Formalized control logic fault definition with ontological reasoning for air handling units
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Lei, Xuechen↗
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Fail-safe numerical control
System provides duplicate set of control logic circuitry. Comparators insure that the same data is present in both circuits. If any discrepancy is found, the machine is automatically stopped, before damage can occur.
Thompson, G. A.↗
Design and implementation of fuzzy logic controllers
The main objectives of our research are to present a self-contained overview of fuzzy sets and fuzzy logic, develop a methodology for control system design using fuzzy logic controllers, and to design and implement a fuzzy logic controller for a real system. We first present the fundamental concepts of fuzzy sets and fuzzy logic. Fuzzy sets and basic fuzzy operations are defined. In addition, for control systems, it is important to understand the concepts of linguistic values, term sets, fuzzy rule base, inference methods, and defuzzification methods. Second, we introduce a four-step fuzzy logic control system design procedure. The design procedure is illustrated via four examples, showing the capabilities and robustness of fuzzy logic control systems. This is followed by a tuning procedure that we developed from our design experience. Third, we present two Lyapunov based techniques for stability analysis. Finally, we present our design and implementation of a fuzzy logic controller for a linear actuator to be used to control the direction of the Free Flight Rotorcraft Research Vehicle at LaRC.
Abihana, Osama A.↗
Pilot control through the TAFCOS automatic flight control system
The set of flight control logic used in a recently completed flight test program to evaluate the total automatic flight control system (TAFCOS) with the controller operating in a fully automatic mode, was used to perform an unmanned simulation on an IBM 360 computer in which the TAFCOS concept was extended to provide a multilevel pilot interface. A pilot TAFCOS interface for direct pilot control by use of a velocity-control-wheel-steering mode was defined as well as a means for calling up conventional autopilot modes. It is concluded that the TAFCOS structure is easily adaptable to the addition of a pilot control through a stick-wheel-throttle control similar to conventional airplane controls. Conventional autopilot modes, such as airspeed-hold, altitude-hold, heading-hold, and flight path angle-hold, can also be included.
Wehrend, W. R., Jr.↗
Learning fuzzy logic control system
The performance of the Learning Fuzzy Logic Control System (LFLCS), developed in this thesis, has been evaluated. The Learning Fuzzy Logic Controller (LFLC) learns to control the motor by learning the set of teaching values that are generated by a classical PI controller. It is assumed that the classical PI controller is tuned to minimize the error of a position control system of the D.C. motor. The Learning Fuzzy Logic Controller developed in this thesis is a multi-input single-output network. Training of the Learning Fuzzy Logic Controller is implemented off-line. Upon completion of the training process (using Supervised Learning, and Unsupervised Learning), the LFLC replaces the classical PI controller. In this thesis, a closed loop position control system of a D.C. motor using the LFLC is implemented. The primary focus is on the learning capabilities of the Learning Fuzzy Logic Controller. The learning includes symbolic representation of the Input Linguistic Nodes set and Output Linguistic Notes set. In addition, we investigate the knowledge-based representation for the network. As part of the design process, we implement a digital computer simulation of the LFLCS. The computer simulation program is written in 'C' computer language, and it is implemented in DOS platform. The LFLCS, designed in this thesis, has been developed on a IBM compatible 486-DX2 66 computer. First, the performance of the Learning Fuzzy Logic Controller is evaluated by comparing the angular shaft position of the D.C. motor controlled by a conventional PI controller and that controlled by the LFLC. Second, the symbolic representation of the LFLC and the knowledge-based representation for the network are investigated by observing the parameters of the Fuzzy Logic membership functions and the links at each layer of the LFLC. While there are some limitations of application with this approach, the result of the simulation shows that the LFLC is able to control the angular shaft position of the D.C. motor. Furthermore, the LFLC has better performance in rise time, settling time and steady state error than to the conventional PI controller. This abstract accurately represents the content of the candidate's thesis. I recommend its publication.
Lung, Leung Kam↗
Vanderbilt Alumni Hall
This dataset includes processed and raw data from the Vanderbilt Alumni Hall Building (VAH) located on the University of Vanderbilt Campus in Nashville, TN. VAH is a mixed use commercial building (LEED Gold Certified) that consists of classrooms, meeting rooms, office rooms, conference rooms, an exercise room, and others. This dataset spans one year of time-series data from 2019 and includes measurements corresponding to whole building electrical power, thermal power, zone level thermal power, set-point, indoor temperature, humidity, water and air side supply and return temperatures and flow rates as CSV files. In addition to the measurements, a metadata .json file, and a .ttl file to visualize the data as per BRICK schema are also included.
32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
Transient Optimization of the Cryogenic Moderator System Controller at the Spallation Neutron Source for Improved Performance
The high-energy neutron beam generated at the Spallation Neutron Source (SNS) at Oak Ridge National Laboratory is moderated to use cold (slow) neutrons for scientific discoveries. The Cryogenic Moderator System (CMS) removes heat from the neutron beam using cryogenic hydrogen (H 2 ) moderators connected via heat exchangers to a helium (He) refrigeration loop that dissipates heat using a compressor-brake system. However, the CMS is affected by sporadic losses in beam power, referred to as "beam trips," as these events generate significant disturbances in cooling requirements. To accommodate the heat load transients during beam trips, the CMS uses a decentralized control strategy consisting of four flow valves and one electric heater adjusted by independent proportional-integral (PI) controllers. During the CMS’s initial commissioning, the PI gains were calibrated based only on tracking performance, overlooking their effectiveness in disturbance rejection. A data-driven, control-oriented closed-loop model was developed to recalibrate the PI gains and minimize the transient disturbances caused by beam trips. The model consists of three main components: (1) a physics-based model of the He refrigeration loop, (2) a machine-learning model of the cryogenic H 2 cooling trains, and (3) the control logic used for feedback set-point tracking. Experimental results showed that the recalibrated gains obtained in this study improved the CMS’s transient response during beam trips.
Maldonado Puente, Bryan↗
NASA/JPL aircraft SAR operations for 1984 and 1985
The NASA/JPL aircraft synthetic aperture radar (SAR) was used to conduct major data acquisition expeditions in 1983 through 1985. Substantial improvements to the aircraft SAR were incorporated in 1981 through 1984 resulting in an imaging radar that could simultaneously record all four combinations of linear horizontal and vertical polarization (HH, HV, VH, VV) using computer control of the radar logic, gain setting, and other functions. Data were recorded on high-density digital tapes and processed on a general-purpose computer to produce 10-km square images with 10-m resolution. These digital images yield both the amplitude and phase of the four polarizations. All of the digital images produced so far are archived at the JPL Radar Data Center and are accessible via the Reference Notebook System of that facility. Sites observed in 1984 and 1985 included geological targets in the western United States, as well as agricultural and forestry sites in the Midwest and along the eastern coast. This aircraft radar was destroyed in the CV-990 fire at March Air Force Base on 17 July 1985. It is being rebuilt for flights in l987 and will likely be operated in a mode similar to that described here. The data from 1984 and 1985 as well as those from future expeditions in 1987 and beyond will provide users with a valuable data base for the multifrequency, multipolarization Spaceborne Imaging Radar (SIR-C) scheduled for orbital operations in the early 1990's.
Thompson, T. W.↗
Hybrid neural network and fuzzy logic approaches for rendezvous and capture in space
The nonlinear behavior of many practical systems and unavailability of quantitative data regarding the input-output relations makes the analytical modeling of these systems very difficult. On the other hand, approximate reasoning-based controllers which do not require analytical models have demonstrated a number of successful applications such as the subway system in the city of Sendai. These applications have mainly concentrated on emulating the performance of a skilled human operator in the form of linguistic rules. However, the process of learning and tuning the control rules to achieve the desired performance remains a difficult task. Fuzzy Logic Control is based on fuzzy set theory. A fuzzy set is an extension of a crisp set. Crisp sets only allow full membership or no membership at all, whereas fuzzy sets allow partial membership. In other words, an element may partially belong to a set.
Berenji, Hamid R.↗
Fuzzy logic control for camera tracking system
A concept utilizing fuzzy theory has been developed for a camera tracking system to provide support for proximity operations and traffic management around the Space Station Freedom. Fuzzy sets and fuzzy logic based reasoning are used in a control system which utilizes images from a camera and generates required pan and tilt commands to track and maintain a moving target in the camera's field of view. This control system can be implemented on a fuzzy chip to provide an intelligent sensor for autonomous operations. Capabilities of the control system can be expanded to include approach, handover to other sensors, caution and warning messages.
Lea, Robert N.↗
Fuzzy logic in control systems: Fuzzy logic controller. I, II
Recent advances in the theory and applications of fuzzy-logic controllers (FLCs) are examined in an analytical review. The fundamental principles of fuzzy sets and fuzzy logic are recalled; the basic FLC components (fuzzification and defuzzification interfaces, knowledge base, and decision-making logic) are described; and the advantages of FLCs for incorporating expert knowledge into a control system are indicated. Particular attention is given to fuzzy implication functions, the interpretation of sentence connectives (and, also), compositional operators, and inference mechanisms. Applications discussed include the FLC-guided automobile developed by Sugeno and Nishida (1985), FLC hardware systems, FLCs for subway trains and ship-loading cranes, fuzzy-logic chips, and fuzzy computers.
Lee, Chuen Chien↗
A General Purpose Real-Time Optimization Strategy Applied to Minimizing Simultaneous Heating and Cooling in Buildings
Supervisory control strategies in heating, ventilating, and air-conditioning (HVAC) systems hold the potential for significant energy savings but they are difficult to set up and often depend on unreliable sensor measurements. In this paper, we propose a sensor-free approach to minimizing the energy penalties due to simultaneous heating and cooling in variable-air-volume (VAV) systems with reheat. A general-purpose real-time optimizer is described that is easy to set-up and integrate with existing control logic. A cost function is derived that quantifies the simultaneous heating and cooling penalty that does not require any sensor measurements. The optimizer then minimizes this cost function by automatically adjusting the supply temperature setpoint in the air-handling unit. The paper describes the approach and shows results from application from field trials on a 27-zone building.
Salsbury, Timothy↗
Microprogramming for real-time data acquisition
Transmit microcode trap logic is conditioned by preset clock. Measurement request or issuance of command is controlled by set of software-initialized polling tables. Receive microcode trap logic is conditioned by transmit/receive hardware when response is returned on data bus.
Patella, F. J.↗
A magnetic control system for attitude acquisition
A spacecraft magnetic attitude acquisition system is reported that is capable of automatically despinning a satellite from arbitrarily high rates around any axis and provides terminal orientation that makes capture by conventional fine control attitude control systems routine. The system consists of a 3-axis magnetometer, a set of 3 orthogonal magnets, and appropriate control logic. A well-configured system results in despin times of the order of 5 orbits per rpm for spacecraft in low earth orbits. Following despin, terminal orientation is achieved after another one to three orbits, depending on the capture range of the associated fine control system.
Stickler, A. C.↗
Extending the Capabilities of Thermal Desktop with the OpenTD Application Programming Interface
With the release of Thermal Desktop 6.0, users now had the ability to interface with some of the many elements and constructs of a Thermal Desktop model through external applications developed using the TD API (Application Programming Interface). This file allows applications to be developed in the .NET framework and interface to a number of object types within a Thermal Desktop model. The release of 6.1 expands the subset of objects able to be manipulated and now includes the raw geometrical information of surfaces. With the release of 6.1, the API was now referred to as OpenTD. This paper discusses some of the utilities and capabilities developed using the OpenTD API at the NASA Goddard Space Flight Center. These include utilities to help with configuration control of models and case sets, addition of logic to better process heater performance, and a methodology implemented to allow for submodel level processing of radiation couplings to include smaller radks where needed in a cryogenic region without using the same criteria for the warmer portions of the model. This last utility is targeting a reduction in run time without sacrificing accuracy. Lastly, some lessons learned, work-arounds, and wishes for the next release of the OpenTD API are also presented.
Thermal Desktop↗
Fuzzy Logic Decoupled Longitudinal Control for General Aviation Airplanes
It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control difference airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control throttle position and another to control elevator position. These two controllers were used to control flight path angle and airspeed for both a piston powered single engine airplane simulation and a business jet simulation. Overspeed protection and stall protection were incorporated in the form of expert systems supervisors. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic longitudinal controller could be successfully used on two general aviation aircraft types that have very difference characteristics. These controllers worked for both airplanes over their entire flight envelopes including configuration changes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle lever travel, etc.). The controllers also handled configuration changes without mode switching or knowledge of the current configuration. This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.
Duerksen, Noel↗
Fuzzy Logic Decoupled Lateral Control for General Aviation Airplanes
It has been hypothesized that a human pilot uses the same set of generic skills to control a wide variety of aircraft. If this is true, then it should be possible to construct an electronic controller which embodies this generic skill set such that it can successfully control different airplanes without being matched to a specific airplane. In an attempt to create such a system, a fuzzy logic controller was devised to control aileron or roll spoiler position. This controller was used to control bank angle for both a piston powered single engine aileron equipped airplane simulation and a business jet simulation which used spoilers for primary roll control. Overspeed, stall and overbank protection were incorporated in the form of expert systems supervisors and weighted fuzzy rules. It was found that by using the artificial intelligence techniques of fuzzy logic and expert systems, a generic lateral controller could be successfully used on two general aviation aircraft types that have very different characteristics. These controllers worked for both airplanes over their entire flight envelopes. The controllers for both airplanes were identical except for airplane specific limits (maximum allowable airspeed, throttle ]ever travel, etc.). This research validated the fact that the same fuzzy logic based controller can control two very different general aviation airplanes. It also developed the basic controller architecture and specific control parameters required for such a general controller.
Duerksen, Noel↗
Proceedings of the Second Joint Technology Workshop on Neural Networks and Fuzzy Logic, volume 2
Documented here are papers presented at the Neural Networks and Fuzzy Logic Workshop sponsored by NASA and the University of Texas, Houston. Topics addressed included adaptive systems, learning algorithms, network architectures, vision, robotics, neurobiological connections, speech recognition and synthesis, fuzzy set theory and application, control and dynamics processing, space applications, fuzzy logic and neural network computers, approximate reasoning, and multiobject decision making.
Lea, Robert N.↗