouse button to identify the object that is to be tracked. A rapid centroid estimation algorithm is used to estimate the location of the moving object, and based on simple fuzzy membership functions, fuzzy x and y values are input into a six-rule fuzzy logic rule base. The output of this system is de-fuzzified to provide pan and tilt velocities required to keep the image of the object approximately centered in the camera field of view.

Magee, Kevin N.↗

NASA NTRS1921

The Choice of Wing Sections for Airplanes

The subject of the choice of an airfoil section is by no means a closed one, and despite the impossibility of making a single rule serve, it is quite practicable to deduce in a strictly rational manner a series of rules and formulas which are capable of being of the greatest use if we but confine ourselves to the consideration of one element of performance at a time. There are seven such elements of performance which are here taken up in turn. The seven are of different relative importance in different types of airplanes. The seven elements are: maximum speed regardless of minimum; maximum speed for given minimum; maximum speed range ratio; maximum rate of climb; maximum absolute ceiling; maximum distance non-stop; and maximum duration non-stop.

Warner, Edward P↗