N. Pavlidou, N. Grammalidis, K. Dimitropoulos et al. · 2014
Reflections, multipath and shadows due to buildings, equipment, and other reflecting objects on the airport surface, make it difficult, if not sometimes impossible for existing Advanced Surface Movement Guidance and Control Systems (A-SMGCS) to reliably cover the whole aerodrome. In these cases another sensor must step in to fill those gaps. Digital video cameras not only can solve these kinds of problems filling blind spots in the existing A-SMGCS systems but also provide a cost effective solution. Within INTERVUSE project an innovative system for airport surface movement control was developed based on intelligent video cameras. 1.
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Yuri A.W. Shardt, Kevin Brooks, Xu Yang et al. · IFAC-PapersOnLine · 2023
As processes become more complex and the need to measure each and every variable becomes more critical, the ability of physical sensors to always provide the sufficient accuracy and sampling time can be difficult. For many complex systems, such as nonideal mixtures, multiphase fluids, and solid-based systems, it may not be possible to even use a physical sensor to measure the key variables. For example, in a multiphase fluid, the concentration or density may only be able to be accurately estimated using a laboratory procedure that can only produce a limited number of samples. Similarly, the quality variables of steel may only be determinable once the final steel product has been produced, which limits the ability to effectively control the process with small time delays. In such cases, recourse has to be made to soft sensors, or mathematical models of the system that can be used to forecast the difficult-to-measure variables and allow for real-time process monitoring, control, and optimisation. Although the development of the soft-sensor model is well-established, the various applications and use cases have not been often considered and the key challenges examined. It can be seen that soft sensors have been applied to a wide range of processes from simple, chemical engineering systems to complex mining processes. In all cases, major improvements in the process operations have been observed. However, key challenges remain in updating the soft-sensor models over time, combining laboratory measurements, especially when they are infrequent or of uncertain quality, and the development of soft sensors for new conditions or processes.
Cited by 12Open access
NASA STI Repository (National Aeronautics and Space Administration)
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Thirumurugan Shanmugam, Achuthan Munusamy, A. S. Muhammad et al. · 2024
Self-driving vehicles are right now one of the most progressive elements in the contemporary automotive industry, they may bring significant improvements for traffic safety, traffic intensity, and emission levels. However, reaching the necessary level of operational reliability for masse implementation implies surmounting issues with real-time occupancy decision making, precise localization, and accurate object identification. This paper presents a systematic approach to these problems using Machine Learning algorithms, Sensor Fusion, and Control Systems. Namely, the framework assesses CNNs and RNNs in core AV functions based on detection, classification, and trajectory prediction capabilities. In CNN evaluation arises with a classification of $94 \%$ and $F 1$ score was $\mathbf{9 4 \%}$ In the similar classification, RNN has a minimal error of $0 \%$ with overall accuracy of $\mathbf{9 1 \%}$ and precision of $\mathbf{9 0 \%}$. For increasing the accomplishment of localization and perception, different sensor fusion techniques were discussed and based on the conclusion that the EKF offered improved performance; the proposed approach achieved accurate localization up to 0.20 meters and an object detection of percent 94. Based on these results, an improved cost function was formulated, and an MPC solution was thus applied. This approach provides a tracking error which was reduced to 0.10 meters, and it has excellent performance compared to the basic PID and LQR control in similar circumstances. In doing so, this work lays down a strong foundation for further research on AV technology and the relevance of human expertise on future $A V$ systems safety and efficiency.
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Andrew Tong · OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information) · 2018
The Syngas Chemical Looping (SCL) process developed at The Ohio State University (OSU) uses an iron-based oxygen carrier to convert syngas into high-purity hydrogen while simultaneously capturing carbon dioxide that is readily sequestrable. A 25 kWth sub-pilot unit was successfully demonstrated multiple times on the OSU Clean Coal Research Facility, and a 250 kWth – 3 MWth pilot demonstration unit has been designed and constructed at the National Carbon Capture Center (NCCC) in Wilsonville, Alabama. The focus of this project is to develop multiple technologies to automate the startup and shutdown of chemical looping system. Success of this project will propel the advanced carbon capture method toward commercialization, hence be disruptive to the fossil fuel and power industries. Advanced process automation control architecture and imaging and optimization sensor software were developed for OSU chemical looping process. A high-level controller (HLC) consisting of decision-making and controller-selection logic integrated with sliding mode controllers (SMCs) were developed to perform chemical looping process startup and shutdown. Babcock & Wilcox Power Generation Group’s FocalPoint Optimization System was implemented to optimize the process operating conditions. The process automation controller and optimization information were realized and tested on OSU’s existing sub-pilot chemical looping test unit under atmospheric condition. The implemented control architecture was able to perform the complete process procedure from startup, steady-state reaction operation to shutdown with minimal operator intervention. The controller was also implemented on the pressurized syngas chemical looping (SCL) pilot test unit constructed at the National Carbon Capture Center (NCCC), demonstrating its pressure control capability with a designed transient state trajectory. An electrical capacitance volume tomography (ECVT) sensor device and its software were developed to image the packed moving bed and slugging fluidized bed of oxygen carriers in chemical looping systems at elevated temperatures. The ECVT device constructed was capable of tracking the subtle voidage variance along the moving bed axis as a feature for directly measuring the oxygen carrier particles’ linear velocity. Also, the high temperature ECVT device was used to study the fluidization characteristics of Geldart Group D particles.
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Daniel W. Seal, Thomas L. Weaver, Bradley L. Kessler et al. · NASA Technical Reports Server (NASA)
This report describes the design, development, and testing of passive fiber optic sensors and a multiplexing electro-optic architecture (EOA) for installation and flight test on a NASA-owned F-18 aircraft. This hardware was developed under the Fiber Optic Control Systems for Advanced Aircraft program, part of a multiyear NASA initiative to design, develop, and demonstrate through flight test 'fly-by-light' systems for application to advanced aircraft flight and propulsion control. This development included the design and production of 10 passive optical sensors and associated multiplexed EOA hardware based on wavelength division multiplexed (WDM) technology. A variety of sensor types (rotary position, linear position, temperature, and pressure) incorporating a broad range of sensor technologies (WDM analog, WDM digital, analog microbend, and fluorescent time rate of decay) were obtained from different manufacturers and functionally integrated with an independently designed EOA. The sensors were built for installation in a variety of aircraft locations, placing the sensors in a variety of harsh environments. The sensors and EOA were designed and built to have the resulting devices be as close as practical to a production system. The integrated system was delivered to NASA for flight testing on a NASA-owned F-18 aircraft. Development and integration testing of the system provided valuable information as to which sensor types were simplest to design and build for a military aircraft environment and which types were simplest to operate with a multiplexed EOA. Not all sensor types met the full range of performance and environmental requirements. EOA development problems provided information on directions to pursue in future fly-by-light flight control development programs. Lessons learned in the development of the EOA and sensor hardware are summarized.
Cited by 1
D. Sengeni, M. R. Mano Jemila, G.S. Krishna Priya et al. · 2024
This research study analyses the integration of a Distributed Control System (DCS) to optimise the efficiency and reliability of industrial automation, with a special emphasis on reducing power loss. Leveraging real-time sensor data and machine learning models, including Decision Trees, Artificial Neural Networks, and Random Forests, the research provides a proactive strategy to anticipating and avoiding anomalous current and voltage patterns. The DCS, armed with predictive maintenance procedures, emerges as a solid framework for reducing energy usage, assuring system stability, and limiting possible quality losses. Evaluation using performance ratings and confusion matrices reveals the efficiency of the proposed system in properly recognising and correcting deviations from normal operating circumstances. The results contribute not only to the progress of distributed control systems in industrial automation but also provide a realistic approach to real-time monitoring and predictive maintenance, supporting sustainability and operational excellence in manufacturing settings. This study sets a platform for future initiatives seeking to construct intelligent, adaptable systems for increased industrial automation performance.
Cited by 3
Kumar, Krishen, Kachroo, Pushkin · Digital Scholarship - UNLV (University of Nevada Reno) · 1996
There is a need for developing a methodology for obtaining sensor requirements for control systems. This study is an attempt at developing a methodology for specifying sensor needs as part of the design process of dynamic control systems in general, and automated highway system (AHS) in particular. Such approaches have not been advanced to-date. The current practice is to assume sensor parameters from available sensors and devise control strategies. That does not in general produce optimal designs. This paper provides a discussion on the sensor requirements needed for longitudinal headway control of vehicles in an AHS.
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Richard Furness, Steven D. Jones, James Rankin et al. · SAE technical papers on CD-ROM/SAE technical paper series · 1996
<div class="htmlview paragraph">This paper presents a description of intelligent sensor-based manufacturing, reviews previous research in this area, and identifies control system requirements necessary to support successful application of this technology. Current production control systems inhibit the successful implementation of advanced manufacturing control technologies. It is often difficult, if not impossible, to integrate new sensing technologies and advanced control algorithms with existing control platforms. To address this difficulty, hardware and software needs to support intelligent sensor-based manufacturing are discussed.</div>
Cited by 1
Sabrie Soloman · 2009
A Comprehensive Guide to Sensors and Control Systems in Manufacturing
Thoroughly updated with cutting-edge technologies, this detailed resource offers proven methods for effectively evaluating, selecting, and implementing sensors and controls to ensure error-free manufacturing environments. Sensors and Control Systems in Manufacturing, Second Edition offers step-by-step guidance on applying sensors to measure product parameters, control manufacturing, develop precision manufacturing systems, and generate and control motion. Real-world examples are included throughout to demonstrate successful industrial applications.
Coverage includes:
The latest sensor technologies, such as MEMS, photo-, bio-, nano-, and LED sensors Sensor classification and types, including photoelectric, inductive and capacitive proximity, confocal microscropy, and laser sensors Fiber optics in sensors and control systems Networking of sensors and control systems in manufacturing Sensors and control technology in computer-integrated manufacturing Advanced sensor technology in precision manufacturing applications Industrial sensors and control Sensors in flexible manufacturing systems Communications--indexing, transmission, and signal processing SpectRx(tm) sensing technology Manufacturing operation and control through financial planning
Table of contents
Chapter 1. Introduction – Traditional Sensors;Chapter 2. Establishing Sensors Strategy in Automated High Volume Production Environment; Chapter 3. Laser Sensors; Chapter 4. LED Sensing Technology; Chapter 5. Fiber Optics in Sensors and Control Systems; Chapter 6. Vision Sensing Technology in Pharmaceuticals and Medical Industries; Chapter 7. Networking of Sensors and Control Systems in Manufacturing; Chapter 8. The role of Sensors and Control Technology in Computer Integrated Manufacturing Technology; Chapter 9. Advanced Sensor Technology in Production Manufacturing Applications; Chapter 10. Medical and Biomedical Sensors; Chapter 11. Industrial Sensors and Control; Chapter 12. Sensors in Agile-Flexible Manufacturing Systems; Chapter 13. Communications; Chapter 14. Economic and Social Interest in Sensor Development and Manufacturing Business
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Jordis Blackburn · Defense Technical Information Center (DTIC) · 1984
The Fourth International Conference on Robot Vision and Sensory Controls was held in London from 9 through 11 October 1984. The conference covered the following areas: sensor-based manufacturing, vision systems, sensor-guided welding, three-dimensional sensing, robot guidance and sensory control, nonvision sensing, knowledge-based sensory systems, and advanced vision techniques. (Author)
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Surdilovic, D., Duelen, G., Münch, H. · Fraunhofer-Publica (Fraunhofer-Gesellschaft) · 1990
This paper presents an advanced robot control system which is currently under development at the Institute for Production Systems and Design Technology (IPK). This general purpose system attempts to provide a basic hard-and software frame for the integration of avariety of advanced control techniques and concepts. Its architecture is designed similar to those developed by NASA and NBS. Different levels of this framework incorporate the theoretical and practical experiances gained at the IPK during years of development of industrial control systems and other investigations related to advanced control in the fields of: Off-line programming, trajectory planning, sensor guided process control, cooperating robots, control of redundant robotic systems and hybride forceposition/control.
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L. P. Giroir, Martin, A., Paulson, V. et al. · Defense Technical Information Center (DTIC) · 1974
The advanced electronic display system (ADEDS) task of the SST Technology Follow-on Program includes the formal definition and documentation of the signal interface mechanization. This report defines the signal interfaces as mechanized for the flight test airplane installation. Included is the definition of interfaces between: elements of the display system, the display system and ancillary sensor systems, elements of the navigation system, the display and navigation systems, the navigation system and ancillary sensor systems, and the navigation system and other elements of the advanced guidance and control system. (Author)
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2017
The following topics are dealt with: data analytics; ensemble classifiers; intelligent systems; signal processing; face recognition; cyber-medical systems; UAV; sensor fusion; smart cities; advanced driver assistance system; transport management systems; educational models; control systems; cybersecurity; higher education; and stomach cancer images.
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Yuchong Nie · Springer Link (Chiba Institute of Technology) · 2025
In the context of increasing vehicle demand, the level of technological development in vehicle performance plays a dominant role in the competition of the automotive market. Among the emerging aspects, intelligent vehicles utilize cutting-edge vehicle control systems, benefiting from high-precision navigation systems and sensor networks, to achieve functions such as autonomous driving, automatic route finding, and automated parking. This research summarizes the working principles of high-precision navigation systems and sensor networks; analyzes the adaptability of sensor applications based on specification data, expands on advanced technologies in sensor networks, and explores the potential applications of sensors and navigation systems. These studies enhance the understanding of how the accuracy of navigation systems affects practical outcomes in driving systems, providing some reference for developers of vehicle control systems and furthering the technological development of intelligent vehicles.
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Caleb Petrie, Smit Gupta, Vittal S. Rao et al. · 2018
The incorporation of advanced sensor data acquisition techniques, concepts of cyber physical systems, and the Internet of Things (IoT) devices into infrastructures and building energy management systems is enabling the smart city deployments. The main emphasis of this paper is to design and implementation of energy efficient controls into the heating, ventilation, and air conditioning (HVAC) systems of the commercial buildings. These systems are responsible for providing acceptable indoor air quality and thermal comfort to the occupants. By tuning and implementing advanced control systems into the existing HVAC systems, energy consumption can be reduced by 20-30%. The traditional control techniques are compared with two advanced control techniques: Pattern Recognition Adaptive Controller (PRAC) and Model Predictive Control (MPC). The salient features of the advanced control techniques are presented. By utilizing the existing hardware and software systems, the proposed control techniques are implemented on one of the academic buildings of the Texas Tech University campus. The preliminary results obtained in the minimization of simultaneous heating and cooling and energy savings of the HVAC systems are presented in the paper.
Cited by 13
Ms Thangamani, S Manojkumar, R Dwikarand et al. · 2013
The following topics are dealt with: network security; pervasive computing; cloud computing; advanced computing technologies; mobile computing; wireless communications; data mining; knowledge discovery; advanced networking; information security; information retrieval; artificial intelligence; soft computing; grid computing; 3G/4G wireless technologies; advanced communication systems; optical communication; networking sensor / ad hoc networks; medical electronics; RF antenna design; RF antenna modeling; RF antenna measurement; computational electromagnetics; image processing; speech processing; real time embedded systems; MEMs and NEMs; electrical drives; embedded control; embedded systems; nano-photonics; fuzzy logic; neural network technologies; embedded networking; embedded system design ; VLSI automation & distributed control systems; remote sensing.
Cited by 0Open access
B. J. Almand · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1985
This paper is a synopsis from a study of sensor data fusion and artificial intelligence (AI) aspects of blackboarding systems (or belief structure methodology). The study promotes the design of a knowledge base for robot motion control and a decisionmaking scheme for a robot working in an environment, using multiple sensors for guidance and control. Advanced manipulator control systems require output processing from several sensors, fusion of the sensor data, and determination of motions that best adjust the end-effector position for an optimal motion trajectory. A method to weigh the data from the manipulator guidance sensors and rules for sensor output processing will be proposed.
Cited by 4
Alan M. Lytle, Fred Proctor, Kamel Saidi · 2008
The Construction Metrology and Automation Group at the National Institute of Standards and Technology (NIST) is conducting research to provide standards, methodologies, and performance metrics that will assist the development of advanced systems to automate construction tasks. This research includes crane automation, advanced site metrology systems, laser-based 3D imaging, calibrated camera networks, construction object identification and tracking, and sensor integration and process control from Building Information Models. The NIST RoboCrane has factored into much of this research both as a robotics test platform and a sensor/target positioning apparatus. This chapter provides a brief review of the RoboCrane platform, an explanation of control algorithms including the NIST GoMotion controller, and a discussion of crane task decomposition using the Four Dimensional/Real-time Control System approach.
Cited by 5Open access
Xin Chen · Trans Tech Publications Ltd. eBooks · 2011
The peer-reviewed papers making up this book cover the subject areas of: materials and their applications, mechatronics, industrial robotics and automation, machine vision, sensor technology, micro-electronic technology, measure control technologies and intelligent systems, transmission and control of fluids, mechanical control and information processing technology, embedded systems, advanced forming manufacturing and equipment, NEMS/MEMS technology and equipment, micro-electronic packaging technology and equipment, advanced nanocomposite techniques and equipment, power and fluid machinery, energy machinery and equipment, construction machinery and equipment and other related topics. The work constitutes an invaluable guide to the subjects covered.
Cited by 4Open access