WorldWideScience

Sample records for learning control systems

  1. Repetitive learning control of continuous chaotic systems

    International Nuclear Information System (INIS)

    Chen Maoyin; Shang Yun; Zhou Donghua

    2004-01-01

    Combining a shift method and the repetitive learning strategy, a repetitive learning controller is proposed to stabilize unstable periodic orbits (UPOs) within chaotic attractors in the sense of least mean square. If nonlinear parts in chaotic systems satisfy Lipschitz condition, the proposed controller can be simplified into a simple proportional repetitive learning controller

  2. Linear System Control Using Stochastic Learning Automata

    Science.gov (United States)

    Ziyad, Nigel; Cox, E. Lucien; Chouikha, Mohamed F.

    1998-01-01

    This paper explains the use of a Stochastic Learning Automata (SLA) to control switching between three systems to produce the desired output response. The SLA learns the optimal choice of the damping ratio for each system to achieve a desired result. We show that the SLA can learn these states for the control of an unknown system with the proper choice of the error criteria. The results of using a single automaton are compared to using multiple automata.

  3. Indirect learning control for nonlinear dynamical systems

    Science.gov (United States)

    Ryu, Yeong Soon; Longman, Richard W.

    1993-01-01

    In a previous paper, learning control algorithms were developed based on adaptive control ideas for linear time variant systems. The learning control methods were shown to have certain advantages over their adaptive control counterparts, such as the ability to produce zero tracking error in time varying systems, and the ability to eliminate repetitive disturbances. In recent years, certain adaptive control algorithms have been developed for multi-body dynamic systems such as robots, with global guaranteed convergence to zero tracking error for the nonlinear system euations. In this paper we study the relationship between such adaptive control methods designed for this specific class of nonlinear systems, and the learning control problem for such systems, seeking to converge to zero tracking error in following a specific command repeatedly, starting from the same initial conditions each time. The extension of these methods from the adaptive control problem to the learning control problem is seen to be trivial. The advantages and disadvantages of using learning control based on such adaptive control concepts for nonlinear systems, and the use of other currently available learning control algorithms are discussed.

  4. Online reinforcement learning control for aerospace systems

    NARCIS (Netherlands)

    Zhou, Y.

    2018-01-01

    Reinforcement Learning (RL) methods are relatively new in the field of aerospace guidance, navigation, and control. This dissertation aims to exploit RL methods to improve the autonomy and online learning of aerospace systems with respect to the a priori unknown system and environment, dynamical

  5. Learning to Control Advanced Life Support Systems

    Science.gov (United States)

    Subramanian, Devika

    2004-01-01

    Advanced life support systems have many interacting processes and limited resources. Controlling and optimizing advanced life support systems presents unique challenges. In particular, advanced life support systems are nonlinear coupled dynamical systems and it is difficult for humans to take all interactions into account to design an effective control strategy. In this project. we developed several reinforcement learning controllers that actively explore the space of possible control strategies, guided by rewards from a user specified long term objective function. We evaluated these controllers using a discrete event simulation of an advanced life support system. This simulation, called BioSim, designed by Nasa scientists David Kortenkamp and Scott Bell has multiple, interacting life support modules including crew, food production, air revitalization, water recovery, solid waste incineration and power. They are implemented in a consumer/producer relationship in which certain modules produce resources that are consumed by other modules. Stores hold resources between modules. Control of this simulation is via adjusting flows of resources between modules and into/out of stores. We developed adaptive algorithms that control the flow of resources in BioSim. Our learning algorithms discovered several ingenious strategies for maximizing mission length by controlling the air and water recycling systems as well as crop planting schedules. By exploiting non-linearities in the overall system dynamics, the learned controllers easily out- performed controllers written by human experts. In sum, we accomplished three goals. We (1) developed foundations for learning models of coupled dynamical systems by active exploration of the state space, (2) developed and tested algorithms that learn to efficiently control air and water recycling processes as well as crop scheduling in Biosim, and (3) developed an understanding of the role machine learning in designing control systems for

  6. Learning System Center App Controller

    CERN Document Server

    Naeem, Nasir

    2015-01-01

    This book is intended for IT professionals working with Hyper-V, Azure cloud, VMM, and private cloud technologies who are looking for a quick way to get up and running with System Center 2012 R2 App Controller. To get the most out of this book, you should be familiar with Microsoft Hyper-V technology. Knowledge of Virtual Machine Manager is helpful but not mandatory.

  7. Integrated Programme Control Systems: Lessons Learned

    Energy Technology Data Exchange (ETDEWEB)

    Brown, C. W. [Babcock International Group PLC (formerly UKAEA Ltd) B21 Forss, Thurso, Caithness, Scotland (United Kingdom)

    2013-08-15

    Dounreay was the UK's centre of fast reactor research and development from 1955 until 1994 and is now Scotland's largest nuclear clean up and demolition project. After four decades of research, Dounreay is now a site of construction, demolition and waste management, designed to return the site to as near as practicable to its original condition. Dounreay has a turnover in the region of Pounds 150 million a year and employs approximately 900 people. It subcontracts work to 50 or so companies in the supply chain and this provides employment for a similar number of people. The plan for decommissioning the site anticipates all redundant buildings will be cleared in the short term. The target date to achieve interim end state by 2039 is being reviewed in light of Government funding constraints, and will be subject to change through the NDA led site management competition. In the longer term, controls will be put in place on the use of contaminated land until 2300. In supporting the planning, management and organisational aspects for this complex decommissioning programme an integrated programme controls system has been developed and deployed. This consists of a combination of commercial and bespoke tools integrated to support all aspects of programme management, namely scope, schedule, cost, estimating and risk in order to provide baseline and performance management data based upon the application of earned value management principles. Through system evolution and lessons learned, the main benefits of this approach are management data consistency, rapid communication of live information, and increased granularity of data providing summary and detailed reports which identify performance trends that lead to corrective actions. The challenges of such approach are effective use of the information to realise positive changes, balancing the annual system support and development costs against the business needs, and maximising system performance. (author)

  8. Cognitive Models for Learning to Control Dynamic Systems

    National Research Council Canada - National Science Library

    Eberhart, Russ; Hu, Xiaohui; Chen, Yaobin

    2008-01-01

    Report developed under STTR contract for topic "Cognitive models for learning to control dynamic systems" demonstrated a swarm intelligence learning algorithm and its application in unmanned aerial vehicle (UAV) mission planning...

  9. Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)

    Science.gov (United States)

    Niewoehner, Kevin R.; Carter, John (Technical Monitor)

    2001-01-01

    The research accomplishments for the cooperative agreement 'Online Learning Flight Control for Intelligent Flight Control Systems (IFCS)' include the following: (1) previous IFC program data collection and analysis; (2) IFC program support site (configured IFC systems support network, configured Tornado/VxWorks OS development system, made Configuration and Documentation Management Systems Internet accessible); (3) Airborne Research Test Systems (ARTS) II Hardware (developed hardware requirements specification, developing environmental testing requirements, hardware design, and hardware design development); (4) ARTS II software development laboratory unit (procurement of lab style hardware, configured lab style hardware, and designed interface module equivalent to ARTS II faceplate); (5) program support documentation (developed software development plan, configuration management plan, and software verification and validation plan); (6) LWR algorithm analysis (performed timing and profiling on algorithm); (7) pre-trained neural network analysis; (8) Dynamic Cell Structures (DCS) Neural Network Analysis (performing timing and profiling on algorithm); and (9) conducted technical interchange and quarterly meetings to define IFC research goals.

  10. Systems control with generalized probabilistic fuzzy-reinforcement learning

    NARCIS (Netherlands)

    Hinojosa, J.; Nefti, S.; Kaymak, U.

    2011-01-01

    Reinforcement learning (RL) is a valuable learning method when the systems require a selection of control actions whose consequences emerge over long periods for which input-output data are not available. In most combinations of fuzzy systems and RL, the environment is considered to be

  11. Generalized projective synchronization of chaotic systems via adaptive learning control

    International Nuclear Information System (INIS)

    Yun-Ping, Sun; Jun-Min, Li; Hui-Lin, Wang; Jiang-An, Wang

    2010-01-01

    In this paper, a learning control approach is applied to the generalized projective synchronisation (GPS) of different chaotic systems with unknown periodically time-varying parameters. Using the Lyapunov–Krasovskii functional stability theory, a differential-difference mixed parametric learning law and an adaptive learning control law are constructed to make the states of two different chaotic systems asymptotically synchronised. The scheme is successfully applied to the generalized projective synchronisation between the Lorenz system and Chen system. Moreover, numerical simulations results are used to verify the effectiveness of the proposed scheme. (general)

  12. Fuzzy self-learning control for magnetic servo system

    Science.gov (United States)

    Tarn, J. H.; Kuo, L. T.; Juang, K. Y.; Lin, C. E.

    1994-01-01

    It is known that an effective control system is the key condition for successful implementation of high-performance magnetic servo systems. Major issues to design such control systems are nonlinearity; unmodeled dynamics, such as secondary effects for copper resistance, stray fields, and saturation; and that disturbance rejection for the load effect reacts directly on the servo system without transmission elements. One typical approach to design control systems under these conditions is a special type of nonlinear feedback called gain scheduling. It accommodates linear regulators whose parameters are changed as a function of operating conditions in a preprogrammed way. In this paper, an on-line learning fuzzy control strategy is proposed. To inherit the wealth of linear control design, the relations between linear feedback and fuzzy logic controllers have been established. The exercise of engineering axioms of linear control design is thus transformed into tuning of appropriate fuzzy parameters. Furthermore, fuzzy logic control brings the domain of candidate control laws from linear into nonlinear, and brings new prospects into design of the local controllers. On the other hand, a self-learning scheme is utilized to automatically tune the fuzzy rule base. It is based on network learning infrastructure; statistical approximation to assign credit; animal learning method to update the reinforcement map with a fast learning rate; and temporal difference predictive scheme to optimize the control laws. Different from supervised and statistical unsupervised learning schemes, the proposed method learns on-line from past experience and information from the process and forms a rule base of an FLC system from randomly assigned initial control rules.

  13. Fixed Point Learning Based Intelligent Traffic Control System

    Science.gov (United States)

    Zongyao, Wang; Cong, Sui; Cheng, Shao

    2017-10-01

    Fixed point learning has become an important tool to analyse large scale distributed system such as urban traffic network. This paper presents a fixed point learning based intelligence traffic network control system. The system applies convergence property of fixed point theorem to optimize the traffic flow density. The intelligence traffic control system achieves maximum road resources usage by averaging traffic flow density among the traffic network. The intelligence traffic network control system is built based on decentralized structure and intelligence cooperation. No central control is needed to manage the system. The proposed system is simple, effective and feasible for practical use. The performance of the system is tested via theoretical proof and simulations. The results demonstrate that the system can effectively solve the traffic congestion problem and increase the vehicles average speed. It also proves that the system is flexible, reliable and feasible for practical use.

  14. A new 2-d approach to iterative , learning control system

    International Nuclear Information System (INIS)

    Ashraf, S.; Muhammad, E.; Tasleem, M.

    2004-01-01

    The well known two-dimensional system theory is used to analyze and develop a class of learning control system. In this paper we first explore and test a method given by ZHENG and JAMSHIDI. In that paper all the input samples are treated at once. In comparison our paper presents a scheme in which one sample at a time is treated. The 2- D state-space model of proposed learning control scheme is given. An important consequence of the proposed scheme is that given the right choice of gain matrix and sampling time the system's output can be made to converge to any degree of accuracy. (author)

  15. Machine Learning Control For Highly Reconfigurable High-Order Systems

    Science.gov (United States)

    2015-01-02

    calibration and applications,” Mechatronics and Embedded Systems and Applications (MESA), 2010 IEEE/ASME International Conference on, IEEE, 2010, pp. 38–43...AFRL-OSR-VA-TR-2015-0012 MACHINE LEARNING CONTROL FOR HIGHLY RECONFIGURABLE HIGH-ORDER SYSTEMS John Valasek TEXAS ENGINEERING EXPERIMENT STATION...DIMENSIONAL RECONFIGURABLE SYSTEMS FA9550-11-1-0302 Period of Performance 1 July 2011 – 29 September 2014 John Valasek Aerospace Engineering

  16. Lessons learned on the Ground Test Accelerator control system

    International Nuclear Information System (INIS)

    Kozubal, A.J.; Weiss, R.E.

    1994-01-01

    When we initiated the control system design for the Ground Test Accelerator (GTA), we envisioned a system that would be flexible enough to handle the changing requirements of an experimental project. This control system would use a developers' toolkit to reduce the cost and time to develop applications for GTA, and through the use of open standards, the system would accommodate unforeseen requirements as they arose. Furthermore, we would attempt to demonstrate on GTA a level of automation far beyond that achieved by existing accelerator control systems. How well did we achieve these goals? What were the stumbling blocks to deploying the control system, and what assumptions did we make about requirements that turned out to be incorrect? In this paper we look at the process of developing a control system that evolved into what is now the ''Experimental Physics and Industrial Control System'' (EPICS). Also, we assess the impact of this system on the GTA project, as well as the impact of GTA on EPICS. The lessons learned on GTA will be valuable for future projects

  17. A Parametric Learning and Identification Based Robust Iterative Learning Control for Time Varying Delay Systems

    Directory of Open Access Journals (Sweden)

    Lun Zhai

    2014-01-01

    Full Text Available A parametric learning based robust iterative learning control (ILC scheme is applied to the time varying delay multiple-input and multiple-output (MIMO linear systems. The convergence conditions are derived by using the H∞ and linear matrix inequality (LMI approaches, and the convergence speed is analyzed as well. A practical identification strategy is applied to optimize the learning laws and to improve the robustness and performance of the control system. Numerical simulations are illustrated to validate the above concepts.

  18. Iterative learning control for multi-agent systems coordination

    CERN Document Server

    Yang, Shiping; Li, Xuefang; Shen, Dong

    2016-01-01

    A timely guide using iterative learning control (ILC) as a solution for multi-agent systems (MAS) challenges, this book showcases recent advances and industrially relevant applications. Readers are first given a comprehensive overview of the intersection between ILC and MAS, then introduced to a range of topics that include both basic and advanced theoretical discussions, rigorous mathematics, engineering practice, and both linear and nonlinear systems. Through systematic discussion of network theory and intelligent control, the authors explore future research possibilities, develop new tools, and provide numerous applications such as power grids, communication and sensor networks, intelligent transportation systems, and formation control. Readers will gain a roadmap of the latest advances in the fields and can use their newfound knowledge to design their own algorithms.

  19. The Effectiveness of E-Learning Systems: A Review of the Empirical Literature on Learner Control

    Science.gov (United States)

    Sorgenfrei, Christian; Smolnik, Stefan

    2016-01-01

    E-learning systems are considerably changing education and organizational training. With the advancement of online-based learning systems, learner control over the instructional process has emerged as a decisive factor in technology-based forms of learning. However, conceptual work on the role of learner control in e-learning has not advanced…

  20. Group performance and group learning at dynamic system control tasks

    International Nuclear Information System (INIS)

    Drewes, Sylvana

    2013-01-01

    Proper management of dynamic systems (e.g. cooling systems of nuclear power plants or production and warehousing) is important to ensure public safety and economic success. So far, research has provided broad evidence for systematic shortcomings in individuals' control performance of dynamic systems. This research aims to investigate whether groups manifest synergy (Larson, 2010) and outperform individuals and if so, what processes lead to these performance advantages. In three experiments - including simulations of a nuclear power plant and a business setting - I compare the control performance of three-person-groups to the average individual performance and to nominal groups (N = 105 groups per experiment). The nominal group condition captures the statistical advantage of aggregated group judgements not due to social interaction. First, results show a superior performance of groups compared to individuals. Second, a meta-analysis across all three experiments shows interaction-based process gains in dynamic control tasks: Interacting groups outperform the average individual performance as well as the nominal group performance. Third, group interaction leads to stable individual improvements of group members that exceed practice effects. In sum, these results provide the first unequivocal evidence for interaction-based performance gains of groups in dynamic control tasks and imply that employers should rely on groups to provide opportunities for individual learning and to foster dynamic system control at its best.

  1. Recent developments in learning control and system identification for robots and structures

    Science.gov (United States)

    Phan, M.; Juang, J.-N.; Longman, R. W.

    1990-01-01

    This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

  2. Lessons learned from the MIT Tara control and data system

    International Nuclear Information System (INIS)

    Gaudreau, M.P.J.; Sullivan, J.D.; Fredian, T.W.; Irby, J.H.; Karcher, C.A.; Rameriz, R.A.; Sevillano, E.; Stillerman, J.A.; Thomas, P.

    1987-10-01

    The control and data system of the MIT Tara Tandem Mirror has worked successfully throughout the lifetime of the experiment (1983 through 1987). As the Tara project winds down, it is appropriate to summarize the lessons learned from the implementation and operation of the control and data system over the years and in its final form. The control system handled ∼2400 I/0 points in real time throughout the 5 to 10 minute shot cycle while the data system, in near real time, handled ∼1000 signals with a total of 5 to 7 Mbytes of data each shot. The implementation depended upon a consistent approach based on separating physics and engineering functions and on detailed functional diagrams with narrowly defined cross communication. This paper is a comprehensive treatment of the principal successes, residual problems, and dilemmas that arose from the beginning until the final hardware and software implementation. Suggestions for future systems of either similar size or of larger scale such as CIT are made in the conclusion. 11 refs., 1 fig

  3. Design of fuzzy learning control systems for steam generator water level control

    International Nuclear Information System (INIS)

    Park, Gee Yong

    1996-02-01

    A fuzzy learning algorithm is developed in order to construct the useful control rules and tune the membership functions in the fuzzy logic controller used for water level control of nuclear steam generator. The fuzzy logic controllers have shown to perform better than conventional controllers for ill-defined or complex processes such as nuclear steam generator. Whereas the fuzzy logic controller does not need a detailed mathematical model of a plant to be controlled, its structure is to be made on the basis of the operator's linguistic information experienced from the plant operations. It is not an easy work and also there is no systematic way to translate the operator's linguistic information into quantitative information. When the linguistic information of operators is incomplete, tuning the parameters of fuzzy controller is to be performed for better control performance. It is the time and effort consuming procedure that controller designer has to tune the structure of fuzzy logic controller for optimal performance. And if the number of control inputs is many and the rule base is constructed in multidimensional space, it is very difficult for a controller designer to tune the fuzzy controller structure. Hence, the difficulty in putting the experimental knowledge into quantitative (or numerical) data and the difficulty in tuning the rules are the major problems in designing fuzzy logic controller. In order to overcome the problems described above, a learning algorithm by gradient descent method is included in the fuzzy control system such that the membership functions are tuned and the necessary rules are created automatically for good control performance. For stable learning in gradient descent method, the optimal range of learning coefficient not to be trapped and not to provide too slow learning speed is investigated. With the optimal range of learning coefficient, the optimal value of learning coefficient is suggested and with this value, the gradient

  4. E-Learning System for Learning Virtual Circuit Making with a Microcontroller and Programming to Control a Robot

    Science.gov (United States)

    Takemura, Atsushi

    2015-01-01

    This paper proposes a novel e-Learning system for learning electronic circuit making and programming a microcontroller to control a robot. The proposed e-Learning system comprises a virtual-circuit-making function for the construction of circuits with a versatile, Arduino microcontroller and an educational system that can simulate behaviors of…

  5. Experiential learning in control systems laboratories and engineering project management

    Science.gov (United States)

    Reck, Rebecca Marie

    Experiential learning is a process by which a student creates knowledge through the insights gained from an experience. Kolb's model of experiential learning is a cycle of four modes: (1) concrete experience, (2) reflective observation, (3) abstract conceptualization, and (4) active experimentation. His model is used in each of the three studies presented in this dissertation. Laboratories are a popular way to apply the experiential learning modes in STEM courses. Laboratory kits allow students to take home laboratory equipment to complete experiments on their own time. Although students like laboratory kits, no previous studies compared student learning outcomes on assignments using laboratory kits with existing laboratory equipment. In this study, we examined the similarities and differences between the experiences of students who used a portable laboratory kit and students who used the traditional equipment. During the 2014- 2015 academic year, we conducted a quasi-experiment to compare students' achievement of learning outcomes and their experiences in the instructional laboratory for an introductory control systems course. Half of the laboratory sections in each semester used the existing equipment, while the other sections used a new kit. We collected both quantitative data and qualitative data. We did not identify any major differences in the student experience based on the equipment they used. Course objectives, like research objectives and product requirements, help provide clarity and direction for faculty and students. Unfortunately, course and laboratory objectives are not always clearly stated. Without a clear set of objectives, it can be hard to design a learning experience and determine whether students are achieving the intended outcomes of the course or laboratory. In this study, I identified a common set of laboratory objectives, concepts, and components of a laboratory apparatus for undergraduate control systems laboratories. During the summer of

  6. Application of parsimonious learning feedforward control to mechatronic systems

    NARCIS (Netherlands)

    de Vries, Theodorus J.A.; Velthuis, W.J.R.; Idema, L.J.

    2001-01-01

    For motion control, learning feedforward controllers (LFFCs) should be applied when accurate process modelling is difficult. When controlling such processes with LFFCs in the form of multidimensional B-spline networks, large network sizes and a poor generalising ability may result, known as the

  7. Traffic light control by multiagent reinforcement learning systems

    NARCIS (Netherlands)

    Bakker, B.; Whiteson, S.; Kester, L.; Groen, F.C.A.; Babuška, R.; Groen, F.C.A.

    2010-01-01

    Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of

  8. Traffic Light Control by Multiagent Reinforcement Learning Systems

    NARCIS (Netherlands)

    Bakker, B.; Whiteson, S.; Kester, L.J.H.M.; Groen, F.C.A.

    2010-01-01

    Traffic light control is one of the main means of controlling road traffic. Improving traffic control is important because it can lead to higher traffic throughput and reduced traffic congestion. This chapter describes multiagent reinforcement learning techniques for automatic optimization of

  9. Algebraic and adaptive learning in neural control systems

    Science.gov (United States)

    Ferrari, Silvia

    A systematic approach is developed for designing adaptive and reconfigurable nonlinear control systems that are applicable to plants modeled by ordinary differential equations. The nonlinear controller comprising a network of neural networks is taught using a two-phase learning procedure realized through novel techniques for initialization, on-line training, and adaptive critic design. A critical observation is that the gradients of the functions defined by the neural networks must equal corresponding linear gain matrices at chosen operating points. On-line training is based on a dual heuristic adaptive critic architecture that improves control for large, coupled motions by accounting for actual plant dynamics and nonlinear effects. An action network computes the optimal control law; a critic network predicts the derivative of the cost-to-go with respect to the state. Both networks are algebraically initialized based on prior knowledge of satisfactory pointwise linear controllers and continue to adapt on line during full-scale simulations of the plant. On-line training takes place sequentially over discrete periods of time and involves several numerical procedures. A backpropagating algorithm called Resilient Backpropagation is modified and successfully implemented to meet these objectives, without excessive computational expense. This adaptive controller is as conservative as the linear designs and as effective as a global nonlinear controller. The method is successfully implemented for the full-envelope control of a six-degree-of-freedom aircraft simulation. The results show that the on-line adaptation brings about improved performance with respect to the initialization phase during aircraft maneuvers that involve large-angle and coupled dynamics, and parameter variations.

  10. Design of intelligent comfort control system with human learning and minimum power control strategies

    International Nuclear Information System (INIS)

    Liang, J.; Du, R.

    2008-01-01

    This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future

  11. Which Management Control System principles and aspects are relevant when deploying a learning machine?

    OpenAIRE

    Martin, Johansson; Mikael, Göthager

    2017-01-01

    How shall a business adapt its management control systems when learning machines enter the arena? Will the control system continue to focus on humans aspects and continue to consider a learning machine to be an automation tool as any other historically programmed computer? Learning machines introduces productivity capabilities that achieve very high levels of efficiency and quality. A learning machine can sort through large amounts of data and make conclusions difficult by a human mind. Howev...

  12. Digital control systems training on a distance learning platform

    Directory of Open Access Journals (Sweden)

    Jan PIECHA

    2009-01-01

    Full Text Available The paper deals with new training technologies development based on approach to distance learning website, implemented in the laboratory of a Traffic Engineering study branch at Faculty of Transport. The discussed computing interface allows students complete knowledge of traffic controllers’ architecture and machine language programming fundamentals. These training facilities are available at home; at their remote terminal. The training resources consist of electronic / computer based training; guidebooks and software units. The laboratory provides the students with an interface entering into simulation packages and programming interfaces, supporting the web training facilities. The courseware complexity selection is one of the most difficult factors in intelligent training unit’s development. The dynamically configured application provides the user with his individually set structure of the training resources. The trainee controls the application structure and complexity, from the time he started. For simplifying the training process and studying activities, several unifications were provided. The introduced ideas need various standardisations, simplifying the e-learning units’ development and application control processes [8], [9]. Further training facilities development concerns virtual laboratory environment organisation in laboratories of Transport Faculty.

  13. A learning flight control system for the F8-DFBW aircraft. [Digital Fly-By-Wire

    Science.gov (United States)

    Montgomery, R. C.; Mekel, R.; Nachmias, S.

    1978-01-01

    This report contains a complete description of a learning control system designed for the F8-DFBW aircraft. The system is parameter-adaptive with the additional feature that it 'learns' the variation of the control system gains needed over the flight envelope. It, thus, generates and modifies its gain schedule when suitable data are available. The report emphasizes the novel learning features of the system: the forms of representation of the flight envelope and the process by which identified parameters are used to modify the gain schedule. It contains data taken during piloted real-time 6 degree-of-freedom simulations that were used to develop and evaluate the system.

  14. Effectiveness of Adaptive Assessment versus Learner Control in a Multimedia Learning System

    Science.gov (United States)

    Chen, Ching-Huei; Chang, Shu-Wei

    2015-01-01

    The purpose of this study was to explore the effectiveness of adaptive assessment versus learner control in a multimedia learning system designed to help secondary students learn science. Unlike other systems, this paper presents a workflow of adaptive assessment following instructional materials that better align with learners' cognitive…

  15. Learning from neural control.

    Science.gov (United States)

    Wang, Cong; Hill, David J

    2006-01-01

    One of the amazing successes of biological systems is their ability to "learn by doing" and so adapt to their environment. In this paper, first, a deterministic learning mechanism is presented, by which an appropriately designed adaptive neural controller is capable of learning closed-loop system dynamics during tracking control to a periodic reference orbit. Among various neural network (NN) architectures, the localized radial basis function (RBF) network is employed. A property of persistence of excitation (PE) for RBF networks is established, and a partial PE condition of closed-loop signals, i.e., the PE condition of a regression subvector constructed out of the RBFs along a periodic state trajectory, is proven to be satisfied. Accurate NN approximation for closed-loop system dynamics is achieved in a local region along the periodic state trajectory, and a learning ability is implemented during a closed-loop feedback control process. Second, based on the deterministic learning mechanism, a neural learning control scheme is proposed which can effectively recall and reuse the learned knowledge to achieve closed-loop stability and improved control performance. The significance of this paper is that the presented deterministic learning mechanism and the neural learning control scheme provide elementary components toward the development of a biologically-plausible learning and control methodology. Simulation studies are included to demonstrate the effectiveness of the approach.

  16. GA-based fuzzy reinforcement learning for control of a magnetic bearing system.

    Science.gov (United States)

    Lin, C T; Jou, C P

    2000-01-01

    This paper proposes a TD (temporal difference) and GA (genetic algorithm)-based reinforcement (TDGAR) learning method and applies it to the control of a real magnetic bearing system. The TDGAR learning scheme is a new hybrid GA, which integrates the TD prediction method and the GA to perform the reinforcement learning task. The TDGAR learning system is composed of two integrated feedforward networks. One neural network acts as a critic network to guide the learning of the other network (the action network) which determines the outputs (actions) of the TDGAR learning system. The action network can be a normal neural network or a neural fuzzy network. Using the TD prediction method, the critic network can predict the external reinforcement signal and provide a more informative internal reinforcement signal to the action network. The action network uses the GA to adapt itself according to the internal reinforcement signal. The key concept of the TDGAR learning scheme is to formulate the internal reinforcement signal as the fitness function for the GA such that the GA can evaluate the candidate solutions (chromosomes) regularly, even during periods without external feedback from the environment. This enables the GA to proceed to new generations regularly without waiting for the arrival of the external reinforcement signal. This can usually accelerate the GA learning since a reinforcement signal may only be available at a time long after a sequence of actions has occurred in the reinforcement learning problem. The proposed TDGAR learning system has been used to control an active magnetic bearing (AMB) system in practice. A systematic design procedure is developed to achieve successful integration of all the subsystems including magnetic suspension, mechanical structure, and controller training. The results show that the TDGAR learning scheme can successfully find a neural controller or a neural fuzzy controller for a self-designed magnetic bearing system.

  17. Off-policy integral reinforcement learning optimal tracking control for continuous-time chaotic systems

    International Nuclear Information System (INIS)

    Wei Qing-Lai; Song Rui-Zhuo; Xiao Wen-Dong; Sun Qiu-Ye

    2015-01-01

    This paper estimates an off-policy integral reinforcement learning (IRL) algorithm to obtain the optimal tracking control of unknown chaotic systems. Off-policy IRL can learn the solution of the HJB equation from the system data generated by an arbitrary control. Moreover, off-policy IRL can be regarded as a direct learning method, which avoids the identification of system dynamics. In this paper, the performance index function is first given based on the system tracking error and control error. For solving the Hamilton–Jacobi–Bellman (HJB) equation, an off-policy IRL algorithm is proposed. It is proven that the iterative control makes the tracking error system asymptotically stable, and the iterative performance index function is convergent. Simulation study demonstrates the effectiveness of the developed tracking control method. (paper)

  18. Real time reinforcement learning control of dynamic systems applied to an inverted pendulum

    NARCIS (Netherlands)

    van Luenen, W.T.C.; van Luenen, W.T.C.; Stender, J.; Addis, T.

    1990-01-01

    Describes work started in order to investigate the use of neural networks for application in adaptive or learning control systems. Neural networks have learning capabilities and they can be used to realize non-linear mappings. These are attractive features which could make them useful building

  19. Autonomy supported, learner-controlled or system-controlled learning in hypermedia environments and the influence of academic self-regulation style

    NARCIS (Netherlands)

    Gorissen, Chantal; Kester, Liesbeth; Brand-Gruwel, Saskia; Martens, Rob

    2012-01-01

    This study focuses on learning in three different hypermedia environments that either support autonomous learning, learner-controlled learning or system-controlled learning and explores the mediating role of academic self-regulation style ( ASRS; i.e., a macro level of motivation) on learning. This

  20. Autonomy supported, learner-controlled or system-controlled learning in hypermedia environments and the influence of academic self-regulation style

    NARCIS (Netherlands)

    Gorissen, Chantal J J; Kester, Liesbeth; Brand-Gruwel, Saskia; Martens, Rob

    2015-01-01

    This study focuses on learning in three different hypermedia environments that either support autonomous learning, learner-controlled learning or system-controlled learning and explores the mediating role of academic self-regulation style (ASRS; i.e. a macro level of motivation) on learning. This

  1. Autonomy Supported, Learner-Controlled or System-Controlled Learning in Hypermedia Environments and the Influence of Academic Self-Regulation Style

    Science.gov (United States)

    Gorissen, Chantal J. J.; Kester, Liesbeth; Brand-Gruwel, Saskia; Martens, Rob

    2015-01-01

    This study focuses on learning in three different hypermedia environments that either support autonomous learning, learner-controlled learning or system-controlled learning and explores the mediating role of academic self-regulation style (ASRS; i.e. a macro level of motivation) on learning. This research was performed to gain more insight in the…

  2. Developing Learning Tool of Control System Engineering Using Matrix Laboratory Software Oriented on Industrial Needs

    Science.gov (United States)

    Isnur Haryudo, Subuh; Imam Agung, Achmad; Firmansyah, Rifqi

    2018-04-01

    The purpose of this research is to develop learning media of control technique using Matrix Laboratory software with industry requirement approach. Learning media serves as a tool for creating a better and effective teaching and learning situation because it can accelerate the learning process in order to enhance the quality of learning. Control Techniques using Matrix Laboratory software can enlarge the interest and attention of students, with real experience and can grow independent attitude. This research design refers to the use of research and development (R & D) methods that have been modified by multi-disciplinary team-based researchers. This research used Computer based learning method consisting of computer and Matrix Laboratory software which was integrated with props. Matrix Laboratory has the ability to visualize the theory and analysis of the Control System which is an integration of computing, visualization and programming which is easy to use. The result of this instructional media development is to use mathematical equations using Matrix Laboratory software on control system application with DC motor plant and PID (Proportional-Integral-Derivative). Considering that manufacturing in the field of Distributed Control systems (DCSs), Programmable Controllers (PLCs), and Microcontrollers (MCUs) use PID systems in production processes are widely used in industry.

  3. How does a specific learning and memory system in the mammalian brain gain control of behavior?

    Science.gov (United States)

    McDonald, Robert J; Hong, Nancy S

    2013-11-01

    This review addresses a fundamental, yet poorly understood set of issues in systems neuroscience. The issues revolve around conceptualizations of the organization of learning and memory in the mammalian brain. One intriguing, and somewhat popular, conceptualization is the idea that there are multiple learning and memory systems in the mammalian brain and they interact in different ways to influence and/or control behavior. This approach has generated interesting empirical and theoretical work supporting this view. One issue that needs to be addressed is how these systems influence or gain control of voluntary behavior. To address this issue, we clearly specify what we mean by a learning and memory system. We then review two types of processes that might influence which memory system gains control of behavior. One set of processes are external factors that can affect which system controls behavior in a given situation including task parameters like the kind of information available to the subject, types of training experience, and amount of training. The second set of processes are brain mechanisms that might influence what memory system controls behavior in a given situation including executive functions mediated by the prefrontal cortex; switching mechanisms mediated by ascending neurotransmitter systems, the unique role of the hippocampus during learning. The issue of trait differences in control of different learning and memory systems will also be considered in which trait differences in learning and memory function are thought to potentially emerge from differences in level of prefrontal influence, differences in plasticity processes, differences in ascending neurotransmitter control, differential access to effector systems like motivational and motor systems. Finally, we present scenarios in which different mechanisms might interact. This review was conceived to become a jumping off point for new work directed at understanding these issues. The outcome of

  4. Patients with Parkinson's disease learn to control complex systems-an indication for intact implicit cognitive skill learning.

    Science.gov (United States)

    Witt, Karsten; Daniels, Christine; Daniel, Victoria; Schmitt-Eliassen, Julia; Volkmann, Jens; Deuschl, Günther

    2006-01-01

    Implicit memory and learning mechanisms are composed of multiple processes and systems. Previous studies demonstrated a basal ganglia involvement in purely cognitive tasks that form stimulus response habits by reinforcement learning such as implicit classification learning. We will test the basal ganglia influence on two cognitive implicit tasks previously described by Berry and Broadbent, the sugar production task and the personal interaction task. Furthermore, we will investigate the relationship between certain aspects of an executive dysfunction and implicit learning. To this end, we have tested 22 Parkinsonian patients and 22 age-matched controls on two implicit cognitive tasks, in which participants learned to control a complex system. They interacted with the system by choosing an input value and obtaining an output that was related in a complex manner to the input. The objective was to reach and maintain a specific target value across trials (dynamic system learning). The two tasks followed the same underlying complex rule but had different surface appearances. Subsequently, participants performed an executive test battery including the Stroop test, verbal fluency and the Wisconsin card sorting test (WCST). The results demonstrate intact implicit learning in patients, despite an executive dysfunction in the Parkinsonian group. They lead to the conclusion that the basal ganglia system affected in Parkinson's disease does not contribute to the implicit acquisition of a new cognitive skill. Furthermore, the Parkinsonian patients were able to reach a specific goal in an implicit learning context despite impaired goal directed behaviour in the WCST, a classic test of executive functions. These results demonstrate a functional independence of implicit cognitive skill learning and certain aspects of executive functions.

  5. Using Feedback Error Learning for Control of Electro Hydraulic Servo System by Laguerre

    Directory of Open Access Journals (Sweden)

    Amir Reza Zare Bidaki

    2014-01-01

    Full Text Available In this paper, a new Laguerre controller is proposed to control the electro hydraulic servo system. The proposed controller uses feedback error learning method and leads to significantly improve performance in terms of settling time and amplitude of control signal rather than other controllers. All derived results are validated by simulation of nonlinear mathematical model of the system. The simulation results show the advantages of the proposed method for improved control in terms of both settling time and amplitude of control signal.

  6. Turbine Control System Replacement at NPP NEK; System Specifics, Project Experience and Lessons Learned

    International Nuclear Information System (INIS)

    Mandic, D.; Zilavy, M. J.

    2010-01-01

    constitutes only of soft panels or monitor graphics (all MCB - Main Control Board and its controls are available as graphic images on workstations), while the HMI for FG KFSS includes full scope replica of NEK MCR and MCB. The new PDEH system was installed on two KFSS platforms (BG and FG) in October-November, 2008; pre-outage or on-line field installation work was performed in the January-March 2009 time frame; while the old DEH Mod II was decommissioned and the new plant PDEH system was installed during the outage in April, 2009 and tested with the plant on line in May, 2009. PDEH system improvements and specifics compared to the old DEH system and compared to other similar references will be presented and the most interesting project experience and lessons learned will also be discussed in the paper.(author).

  7. Consensus-based distributed cooperative learning from closed-loop neural control systems.

    Science.gov (United States)

    Chen, Weisheng; Hua, Shaoyong; Zhang, Huaguang

    2015-02-01

    In this paper, the neural tracking problem is addressed for a group of uncertain nonlinear systems where the system structures are identical but the reference signals are different. This paper focuses on studying the learning capability of neural networks (NNs) during the control process. First, we propose a novel control scheme called distributed cooperative learning (DCL) control scheme, by establishing the communication topology among adaptive laws of NN weights to share their learned knowledge online. It is further proved that if the communication topology is undirected and connected, all estimated weights of NNs can converge to small neighborhoods around their optimal values over a domain consisting of the union of all state orbits. Second, as a corollary it is shown that the conclusion on the deterministic learning still holds in the decentralized adaptive neural control scheme where, however, the estimated weights of NNs just converge to small neighborhoods of the optimal values along their own state orbits. Thus, the learned controllers obtained by DCL scheme have the better generalization capability than ones obtained by decentralized learning method. A simulation example is provided to verify the effectiveness and advantages of the control schemes proposed in this paper.

  8. Interacting Learning Processes during Skill Acquisition: Learning to control with gradually changing system dynamics.

    Science.gov (United States)

    Ludolph, Nicolas; Giese, Martin A; Ilg, Winfried

    2017-10-16

    There is increasing evidence that sensorimotor learning under real-life conditions relies on a composition of several learning processes. Nevertheless, most studies examine learning behaviour in relation to one specific learning mechanism. In this study, we examined the interaction between reward-based skill acquisition and motor adaptation to changes of object dynamics. Thirty healthy subjects, split into two groups, acquired the skill of balancing a pole on a cart in virtual reality. In one group, we gradually increased the gravity, making the task easier in the beginning and more difficult towards the end. In the second group, subjects had to acquire the skill on the maximum, most difficult gravity level. We hypothesized that the gradual increase in gravity during skill acquisition supports learning despite the necessary adjustments to changes in cart-pole dynamics. We found that the gradual group benefits from the slow increment, although overall improvement was interrupted by the changes in gravity and resulting system dynamics, which caused short-term degradations in performance and timing of actions. In conclusion, our results deliver evidence for an interaction of reward-based skill acquisition and motor adaptation processes, which indicates the importance of both processes for the development of optimized skill acquisition schedules.

  9. Iterative Learning Control design for uncertain and time-windowed systems

    NARCIS (Netherlands)

    Wijdeven, van de J.J.M.

    2008-01-01

    Iterative Learning Control (ILC) is a control strategy capable of dramatically increasing the performance of systems that perform batch repetitive tasks. This performance improvement is achieved by iteratively updating the command signal, using measured error data from previous trials, i.e., by

  10. Controlled Experiment Replication in Evaluation of E-Learning System's Educational Influence

    Science.gov (United States)

    Grubisic, Ani; Stankov, Slavomir; Rosic, Marko; Zitko, Branko

    2009-01-01

    We believe that every effectiveness evaluation should be replicated at least in order to verify the original results and to indicate evaluated e-learning system's advantages or disadvantages. This paper presents the methodology for conducting controlled experiment replication, as well as, results of a controlled experiment and an internal…

  11. An e-Learning System with MR for Experiments Involving Circuit Construction to Control a Robot

    Science.gov (United States)

    Takemura, Atsushi

    2016-01-01

    This paper proposes a novel e-Learning system for technological experiments involving electronic circuit-construction and controlling robot motion that are necessary in the field of technology. The proposed system performs automated recognition of circuit images transmitted from individual learners and automatically supplies the learner with…

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

    Science.gov (United States)

    Bosworth, John

    2006-01-01

    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

  13. An open-closed-loop iterative learning control approach for nonlinear switched systems with application to freeway traffic control

    Science.gov (United States)

    Sun, Shu-Ting; Li, Xiao-Dong; Zhong, Ren-Xin

    2017-10-01

    For nonlinear switched discrete-time systems with input constraints, this paper presents an open-closed-loop iterative learning control (ILC) approach, which includes a feedforward ILC part and a feedback control part. Under a given switching rule, the mathematical induction is used to prove the convergence of ILC tracking error in each subsystem. It is demonstrated that the convergence of ILC tracking error is dependent on the feedforward control gain, but the feedback control can speed up the convergence process of ILC by a suitable selection of feedback control gain. A switched freeway traffic system is used to illustrate the effectiveness of the proposed ILC law.

  14. Robust Monotonically Convergent Iterative Learning Control for Discrete-Time Systems via Generalized KYP Lemma

    Directory of Open Access Journals (Sweden)

    Jian Ding

    2014-01-01

    Full Text Available This paper addresses the problem of P-type iterative learning control for a class of multiple-input multiple-output linear discrete-time systems, whose aim is to develop robust monotonically convergent control law design over a finite frequency range. It is shown that the 2 D iterative learning control processes can be taken as 1 D state space model regardless of relative degree. With the generalized Kalman-Yakubovich-Popov lemma applied, it is feasible to describe the monotonically convergent conditions with the help of linear matrix inequality technique and to develop formulas for the control gain matrices design. An extension to robust control law design against systems with structured and polytopic-type uncertainties is also considered. Two numerical examples are provided to validate the feasibility and effectiveness of the proposed method.

  15. Request Stream Control for the Access to Broadband Multimedia Educational Resources in the Distance Learning System

    Directory of Open Access Journals (Sweden)

    Irina Pavlovna Bolodurina

    2013-10-01

    Full Text Available This article presents a model of queuing system for broadband multimedia educational resources, as well as a model of access to a hybrid cloud system storage. These models are used to enhance the efficiency of computing resources in a distance learning system. An additional OpenStack control module has been developed to achieve the distribution of request streams and balance the load between cloud nodes.

  16. A neural learning classifier system with self-adaptive constructivism for mobile robot control.

    Science.gov (United States)

    Hurst, Jacob; Bull, Larry

    2006-01-01

    For artificial entities to achieve true autonomy and display complex lifelike behavior, they will need to exploit appropriate adaptable learning algorithms. In this context adaptability implies flexibility guided by the environment at any given time and an open-ended ability to learn appropriate behaviors. This article examines the use of constructivism-inspired mechanisms within a neural learning classifier system architecture that exploits parameter self-adaptation as an approach to realize such behavior. The system uses a rule structure in which each rule is represented by an artificial neural network. It is shown that appropriate internal rule complexity emerges during learning at a rate controlled by the learner and that the structure indicates underlying features of the task. Results are presented in simulated mazes before moving to a mobile robot platform.

  17. Alignment Condition-Based Robust Adaptive Iterative Learning Control of Uncertain Robot System

    Directory of Open Access Journals (Sweden)

    Guofeng Tong

    2014-04-01

    Full Text Available This paper proposes an adaptive iterative learning control strategy integrated with saturation-based robust control for uncertain robot system in presence of modelling uncertainties, unknown parameter, and external disturbance under alignment condition. An important merit is that it achieves adaptive switching of gain matrix both in conventional PD-type feedforward control and robust adaptive control in the iteration domain simultaneously. The analysis of convergence of proposed control law is based on Lyapunov's direct method under alignment initial condition. Simulation results demonstrate the faster learning rate and better robust performance with proposed algorithm by comparing with other existing robust controllers. The actual experiment on three-DOF robot manipulator shows its better practical effectiveness.

  18. Application of machine learning and expert systems to Statistical Process Control (SPC) chart interpretation

    Science.gov (United States)

    Shewhart, Mark

    1991-01-01

    Statistical Process Control (SPC) charts are one of several tools used in quality control. Other tools include flow charts, histograms, cause and effect diagrams, check sheets, Pareto diagrams, graphs, and scatter diagrams. A control chart is simply a graph which indicates process variation over time. The purpose of drawing a control chart is to detect any changes in the process signalled by abnormal points or patterns on the graph. The Artificial Intelligence Support Center (AISC) of the Acquisition Logistics Division has developed a hybrid machine learning expert system prototype which automates the process of constructing and interpreting control charts.

  19. Biomechanical Reconstruction Using the Tacit Learning System: Intuitive Control of Prosthetic Hand Rotation.

    Science.gov (United States)

    Oyama, Shintaro; Shimoda, Shingo; Alnajjar, Fady S K; Iwatsuki, Katsuyuki; Hoshiyama, Minoru; Tanaka, Hirotaka; Hirata, Hitoshi

    2016-01-01

    Background: For mechanically reconstructing human biomechanical function, intuitive proportional control, and robustness to unexpected situations are required. Particularly, creating a functional hand prosthesis is a typical challenge in the reconstruction of lost biomechanical function. Nevertheless, currently available control algorithms are in the development phase. The most advanced algorithms for controlling multifunctional prosthesis are machine learning and pattern recognition of myoelectric signals. Despite the increase in computational speed, these methods cannot avoid the requirement of user consciousness and classified separation errors. "Tacit Learning System" is a simple but novel adaptive control strategy that can self-adapt its posture to environment changes. We introduced the strategy in the prosthesis rotation control to achieve compensatory reduction, as well as evaluated the system and its effects on the user. Methods: We conducted a non-randomized study involving eight prosthesis users to perform a bar relocation task with/without Tacit Learning System support. Hand piece and body motions were recorded continuously with goniometers, videos, and a motion-capture system. Findings: Reduction in the participants' upper extremity rotatory compensation motion was monitored during the relocation task in all participants. The estimated profile of total body energy consumption improved in five out of six participants. Interpretation: Our system rapidly accomplished nearly natural motion without unexpected errors. The Tacit Learning System not only adapts human motions but also enhances the human ability to adapt to the system quickly, while the system amplifies compensation generated by the residual limb. The concept can be extended to various situations for reconstructing lost functions that can be compensated.

  20. Lessons learned in digital upgrade projects digital control system implementation at US nuclear power stations

    International Nuclear Information System (INIS)

    Kelley, S.; Bolian, T. W.

    2006-01-01

    AREVA NP has gained significant experience during the past five years in digital upgrades at operating nuclear power stations in the US. Plants are seeking modernization with digital technology to address obsolescence, spare parts availability, vendor support, increasing age-related failures and diminished reliability. New systems offer improved reliability and functionality, and decreased maintenance requirements. Significant lessons learned have been identified relating to the areas of licensing, equipment qualification, software quality assurance and other topics specific to digital controls. Digital control systems have been installed in non safety-related control applications at many utilities within the last 15 years. There have also been a few replacements of small safety-related systems with digital technology. Digital control systems are proving to be reliable, accurate, and easy to maintain. Digital technology is gaining acceptance and momentum with both utilities and regulatory agencies based upon the successes of these installations. Also, new plants are being designed with integrated digital control systems. To support plant life extension and address obsolescence of critical components, utilities are beginning to install digital technology for primary safety-system replacement. AREVA NP analyzed operating experience and lessons learned from its own digital upgrade projects as well as industry-wide experience to identify key issues that should be considered when implementing digital controls in nuclear power stations

  1. Composite Intelligent Learning Control of Strict-Feedback Systems With Disturbance.

    Science.gov (United States)

    Xu, Bin; Sun, Fuchun

    2018-02-01

    This paper addresses the dynamic surface control of uncertain nonlinear systems on the basis of composite intelligent learning and disturbance observer in presence of unknown system nonlinearity and time-varying disturbance. The serial-parallel estimation model with intelligent approximation and disturbance estimation is built to obtain the prediction error and in this way the composite law for weights updating is constructed. The nonlinear disturbance observer is developed using intelligent approximation information while the disturbance estimation is guaranteed to converge to a bounded compact set. The highlight is that different from previous work directly toward asymptotic stability, the transparency of the intelligent approximation and disturbance estimation is included in the control scheme. The uniformly ultimate boundedness stability is analyzed via Lyapunov method. Through simulation verification, the composite intelligent learning with disturbance observer can efficiently estimate the effect caused by system nonlinearity and disturbance while the proposed approach obtains better performance with higher accuracy.

  2. The Roles of Feedback and Feedforward as Humans Learn to Control Unknown Dynamic Systems.

    Science.gov (United States)

    Zhang, Xingye; Wang, Shaoqian; Hoagg, Jesse B; Seigler, T Michael

    2018-02-01

    We present results from an experiment in which human subjects interact with an unknown dynamic system 40 times during a two-week period. During each interaction, subjects are asked to perform a command-following (i.e., pursuit tracking) task. Each subject's performance at that task improves from the first trial to the last trial. For each trial, we use subsystem identification to estimate each subject's feedforward (or anticipatory) control, feedback (or reactive) control, and feedback time delay. Over the 40 trials, the magnitudes of the identified feedback controllers and the identified feedback time delays do not change significantly. In contrast, the identified feedforward controllers do change significantly. By the last trial, the average identified feedforward controller approximates the inverse of the dynamic system. This observation provides evidence that a fundamental component of human learning is updating the anticipatory control until it models the inverse dynamics.

  3. Selected Flight Test Results for Online Learning Neural Network-Based Flight Control System

    Science.gov (United States)

    Williams-Hayes, Peggy S.

    2004-01-01

    The NASA F-15 Intelligent Flight Control System project team developed a series of flight control concepts designed to demonstrate neural network-based adaptive controller benefits, with the objective to develop and flight-test control systems using neural network technology to optimize aircraft performance under nominal conditions and stabilize the aircraft under failure conditions. This report presents flight-test results for an adaptive controller using stability and control derivative values from an online learning neural network. A dynamic cell structure neural network is used in conjunction with a real-time parameter identification algorithm to estimate aerodynamic stability and control derivative increments to baseline aerodynamic derivatives in flight. This open-loop flight test set was performed in preparation for a future phase in which the learning neural network and parameter identification algorithm output would provide the flight controller with aerodynamic stability and control derivative updates in near real time. Two flight maneuvers are analyzed - pitch frequency sweep and automated flight-test maneuver designed to optimally excite the parameter identification algorithm in all axes. Frequency responses generated from flight data are compared to those obtained from nonlinear simulation runs. Flight data examination shows that addition of flight-identified aerodynamic derivative increments into the simulation improved aircraft pitch handling qualities.

  4. Learned parametrized dynamic movement primitives with shared synergies for controlling robotic and musculoskeletal systems

    Directory of Open Access Journals (Sweden)

    Elmar eRückert

    2013-10-01

    Full Text Available A salient feature of human motor skill learning is the ability to exploitsimilarities across related tasks.In biological motor control, it has been hypothesized that muscle synergies,coherent activations of groups of muscles, allow for exploiting shared knowledge.Recent studies have shown that a rich set of complex motor skills can be generated bya combination of a small number of muscle synergies.In robotics, dynamic movement primitives are commonlyused for motor skill learning. This machine learning approach implements a stable attractor systemthat facilitates learning and it can be used in high-dimensional continuous spaces. However, it does not allow for reusing shared knowledge, i.e. for each task an individual set of parameters has to be learned.We propose a novel movement primitive representationthat employs parametrized basis functions, which combines the benefits of muscle synergiesand dynamic movement primitives. For each task asuperposition of synergies modulates a stable attractor system.This approach leads to a compact representation of multiple motor skills andat the same time enables efficient learning in high-dimensional continuous systems.The movement representation supports discrete and rhythmic movements andin particular includes the dynamic movement primitive approach as a special case.We demonstrate the feasibility of the movement representation in three multi-task learning simulated scenarios.First, the characteristics of the proposed representation are illustrated in a point-mass task.Second, in complex humanoid walking experiments,multiple walking patterns with different step heights are learned robustly and efficiently.Finally, in a multi-directional reaching task simulated with a musculoskeletal modelof the human arm, we show how the proposed movement primitives can be used tolearn appropriate muscle excitation patterns and to generalize effectively to new reaching skills.

  5. Event-Triggered Distributed Control of Nonlinear Interconnected Systems Using Online Reinforcement Learning With Exploration.

    Science.gov (United States)

    Narayanan, Vignesh; Jagannathan, Sarangapani

    2017-09-07

    In this paper, a distributed control scheme for an interconnected system composed of uncertain input affine nonlinear subsystems with event triggered state feedback is presented by using a novel hybrid learning scheme-based approximate dynamic programming with online exploration. First, an approximate solution to the Hamilton-Jacobi-Bellman equation is generated with event sampled neural network (NN) approximation and subsequently, a near optimal control policy for each subsystem is derived. Artificial NNs are utilized as function approximators to develop a suite of identifiers and learn the dynamics of each subsystem. The NN weight tuning rules for the identifier and event-triggering condition are derived using Lyapunov stability theory. Taking into account, the effects of NN approximation of system dynamics and boot-strapping, a novel NN weight update is presented to approximate the optimal value function. Finally, a novel strategy to incorporate exploration in online control framework, using identifiers, is introduced to reduce the overall cost at the expense of additional computations during the initial online learning phase. System states and the NN weight estimation errors are regulated and local uniformly ultimately bounded results are achieved. The analytical results are substantiated using simulation studies.

  6. Development of a Computer-aided Learning System for Graphical Analysis of Continuous-Time Control Systems

    Directory of Open Access Journals (Sweden)

    J. F. Opadiji

    2010-06-01

    Full Text Available We present the development and deployment process of a computer-aided learning tool which serves as a training aid for undergraduate control engineering courses. We show the process of algorithm construction and implementation of the software which is also aimed at teaching software development at undergraduate level. The scope of this project is limited to graphical analysis of continuous-time control systems.

  7. Procedural learning during declarative control.

    Science.gov (United States)

    Crossley, Matthew J; Ashby, F Gregory

    2015-09-01

    There is now abundant evidence that human learning and memory are governed by multiple systems. As a result, research is now turning to the next question of how these putative systems interact. For instance, how is overall control of behavior coordinated, and does learning occur independently within systems regardless of what system is in control? Behavioral, neuroimaging, and neuroscience data are somewhat mixed with respect to these questions. Human neuroimaging and animal lesion studies suggest independent learning and are mostly agnostic with respect to control. Human behavioral studies suggest active inhibition of behavioral output but have little to say regarding learning. The results of two perceptual category-learning experiments are described that strongly suggest that procedural learning does occur while the explicit system is in control of behavior and that this learning might be just as good as if the procedural system was controlling the response. These results are consistent with the idea that declarative memory systems inhibit the ability of the procedural system to access motor output systems but do not prevent procedural learning. (c) 2015 APA, all rights reserved).

  8. Reinforcement learning for adaptive optimal control of unknown continuous-time nonlinear systems with input constraints

    Science.gov (United States)

    Yang, Xiong; Liu, Derong; Wang, Ding

    2014-03-01

    In this paper, an adaptive reinforcement learning-based solution is developed for the infinite-horizon optimal control problem of constrained-input continuous-time nonlinear systems in the presence of nonlinearities with unknown structures. Two different types of neural networks (NNs) are employed to approximate the Hamilton-Jacobi-Bellman equation. That is, an recurrent NN is constructed to identify the unknown dynamical system, and two feedforward NNs are used as the actor and the critic to approximate the optimal control and the optimal cost, respectively. Based on this framework, the action NN and the critic NN are tuned simultaneously, without the requirement for the knowledge of system drift dynamics. Moreover, by using Lyapunov's direct method, the weights of the action NN and the critic NN are guaranteed to be uniformly ultimately bounded, while keeping the closed-loop system stable. To demonstrate the effectiveness of the present approach, simulation results are illustrated.

  9. Sensitivity-based self-learning fuzzy logic control for a servo system

    NARCIS (Netherlands)

    Balenovic, M.

    1998-01-01

    Describes an experimental verification of a self-learning fuzzy logic controller (SLFLC). The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model related to the fuzzy controller parameters. The effectiveness of the proposed controller has been

  10. A Reinforcement Learning Approach to Call Admission Control in HAPS Communication System

    Directory of Open Access Journals (Sweden)

    Ni Shu Yan

    2017-01-01

    Full Text Available The large changing of link capacity and number of users caused by the movement of both platform and users in communication system based on high altitude platform station (HAPS will resulting in high dropping rate of handover and reduce resource utilization. In order to solve these problems, this paper proposes an adaptive call admission control strategy based on reinforcement learning approach. The goal of this strategy is to maximize long-term gains of system, with the introduction of cross-layer interaction and the service downgraded. In order to access different traffics adaptively, the access utility of handover traffics and new call traffics is designed in different state of communication system. Numerical simulation result shows that the proposed call admission control strategy can enhance bandwidth resource utilization and the performances of handover traffics.

  11. A model reference and sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

    NARCIS (Netherlands)

    Kovacic, Z.; Bogdan, S.; Balenovic, M.

    1999-01-01

    In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model

  12. Reinforcement learning controller design for affine nonlinear discrete-time systems using online approximators.

    Science.gov (United States)

    Yang, Qinmin; Jagannathan, Sarangapani

    2012-04-01

    In this paper, reinforcement learning state- and output-feedback-based adaptive critic controller designs are proposed by using the online approximators (OLAs) for a general multi-input and multioutput affine unknown nonlinear discretetime systems in the presence of bounded disturbances. The proposed controller design has two entities, an action network that is designed to produce optimal signal and a critic network that evaluates the performance of the action network. The critic estimates the cost-to-go function which is tuned online using recursive equations derived from heuristic dynamic programming. Here, neural networks (NNs) are used both for the action and critic whereas any OLAs, such as radial basis functions, splines, fuzzy logic, etc., can be utilized. For the output-feedback counterpart, an additional NN is designated as the observer to estimate the unavailable system states, and thus, separation principle is not required. The NN weight tuning laws for the controller schemes are also derived while ensuring uniform ultimate boundedness of the closed-loop system using Lyapunov theory. Finally, the effectiveness of the two controllers is tested in simulation on a pendulum balancing system and a two-link robotic arm system.

  13. Learning-Based Adaptive Optimal Tracking Control of Strict-Feedback Nonlinear Systems.

    Science.gov (United States)

    Gao, Weinan; Jiang, Zhong-Ping; Weinan Gao; Zhong-Ping Jiang; Gao, Weinan; Jiang, Zhong-Ping

    2018-06-01

    This paper proposes a novel data-driven control approach to address the problem of adaptive optimal tracking for a class of nonlinear systems taking the strict-feedback form. Adaptive dynamic programming (ADP) and nonlinear output regulation theories are integrated for the first time to compute an adaptive near-optimal tracker without any a priori knowledge of the system dynamics. Fundamentally different from adaptive optimal stabilization problems, the solution to a Hamilton-Jacobi-Bellman (HJB) equation, not necessarily a positive definite function, cannot be approximated through the existing iterative methods. This paper proposes a novel policy iteration technique for solving positive semidefinite HJB equations with rigorous convergence analysis. A two-phase data-driven learning method is developed and implemented online by ADP. The efficacy of the proposed adaptive optimal tracking control methodology is demonstrated via a Van der Pol oscillator with time-varying exogenous signals.

  14. Reinforcement learning design-based adaptive tracking control with less learning parameters for nonlinear discrete-time MIMO systems.

    Science.gov (United States)

    Liu, Yan-Jun; Tang, Li; Tong, Shaocheng; Chen, C L Philip; Li, Dong-Juan

    2015-01-01

    Based on the neural network (NN) approximator, an online reinforcement learning algorithm is proposed for a class of affine multiple input and multiple output (MIMO) nonlinear discrete-time systems with unknown functions and disturbances. In the design procedure, two networks are provided where one is an action network to generate an optimal control signal and the other is a critic network to approximate the cost function. An optimal control signal and adaptation laws can be generated based on two NNs. In the previous approaches, the weights of critic and action networks are updated based on the gradient descent rule and the estimations of optimal weight vectors are directly adjusted in the design. Consequently, compared with the existing results, the main contributions of this paper are: 1) only two parameters are needed to be adjusted, and thus the number of the adaptation laws is smaller than the previous results and 2) the updating parameters do not depend on the number of the subsystems for MIMO systems and the tuning rules are replaced by adjusting the norms on optimal weight vectors in both action and critic networks. It is proven that the tracking errors, the adaptation laws, and the control inputs are uniformly bounded using Lyapunov analysis method. The simulation examples are employed to illustrate the effectiveness of the proposed algorithm.

  15. Discrete-time online learning control for a class of unknown nonaffine nonlinear systems using reinforcement learning.

    Science.gov (United States)

    Yang, Xiong; Liu, Derong; Wang, Ding; Wei, Qinglai

    2014-07-01

    In this paper, a reinforcement-learning-based direct adaptive control is developed to deliver a desired tracking performance for a class of discrete-time (DT) nonlinear systems with unknown bounded disturbances. We investigate multi-input-multi-output unknown nonaffine nonlinear DT systems and employ two neural networks (NNs). By using Implicit Function Theorem, an action NN is used to generate the control signal and it is also designed to cancel the nonlinearity of unknown DT systems, for purpose of utilizing feedback linearization methods. On the other hand, a critic NN is applied to estimate the cost function, which satisfies the recursive equations derived from heuristic dynamic programming. The weights of both the action NN and the critic NN are directly updated online instead of offline training. By utilizing Lyapunov's direct method, the closed-loop tracking errors and the NN estimated weights are demonstrated to be uniformly ultimately bounded. Two numerical examples are provided to show the effectiveness of the present approach. Copyright © 2014 Elsevier Ltd. All rights reserved.

  16. The information system of learning quality control in higher education institutions: achievements and problems of European universities

    Directory of Open Access Journals (Sweden)

    Orekhova Elena

    2016-01-01

    Full Text Available The article deals with the main trends in the development of the system of learning quality control connected with the European integration of higher education and the democratization of education. The authors analyze the state of information systems of learning quality control existing in European higher education and identify their strong and weak points. The authors show that in the learning process universities actively use innovative analytic methods as well as modern means of collecting, storing and transferring information that ensure the successful management of such a complex object as the university of the 21st century.

  17. From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

    Science.gov (United States)

    Grossberg, Stephen

    2015-09-24

    This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory

  18. Evolutionary Acquisition of the Global Command and Control System: Lessons Learned

    National Research Council Canada - National Science Library

    Wallis, Johnathan

    1998-01-01

    This paper summarizes a "lessons learned" study that reviews DoD's approach to managing the GCCS program on behalf on the Assistant Secretary of Defense for Command, Control, Communications, and Intelligence (ASD/C3I...

  19. Interorganizational learning systems

    DEFF Research Database (Denmark)

    Hjalager, Anne-Mette

    1999-01-01

    The occurrence of organizational and interorganizational learning processes is not only the result of management endeavors. Industry structures and market related issues have substantial spill-over effects. The article reviews literature, and it establishes a learning model in which elements from...... organizational environments are included into a systematic conceptual framework. The model allows four types of learning to be identified: P-learning (professional/craft systems learning), T-learning (technology embedded learning), D-learning (dualistic learning systems, where part of the labor force is exclude...... from learning), and S-learning (learning in social networks or clans). The situation related to service industries illustrates the typology....

  20. Optimization and control of a continuous stirred tank fermenter using learning system

    Energy Technology Data Exchange (ETDEWEB)

    Thibault, J [Dept. of Chemical Engineering, Laval Univ., Quebec City, PQ (Canada); Najim, K [CNRS, URA 192, GRECO SARTA, Ecole Nationale Superieure d' Ingenieurs de Genie Chimique, 31 - Toulouse (France)

    1993-05-01

    A variable structure learning automaton is used as an optimization and control of a continuous stirred tank fermenter. The alogrithm requires no modelling of the process. The use of appropriate learning rules enables to locate the optimum dilution rate in order to maximize an objective cost function. It is shown that a hierarchical structure of automata can adapt to environmental changes and can also modify efficiently the domain of variation of the control variable in order to encompass the optimum value. (orig.)

  1. Feedback error learning controller for functional electrical stimulation assistance in a hybrid robotic system for reaching rehabilitation

    Directory of Open Access Journals (Sweden)

    Francisco Resquín

    2016-07-01

    Full Text Available Hybrid robotic systems represent a novel research field, where functional electrical stimulation (FES is combined with a robotic device for rehabilitation of motor impairment. Under this approach, the design of robust FES controllers still remains an open challenge. In this work, we aimed at developing a learning FES controller to assist in the performance of reaching movements in a simple hybrid robotic system setting. We implemented a Feedback Error Learning (FEL control strategy consisting of a feedback PID controller and a feedforward controller based on a neural network. A passive exoskeleton complemented the FES controller by compensating the effects of gravity. We carried out experiments with healthy subjects to validate the performance of the system. Results show that the FEL control strategy is able to adjust the FES intensity to track the desired trajectory accurately without the need of a previous mathematical model.

  2. Scheduled power tracking control of the wind-storage hybrid system based on the reinforcement learning theory

    Science.gov (United States)

    Li, Ze

    2017-09-01

    In allusion to the intermittency and uncertainty of the wind electricity, energy storage and wind generator are combined into a hybrid system to improve the controllability of the output power. A scheduled power tracking control method is proposed based on the reinforcement learning theory and Q-learning algorithm. In this method, the state space of the environment is formed with two key factors, i.e. the state of charge of the energy storage and the difference value between the actual wind power and scheduled power, the feasible action is the output power of the energy storage, and the corresponding immediate rewarding function is designed to reflect the rationality of the control action. By interacting with the environment and learning from the immediate reward, the optimal control strategy is gradually formed. After that, it could be applied to the scheduled power tracking control of the hybrid system. Finally, the rationality and validity of the method are verified through simulation examples.

  3. Controlling the chaotic discrete-Hénon system using a feedforward neural network with an adaptive learning rate

    OpenAIRE

    GÖKCE, Kürşad; UYAROĞLU, Yılmaz

    2013-01-01

    This paper proposes a feedforward neural network-based control scheme to control the chaotic trajectories of a discrete-Hénon map in order to stay within an acceptable distance from the stable fixed point. An adaptive learning back propagation algorithm with online training is employed to improve the effectiveness of the proposed method. The simulation study carried in the discrete-Hénon system verifies the validity of the proposed control system.

  4. Development of Remote Monitoring and a Control System Based on PLC and WebAccess for Learning Mechatronics

    OpenAIRE

    Wen-Jye Shyr; Te-Jen Su; Chia-Ming Lin

    2013-01-01

    This study develops a novel method for learning mechatronics using remote monitoring and control, based on a programmable logic controller (PLC) and WebAccess. A mechatronics module, a Web‐CAM and a PLC were integrated with WebAccess software to organize a remote laboratory. The proposed system enables users to access the Internet for remote monitoring and control of the mechatronics module via a web browser, thereby enhancing work flexibility by enabling personnel to control mechatronics equ...

  5. International Space Station Passive Thermal Control System Analysis, Top Ten Lessons-Learned

    Science.gov (United States)

    Iovine, John

    2011-01-01

    The International Space Station (ISS) has been on-orbit for over 10 years, and there have been numerous technical challenges along the way from design to assembly to on-orbit anomalies and repairs. The Passive Thermal Control System (PTCS) management team has been a key player in successfully dealing with these challenges. The PTCS team performs thermal analysis in support of design and verification, launch and assembly constraints, integration, sustaining engineering, failure response, and model validation. This analysis is a significant body of work and provides a unique opportunity to compile a wealth of real world engineering and analysis knowledge and the corresponding lessons-learned. The analysis lessons encompass the full life cycle of flight hardware from design to on-orbit performance and sustaining engineering. These lessons can provide significant insight for new projects and programs. Key areas to be presented include thermal model fidelity, verification methods, analysis uncertainty, and operations support.

  6. Action Control, L2 Motivational Self System, and Motivated Learning Behavior in a Foreign Language Learning Context

    Science.gov (United States)

    Khany, Reza; Amiri, Majid

    2018-01-01

    Theoretical developments in second or foreign language motivation research have led to a better understanding of the convoluted nature of motivation in the process of language acquisition. Among these theories, action control theory has recently shown a good deal of explanatory power in second language learning contexts and in the presence of…

  7. Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

    Science.gov (United States)

    Wang, W.; Wang, D.; Peng, Z. H.

    2017-09-01

    Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.

  8. Elevator Group Supervisory Control System Using Genetic Network Programming with Macro Nodes and Reinforcement Learning

    Science.gov (United States)

    Zhou, Jin; Yu, Lu; Mabu, Shingo; Hirasawa, Kotaro; Hu, Jinglu; Markon, Sandor

    Elevator Group Supervisory Control System (EGSCS) is a very large scale stochastic dynamic optimization problem. Due to its vast state space, significant uncertainty and numerous resource constraints such as finite car capacities and registered hall/car calls, it is hard to manage EGSCS using conventional control methods. Recently, many solutions for EGSCS using Artificial Intelligence (AI) technologies have been reported. Genetic Network Programming (GNP), which is proposed as a new evolutionary computation method several years ago, is also proved to be efficient when applied to EGSCS problem. In this paper, we propose an extended algorithm for EGSCS by introducing Reinforcement Learning (RL) into GNP framework, and an improvement of the EGSCS' performances is expected since the efficiency of GNP with RL has been clarified in some other studies like tile-world problem. Simulation tests using traffic flows in a typical office building have been made, and the results show an actual improvement of the EGSCS' performances comparing to the algorithms using original GNP and conventional control methods. Furthermore, as a further study, an importance weight optimization algorithm is employed based on GNP with RL and its efficiency is also verified with the better performances.

  9. Rule-bases construction through self-learning for a table-based Sugeno-Takagi fuzzy logic control system

    Directory of Open Access Journals (Sweden)

    C. Boldisor

    2009-12-01

    Full Text Available A self-learning based methodology for building the rule-base of a fuzzy logic controller (FLC is presented and verified, aiming to engage intelligent characteristics to a fuzzy logic control systems. The methodology is a simplified version of those presented in today literature. Some aspects are intentionally ignored since it rarely appears in control system engineering and a SISO process is considered here. The fuzzy inference system obtained is a table-based Sugeno-Takagi type. System’s desired performance is defined by a reference model and rules are extracted from recorded data, after the correct control actions are learned. The presented algorithm is tested in constructing the rule-base of a fuzzy controller for a DC drive application. System’s performances and method’s viability are analyzed.

  10. A Controller Design with ANFIS Architecture Attendant Learning Ability for SSSC-Based Damping Controller Applied in Single Machine Infinite Bus System

    Directory of Open Access Journals (Sweden)

    A. Khoshsaadat

    2014-09-01

    Full Text Available Static Synchronous Series Compensator (SSSC is a series compensating Flexible AC Transmission System (FACTS controller for maintaining to the power flow control on a transmission line by injecting a voltage in quadrature with the line current and in series mode with the line. In this work, an Adaptive Network-based Fuzzy Inference System controller (ANFISC has been proposed for controlling of the SSSC-based damping system and applied to a Single Machine Infinite Bus (SMIB power system. For implementation of the learning process in this controller, we use of the one approach of the learning ability that named as Forward Signal and Backward Error Back-Propagation (FSBEBP method for improving of the system efficiency. This artificial intelligence-based control model leads to a controller with adaptive structure, improved correctness, high damping ability and dynamic performance. System implementation is easy and it requires 49 fuzzy rules for inference engine of the system. As compared with the other complex neuro-fuzzy systems, this controller has medium number of the fuzzy rules and low number of layers, but it has high accuracy. In order to demonstrate of the proposed controller ability, it is simulated and its output compared with that of classic Lead-Lag-based Controller (LLC and PI controller.

  11. Lessons Learned from the Crew Health Care System (CHeCS) Rack 1 Environmental Control and Life Support (ECLS) Design

    Science.gov (United States)

    Williams, David E.

    2006-01-01

    This paper will provide an overview of the International Space Station (ISS) Environmental Control and Life Support (ECLS) design of the Crew Health Care System (CHeCS) Rack 1 and it will document some of the lessons that have been learned to date for the ECLS equipment in this rack.

  12. Open-closed-loop iterative learning control for a class of nonlinear systems with random data dropouts

    Science.gov (United States)

    Cheng, X. Y.; Wang, H. B.; Jia, Y. L.; Dong, YH

    2018-05-01

    In this paper, an open-closed-loop iterative learning control (ILC) algorithm is constructed for a class of nonlinear systems subjecting to random data dropouts. The ILC algorithm is implemented by a networked control system (NCS), where only the off-line data is transmitted by network while the real-time data is delivered in the point-to-point way. Thus, there are two controllers rather than one in the control system, which makes better use of the saved and current information and thereby improves the performance achieved by open-loop control alone. During the transfer of off-line data between the nonlinear plant and the remote controller data dropout occurs randomly and the data dropout rate is modeled as a binary Bernoulli random variable. Both measurement and control data dropouts are taken into consideration simultaneously. The convergence criterion is derived based on rigorous analysis. Finally, the simulation results verify the effectiveness of the proposed method.

  13. Oxygen control systems and impurity purification in LBE: Learning from DEMETRA project

    Energy Technology Data Exchange (ETDEWEB)

    Brissonneau, L., E-mail: laurent.brissonneau@cea.fr [CEA/DEN, Cadarache, DTN/STPA/LIPC, F-13108 Saint-Paul-lez-Durance (France); Beauchamp, F.; Morier, O. [CEA/DEN, Cadarache, DTN/STPA/LIPC, F-13108 Saint-Paul-lez-Durance (France); Schroer, C.; Konys, J. [Karlsruher Institut fuer Technologie (KIT), Institut fuer Materialforschung III, Hermann-von-Helmholtz-Platz 1, 76344 Eggenstein-Leopoldshafen (Germany); Kobzova, A.; Di Gabriele, F. [NRI, UJV Husinec-Rez 130, Rez 25068 (Czech Republic); Courouau, J.-L. [CEA/DEN, Saclay, DPC/SCCME/LECNA, F-919191 Gif-sur-Yvette (France)

    2011-08-31

    Operating a system using Lead-Bismuth Eutectic (LBE) requires a control of the dissolved oxygen concentration to avoid corrosion of structural materials and oxide build-up in the coolant. Reliable devices are therefore needed to monitor and adjust the oxygen concentration and to remove impurities during operation. In this article, we describe the learning gained from experiments run in the framework of the DEMETRA project (IP-EUROTRANS 6th FP contract) on the oxygen supply in LBE and on impurity filtration and management in different European facilities. An oxygen control device should supply oxygen in LBE at sufficient rate to compensate loss by surface oxidation, otherwise local dissolution of oxide layers might lead to the loss of steel protection against dissolution. Oxygen can be supplied by gas phase H{sub 2}O or O{sub 2}, or by solid phase, PbO dissolution. Each of these systems has substantial advantages and drawbacks. Considerations are given on devices for large scale facilities. The management of impurities (lead oxides and corrosion products) is also a crucial issue as their presence in the liquid phase or in the aerosols is likely to impair the facility, instrumentation and mechanical devices. To avoid impurity build-up on the long-term, purification of LBE is required to keep the impurity inventory low by trapping oxide and metallic impurities in specific filter units. On the basis of impurities characterisation and experimental results gained through filtration tests in different loops, this paper gives a description of the state-of-art knowledge of LBE purification with different filter media. It is now understood that the nature and behaviour of impurities formed in LBE will change according to the operating modes as well as the method to propose to remove impurities. This experience can be used to validate the basis filtration process, define the operating procedures and evaluate perspectives for the design of purification units for long

  14. Attentional control of associative learning--a possible role of the central cholinergic system.

    Science.gov (United States)

    Pauli, Wolfgang M; O'Reilly, Randall C

    2008-04-02

    How does attention interact with learning? Kruschke [Kruschke, J.K. (2001). Toward a unified Model of Attention in Associative Learning. J. Math. Psychol. 45, 812-863.] proposed a model (EXIT) that captures Mackintosh's [Mackintosh, N.J. (1975). A theory of attention: Variations in the associability of stimuli with reinforcement. Psychological Review, 82(4), 276-298.] framework for attentional modulation of associative learning. We developed a computational model that showed analogous interactions between selective attention and associative learning, but is significantly simplified and, in contrast to EXIT, is motivated by neurophysiological findings. Competition among input representations in the internal representation layer, which increases the contrast between stimuli, is critical for simulating these interactions in human behavior. Furthermore, this competition is modulated in a way that might be consistent with the phasic activation of the central cholinergic system, which modulates activity in sensory cortices. Specifically, phasic increases in acetylcholine can cause increased excitability of both pyramidal excitatory neurons in cortical layers II/III and cortical GABAergic inhibitory interneurons targeting the same pyramidal neurons. These effects result in increased attentional contrast in our model. This model thus represents an initial attempt to link human attentional learning data with underlying neural substrates.

  15. Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

    Science.gov (United States)

    Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

    2017-10-01

    Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

  16. Reinforcement-Learning-Based Robust Controller Design for Continuous-Time Uncertain Nonlinear Systems Subject to Input Constraints.

    Science.gov (United States)

    Liu, Derong; Yang, Xiong; Wang, Ding; Wei, Qinglai

    2015-07-01

    The design of stabilizing controller for uncertain nonlinear systems with control constraints is a challenging problem. The constrained-input coupled with the inability to identify accurately the uncertainties motivates the design of stabilizing controller based on reinforcement-learning (RL) methods. In this paper, a novel RL-based robust adaptive control algorithm is developed for a class of continuous-time uncertain nonlinear systems subject to input constraints. The robust control problem is converted to the constrained optimal control problem with appropriately selecting value functions for the nominal system. Distinct from typical action-critic dual networks employed in RL, only one critic neural network (NN) is constructed to derive the approximate optimal control. Meanwhile, unlike initial stabilizing control often indispensable in RL, there is no special requirement imposed on the initial control. By utilizing Lyapunov's direct method, the closed-loop optimal control system and the estimated weights of the critic NN are proved to be uniformly ultimately bounded. In addition, the derived approximate optimal control is verified to guarantee the uncertain nonlinear system to be stable in the sense of uniform ultimate boundedness. Two simulation examples are provided to illustrate the effectiveness and applicability of the present approach.

  17. Self-Learning Variable Structure Control for a Class of Sensor-Actuator Systems

    Science.gov (United States)

    Chen, Sanfeng; Li, Shuai; Liu, Bo; Lou, Yuesheng; Liang, Yongsheng

    2012-01-01

    Variable structure strategy is widely used for the control of sensor-actuator systems modeled by Euler-Lagrange equations. However, accurate knowledge on the model structure and model parameters are often required for the control design. In this paper, we consider model-free variable structure control of a class of sensor-actuator systems, where only the online input and output of the system are available while the mathematic model of the system is unknown. The problem is formulated from an optimal control perspective and the implicit form of the control law are analytically obtained by using the principle of optimality. The control law and the optimal cost function are explicitly solved iteratively. Simulations demonstrate the effectiveness and the efficiency of the proposed method. PMID:22778633

  18. User's manual of self learning gas puffing system for plasma density control

    International Nuclear Information System (INIS)

    Tanahashi, S.

    1989-04-01

    Pre-programmed gas puffing is often used to get adequet plasma density wave forms in the pulse operating devices for fusion experiments. This method has a defect that preset values have to be adjusted manually in accordance with changes of out gassing rate in successive shots. In order to remove this defect, a self learning system has been developed so as to keep the plasma density close to a given reference waveform. After a few succesive shots, it accomplishes self learning and is ready to keep up with a gradual change of the wall condition. This manual gives the usage of the system and the program list written in BASIC and ASSEMBLER languages. (author)

  19. Automatic Learning of Fine Operating Rules for Online Power System Security Control.

    Science.gov (United States)

    Sun, Hongbin; Zhao, Feng; Wang, Hao; Wang, Kang; Jiang, Weiyong; Guo, Qinglai; Zhang, Boming; Wehenkel, Louis

    2016-08-01

    Fine operating rules for security control and an automatic system for their online discovery were developed to adapt to the development of smart grids. The automatic system uses the real-time system state to determine critical flowgates, and then a continuation power flow-based security analysis is used to compute the initial transfer capability of critical flowgates. Next, the system applies the Monte Carlo simulations to expected short-term operating condition changes, feature selection, and a linear least squares fitting of the fine operating rules. The proposed system was validated both on an academic test system and on a provincial power system in China. The results indicated that the derived rules provide accuracy and good interpretability and are suitable for real-time power system security control. The use of high-performance computing systems enables these fine operating rules to be refreshed online every 15 min.

  20. VTA GABA neurons modulate specific learning behaviours through the control of dopamine and cholinergic systems

    Directory of Open Access Journals (Sweden)

    Meaghan C Creed

    2014-01-01

    Full Text Available The mesolimbic reward system is primarily comprised of the ventral tegmental area (VTA and the nucleus accumbens (NAc as well as their afferent and efferent connections. This circuitry is essential for learning about stimuli associated with motivationally-relevant outcomes. Moreover, addictive drugs affect and remodel this system, which may underlie their addictive properties. In addition to DA neurons, the VTA also contains approximately 30% ɣ-aminobutyric acid (GABA neurons. The task of signalling both rewarding and aversive events from the VTA to the NAc has mostly been ascribed to DA neurons and the role of GABA neurons has been largely neglected until recently. GABA neurons provide local inhibition of DA neurons and also long-range inhibition of projection regions, including the NAc. Here we review studies using a combination of in vivo and ex vivo electrophysiology, pharmacogenetic and optogenetic manipulations that have characterized the functional neuroanatomy of inhibitory circuits in the mesolimbic system, and describe how GABA neurons of the VTA regulate reward and aversion-related learning. We also discuss pharmacogenetic manipulation of this system with benzodiazepines (BDZs, a class of addictive drugs, which act directly on GABAA receptors located on GABA neurons of the VTA. The results gathered with each of these approaches suggest that VTA GABA neurons bi-directionally modulate activity of local DA neurons, underlying reward or aversion at the behavioural level. Conversely, long-range GABA projections from the VTA to the NAc selectively target cholinergic interneurons (CINs to pause their firing and temporarily reduce cholinergic tone in the NAc, which modulates associative learning. Further characterization of inhibitory circuit function within and beyond the VTA is needed in order to fully understand the function of the mesolimbic system under normal and pathological conditions.

  1. JACoW Model learning algorithms for anomaly detection in CERN control systems

    CERN Document Server

    Tilaro, Filippo; Gonzalez-Berges, Manuel; Roshchin, Mikhail; Varela, Fernando

    2018-01-01

    The CERN automation infrastructure consists of over 600 heterogeneous industrial control systems with around 45 million deployed sensors, actuators and control objects. Therefore, it is evident that the monitoring of such huge system represents a challenging and complex task. This paper describes three different mathematical approaches that have been designed and developed to detect anomalies in any of the CERN control systems. Specifically, one of these algorithms is purely based on expert knowledge; the other two mine the historical generated data to create a simple model of the system; this model is then used to detect faulty sensors measurements. The presented methods can be categorized as dynamic unsupervised anomaly detection; “dynamic” since the behaviour of the system and the evolution of its attributes are observed and changing in time. They are “unsupervised” because we are trying to predict faulty events without examples in the data history. So, the described strategies involve monitoring t...

  2. A New Learning Control System for Basketball Free Throws Based on Real Time Video Image Processing and Biofeedback

    Directory of Open Access Journals (Sweden)

    R. Sarang

    2018-02-01

    Full Text Available Shooting free throws plays an important role in basketball. The major problem in performing a correct free throw seems to be inappropriate training. Training is performed offline and it is often not that persistent. The aim of this paper is to consciously modify and control the free throw using biofeedback. Elbow and shoulder dynamics are calculated by an image processing technique equipped with a video image acquisition system. The proposed setup in this paper, named learning control system, is able to quantify and provide feedback of the above parameters in real time as audio signals. Therefore, it yielded to performing a correct learning and conscious control of shooting. Experimental results showed improvements in the free throw shooting style including shot pocket and locked position. The mean values of elbow and shoulder angles were controlled approximately on 89o and 26o, for shot pocket and also these angles were tuned approximately on 180o and 47o respectively for the locked position (closed to the desired pattern of the free throw based on valid FIBA references. Not only the mean values enhanced but also the standard deviations of these angles decreased meaningfully, which shows shooting style convergence and uniformity. Also, in training conditions, the average percentage of making successful free throws increased from about 64% to even 87% after using this setup and in competition conditions the average percentage of successful free throws enhanced about 20%, although using the learning control system may not be the only reason for these outcomes. The proposed system is easy to use, inexpensive, portable and real time applicable.

  3. How to Successfully Renovate a Controls System? - Lessons Learned from the Renovation of the CERN Injectors’ Controls Software

    CERN Document Server

    Kruk, G; Kulikova, O; Lezhebokov, V; Pace, M; Pera Mira, P; Roux, E; Wozniak, J Pawel

    2014-01-01

    Renovation of the control system of the CERN LHC injectors was initiated in 2007 in the scope of the Injector Controls Architecture (InCA) project. One of its main objectives was to homogenize the controls software across CERN accelerators and reuse as much as possible the existing modern sub-systems, such as the settings management used for the LHC. The project team created a platform that would permit coexistence and intercommunication between old and new components via a dedicated gateway, allowing a progressive replacement of the former. Dealing with a heterogeneous environment, with many diverse and interconnected modules, implemented using different technologies and programming languages, the team had to introduce all the modifications in the smoothest possible way, without causing machine downtime. After a brief description of the system architecture, the paper discusses the technical and non-technical sides of the renovation process such as validation and deployment methodology, operational applicatio...

  4. Development of Remote Monitoring and a Control System Based on PLC and WebAccess for Learning Mechatronics

    Directory of Open Access Journals (Sweden)

    Wen-Jye Shyr

    2013-02-01

    Full Text Available This study develops a novel method for learning mechatronics using remote monitoring and control, based on a programmable logic controller (PLC and WebAccess. A mechatronics module, a Web-CAM and a PLC were integrated with WebAccess software to organize a remote laboratory. The proposed system enables users to access the Internet for remote monitoring and control of the mechatronics module via a web browser, thereby enhancing work flexibility by enabling personnel to control mechatronics equipment from a remote location. Mechatronics control and long-distance monitoring were realized by establishing communication between the PLC and WebAccess. Analytical results indicate that the proposed system is feasible. The suitability of this system is demonstrated in the department of industrial education and technology at National Changhua University of Education, Taiwan. Preliminary evaluation of the system was encouraging and has shown that it has achieved success in helping students understand concepts and master remote monitoring and control techniques.

  5. Recommender Systems for Learning

    CERN Document Server

    Manouselis, Nikos; Verbert, Katrien; Duval, Erik

    2013-01-01

    Technology enhanced learning (TEL) aims to design, develop and test sociotechnical innovations that will support and enhance learning practices of both individuals and organisations. It is therefore an application domain that generally covers technologies that support all forms of teaching and learning activities. Since information retrieval (in terms of searching for relevant learning resources to support teachers or learners) is a pivotal activity in TEL, the deployment of recommender systems has attracted increased interest. This brief attempts to provide an introduction to recommender systems for TEL settings, as well as to highlight their particularities compared to recommender systems for other application domains.

  6. Automatic generation control of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization algorithm

    Directory of Open Access Journals (Sweden)

    Rabindra Kumar Sahu

    2016-03-01

    Full Text Available This paper presents the design and analysis of Proportional-Integral-Double Derivative (PIDD controller for Automatic Generation Control (AGC of multi-area power systems with diverse energy sources using Teaching Learning Based Optimization (TLBO algorithm. At first, a two-area reheat thermal power system with appropriate Generation Rate Constraint (GRC is considered. The design problem is formulated as an optimization problem and TLBO is employed to optimize the parameters of the PIDD controller. The superiority of the proposed TLBO based PIDD controller has been demonstrated by comparing the results with recently published optimization technique such as hybrid Firefly Algorithm and Pattern Search (hFA-PS, Firefly Algorithm (FA, Bacteria Foraging Optimization Algorithm (BFOA, Genetic Algorithm (GA and conventional Ziegler Nichols (ZN for the same interconnected power system. Also, the proposed approach has been extended to two-area power system with diverse sources of generation like thermal, hydro, wind and diesel units. The system model includes boiler dynamics, GRC and Governor Dead Band (GDB non-linearity. It is observed from simulation results that the performance of the proposed approach provides better dynamic responses by comparing the results with recently published in the literature. Further, the study is extended to a three unequal-area thermal power system with different controllers in each area and the results are compared with published FA optimized PID controller for the same system under study. Finally, sensitivity analysis is performed by varying the system parameters and operating load conditions in the range of ±25% from their nominal values to test the robustness.

  7. Learning Content Management Systems

    Directory of Open Access Journals (Sweden)

    Tache JURUBESCU

    2008-01-01

    Full Text Available The paper explains the evolution of e-Learning and related concepts and tools and its connection with other concepts such as Knowledge Management, Human Resources Management, Enterprise Resource Planning, and Information Technology. The paper also distinguished Learning Content Management Systems from Learning Management Systems and Content Management Systems used for general web-based content. The newest Learning Content Management System, very expensive and yet very little implemented is one of the best tools that helps us to cope with the realities of the 21st Century in what learning concerns. The debates over how beneficial one or another system is for an organization, can be driven by costs involved, efficiency envisaged, and availability of the product on the market.

  8. Do questions help? The impact of audience response systems on medical student learning: a randomised controlled trial.

    Science.gov (United States)

    Mains, Tyler E; Cofrancesco, Joseph; Milner, Stephen M; Shah, Nina G; Goldberg, Harry

    2015-07-01

    Audience response systems (ARSs) are electronic devices that allow educators to pose questions during lectures and receive immediate feedback on student knowledge. The current literature on the effectiveness of ARSs is contradictory, and their impact on student learning remains unclear. This randomised controlled trial was designed to isolate the impact of ARSs on student learning and students' perception of ARSs during a lecture. First-year medical student volunteers at Johns Hopkins were randomly assigned to either (i) watch a recorded lecture on an unfamiliar topic in which three ARS questions were embedded or (ii) watch the same lecture without the ARS questions. Immediately after the lecture on 5 June 2012, and again 2 weeks later, both groups were asked to complete a questionnaire to assess their knowledge of the lecture content and satisfaction with the learning experience. 92 students participated. The mean (95% CI) initial knowledge assessment score was 7.63 (7.17 to 8.09) for the ARS group (N=45) and 6.39 (5.81 to 6.97) for the control group (N=47), p=0.001. Similarly, the second knowledge assessment mean score was 6.95 (6.38 to 7.52) for the ARS group and 5.88 (5.29 to 6.47) for the control group, p=0.001. The ARS group also reported higher levels of engagement and enjoyment. Embedding three ARS questions within a 30 min lecture increased students' knowledge immediately after the lecture and 2 weeks later. We hypothesise that this increase was due to forced information retrieval by students during the learning process, a form of the testing effect. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

  9. Multiclassifier system with hybrid learning applied to the control of bioprosthetic hand.

    Science.gov (United States)

    Kurzynski, Marek; Krysmann, Maciej; Trajdos, Pawel; Wolczowski, Andrzej

    2016-02-01

    In this paper the problem of recognition of the intended hand movements for the control of bio-prosthetic hand is addressed. The proposed method is based on recognition of electromiographic (EMG) and mechanomiographic (MMG) biosignals using a multiclassifier system (MCS) working in a two-level structure with a dynamic ensemble selection (DES) scheme and original concepts of competence function. Additionally, feedback information coming from bioprosthesis sensors on the correct/incorrect classification is applied to the adjustment of the combining mechanism during MCS operation through adaptive tuning competences of base classifiers depending on their decisions. Three MCS systems operating in decision tree structure and with different tuning algorithms are developed. In the MCS1 system, competence is uniformly allocated to each class belonging to the group indicated by the feedback signal. In the MCS2 system, the modification of competence depends on the node of decision tree at which a correct/incorrect classification is made. In the MCS3 system, the randomized model of classifier and the concept of cross-competence are used in the tuning procedure. Experimental investigations on the real data and computer-simulated procedure of generating feedback signals are performed. In these investigations classification accuracy of the MCS systems developed is compared and furthermore, the MCS systems are evaluated with respect to the effectiveness of the procedure of tuning competence. The results obtained indicate that modification of competence of base classifiers during the working phase essentially improves performance of the MCS system and that this improvement depends on the MCS system and tuning method used. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Evaluation of an e-learning system for diagnosis of gastric lesions using magnifying narrow-band imaging: a multicenter randomized controlled study.

    Science.gov (United States)

    Nakanishi, Hiroyoshi; Doyama, Hisashi; Ishikawa, Hideki; Uedo, Noriya; Gotoda, Takuji; Kato, Mototsugu; Nagao, Shigeaki; Nagami, Yasuaki; Aoyagi, Hiroyuki; Imagawa, Atsushi; Kodaira, Junichi; Mitsui, Shinya; Kobayashi, Nozomu; Muto, Manabu; Takatori, Hajime; Abe, Takashi; Tsujii, Masahiko; Watari, Jiro; Ishiyama, Shuhei; Oda, Ichiro; Ono, Hiroyuki; Kaneko, Kazuhiro; Yokoi, Chizu; Ueo, Tetsuya; Uchita, Kunihisa; Matsumoto, Kenshi; Kanesaka, Takashi; Morita, Yoshinori; Katsuki, Shinichi; Nishikawa, Jun; Inamura, Katsuhisa; Kinjo, Tetsu; Yamamoto, Katsumi; Yoshimura, Daisuke; Araki, Hiroshi; Kashida, Hiroshi; Hosokawa, Ayumu; Mori, Hirohito; Yamashita, Haruhiro; Motohashi, Osamu; Kobayashi, Kazuhiko; Hirayama, Michiaki; Kobayashi, Hiroyuki; Endo, Masaki; Yamano, Hiroo; Murakami, Kazunari; Koike, Tomoyuki; Hirasawa, Kingo; Miyaoka, Youichi; Hamamoto, Hidetaka; Hikichi, Takuto; Hanabata, Norihiro; Shimoda, Ryo; Hori, Shinichiro; Sato, Tadashi; Kodashima, Shinya; Okada, Hiroyuki; Mannami, Tomohiko; Yamamoto, Shojiro; Niwa, Yasumasa; Yashima, Kazuo; Tanabe, Satoshi; Satoh, Hiro; Sasaki, Fumisato; Yamazato, Tetsuro; Ikeda, Yoshiou; Nishisaki, Hogara; Nakagawa, Masahiro; Matsuda, Akio; Tamura, Fumio; Nishiyama, Hitoshi; Arita, Keiko; Kawasaki, Keisuke; Hoppo, Kazushige; Oka, Masashi; Ishihara, Shinichi; Mukasa, Michita; Minamino, Hiroaki; Yao, Kenshi

    2017-10-01

    Background and study aim  Magnifying narrow-band imaging (M-NBI) is useful for the accurate diagnosis of early gastric cancer (EGC). However, acquiring skill at M-NBI diagnosis takes substantial effort. An Internet-based e-learning system to teach endoscopic diagnosis of EGC using M-NBI has been developed. This study evaluated its effectiveness. Participants and methods  This study was designed as a multicenter randomized controlled trial. We recruited endoscopists as participants from all over Japan. After completing Test 1, which consisted of M-NBI images of 40 gastric lesions, participants were randomly assigned to the e-learning or non-e-learning groups. Only the e-learning group was allowed to access the e-learning system. After the e-learning period, both groups received Test 2. The analysis set was participants who scored e-learning group and 197 in the non-e-learning group). After the e-learning period, all 395 completed Test 2. The analysis sets were e-learning group: n = 184; and non-e-learning group: n = 184. The mean Test 1 score was 59.9 % for the e-learning group and 61.7 % for the non-e-learning group. The change in accuracy in Test 2 was significantly higher in the e-learning group than in the non-e-learning group (7.4 points vs. 0.14 points, respectively; P  e-learning system in improving practitioners' capabilities to diagnose EGC using M-NBI.Trial registered at University Hospital Medical Information Network Clinical Trials Registry (UMIN000008569). © Georg Thieme Verlag KG Stuttgart · New York.

  11. Machine learning systems

    Energy Technology Data Exchange (ETDEWEB)

    Forsyth, R

    1984-05-01

    With the dramatic rise of expert systems has come a renewed interest in the fuel that drives them-knowledge. For it is specialist knowledge which gives expert systems their power. But extracting knowledge from human experts in symbolic form has proved arduous and labour-intensive. So the idea of machine learning is enjoying a renaissance. Machine learning is any automatic improvement in the performance of a computer system over time, as a result of experience. Thus a learning algorithm seeks to do one or more of the following: cover a wider range of problems, deliver more accurate solutions, obtain answers more cheaply, and simplify codified knowledge. 6 references.

  12. Voice over Internet Protocol (VoIP) Technology as a Global Learning Tool: Information Systems Success and Control Belief Perspectives

    Science.gov (United States)

    Chen, Charlie C.; Vannoy, Sandra

    2013-01-01

    Voice over Internet Protocol- (VoIP) enabled online learning service providers struggling with high attrition rates and low customer loyalty issues despite VoIP's high degree of system fit for online global learning applications. Effective solutions to this prevalent problem rely on the understanding of system quality, information quality, and…

  13. Design And Planning Of E- Learning EnvironmentE-Education System On Heterogeneous Wireless Network Control System

    Directory of Open Access Journals (Sweden)

    ThandarOo

    2015-06-01

    Full Text Available Abstract The purpose of this research is to provide a more efficient and effective communication method between teacher and student with the use of heterogeneous network. Moreover the effective use of heterogeneous network can be emphasized. The system of e-education can develop utilizing wireless network.The e-Education system can help students to communicate with their teacher more easily and effectively using a heterogeneous wireless network system. In this wireless network system students who are blind or dumb will also be able to communicate and learn from the teacher as normal students can do. All the devices or laptops will be connected on wireless LAN. Even when the teacher is not around he will be able to help his students with their study or give instructions easily by using the mobile phone to send text or voice signal. When the teacher sends information to the dumb student it will be converted into sign language for the student to be able to understand. When the dumb student sends the information to the teacher it will be converted into text for the teacher to understand. For the blind student text instructions from the teacher will be converted into audio signal using text-to-speech conversion.Thus the performance of heterogeneous wireless network model can evaluate by using Robust Optimization Method. Therefore the e-Education systems performance improves by evaluating Robust Optimization Method.

  14. Development of an E-learning System for the Endoscopic Diagnosis of Early Gastric Cancer: An International Multicenter Randomized Controlled Trial.

    Science.gov (United States)

    Yao, K; Uedo, N; Muto, M; Ishikawa, H; Cardona, H J; Filho, E C Castro; Pittayanon, R; Olano, C; Yao, F; Parra-Blanco, A; Ho, S H; Avendano, A G; Piscoya, A; Fedorov, E; Bialek, A P; Mitrakov, A; Caro, L; Gonen, C; Dolwani, S; Farca, A; Cuaresma, L F; Bonilla, J J; Kasetsermwiriya, W; Ragunath, K; Kim, S E; Marini, M; Li, H; Cimmino, D G; Piskorz, M M; Iacopini, F; So, J B; Yamazaki, K; Kim, G H; Ang, T L; Milhomem-Cardoso, D M; Waldbaum, C A; Carvajal, W A Piedra; Hayward, C M; Singh, R; Banerjee, R; Anagnostopoulos, G K; Takahashi, Y

    2016-07-01

    In many countries, gastric cancer is not diagnosed until an advanced stage. An Internet-based e-learning system to improve the ability of endoscopists to diagnose gastric cancer at an early stage was developed and was evaluated for its effectiveness. The study was designed as a randomized controlled trial. After receiving a pre-test, participants were randomly allocated to either an e-learning or non-e-learning group. Only those in the e-learning group gained access to the e-learning system. Two months after the pre-test, both groups received a post-test. The primary endpoint was the difference between the two groups regarding the rate of improvement of their test results. 515 endoscopists from 35 countries were assessed for eligibility, and 332 were enrolled in the study, with 166 allocated to each group. Of these, 151 participants in the e-learning group and 144 in the non-e-learning group were included in the analysis. The mean improvement rate (standard deviation) in the e-learning and non-e-learning groups was 1·24 (0·26) and 1·00 (0·16), respectively (Pe-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039). Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  15. Inclusion of Immersive Virtual Learning Environments and Visual Control Systems to Support the Learning of Students with Asperger Syndrome

    Science.gov (United States)

    Lorenzo, Gonzalo; Pomares, Jorge; Lledo, Asuncion

    2013-01-01

    This paper presents the use of immersive virtual reality systems in the educational intervention with Asperger students. The starting points of this study are features of these students' cognitive style that requires an explicit teaching style supported by visual aids and highly structured environments. The proposed immersive virtual reality…

  16. neural control system

    International Nuclear Information System (INIS)

    Elshazly, A.A.E.

    2002-01-01

    Automatic power stabilization control is the desired objective for any reactor operation , especially, nuclear power plants. A major problem in this area is inevitable gap between a real plant ant the theory of conventional analysis and the synthesis of linear time invariant systems. in particular, the trajectory tracking control of a nonlinear plant is a class of problems in which the classical linear transfer function methods break down because no transfer function can represent the system over the entire operating region . there is a considerable amount of research on the model-inverse approach using feedback linearization technique. however, this method requires a prices plant model to implement the exact linearizing feedback, for nuclear reactor systems, this approach is not an easy task because of the uncertainty in the plant parameters and un-measurable state variables . therefore, artificial neural network (ANN) is used either in self-tuning control or in improving the conventional rule-based exper system.the main objective of this thesis is to suggest an ANN, based self-learning controller structure . this method is capable of on-line reinforcement learning and control for a nuclear reactor with a totally unknown dynamics model. previously, researches are based on back- propagation algorithm . back -propagation (BP), fast back -propagation (FBP), and levenberg-marquardt (LM), algorithms are discussed and compared for reinforcement learning. it is found that, LM algorithm is quite superior

  17. Learn How to Control Asthma

    Science.gov (United States)

    ... Guidelines Asthma & Community Health Learn How to Control Asthma Language: English (US) Español (Spanish) Arabic Chinese Français ... Is Asthma Treated? Select a Language What Is Asthma? Asthma is a disease that affects your lungs. ...

  18. Knowledge Control Model of Distance Learning System “Kherson Virtual University”.

    Directory of Open Access Journals (Sweden)

    H. M. Kravtsov

    2008-06-01

    Full Text Available The results of designing and modeling of distance testing system on the base of international standards IMS, SCORM are represented. Distance testing system “Web-Examiner” is used for the illustration.

  19. A new Dutch building control system : Lessons to be learned from neighbours?

    NARCIS (Netherlands)

    Meijer, F.M.; Visscher, H.J.

    2016-01-01

    Traditionally quality control of construction work in Europe was a governmental responsibility. In most European countries local authority building control were responsible for the issuing of planning or building permits and carried out plan approval, site-inspections and checks on completion of

  20. Reinforcement-learning-based output-feedback control of nonstrict nonlinear discrete-time systems with application to engine emission control.

    Science.gov (United States)

    Shih, Peter; Kaul, Brian C; Jagannathan, Sarangapani; Drallmeier, James A

    2009-10-01

    A novel reinforcement-learning-based output adaptive neural network (NN) controller, which is also referred to as the adaptive-critic NN controller, is developed to deliver the desired tracking performance for a class of nonlinear discrete-time systems expressed in nonstrict feedback form in the presence of bounded and unknown disturbances. The adaptive-critic NN controller consists of an observer, a critic, and two action NNs. The observer estimates the states and output, and the two action NNs provide virtual and actual control inputs to the nonlinear discrete-time system. The critic approximates a certain strategic utility function, and the action NNs minimize the strategic utility function and control inputs. All NN weights adapt online toward minimization of a performance index, utilizing the gradient-descent-based rule, in contrast with iteration-based adaptive-critic schemes. Lyapunov functions are used to show the stability of the closed-loop tracking error, weights, and observer estimates. Separation and certainty equivalence principles, persistency of excitation condition, and linearity in the unknown parameter assumption are not needed. Experimental results on a spark ignition (SI) engine operating lean at an equivalence ratio of 0.75 show a significant (25%) reduction in cyclic dispersion in heat release with control, while the average fuel input changes by less than 1% compared with the uncontrolled case. Consequently, oxides of nitrogen (NO(x)) drop by 30%, and unburned hydrocarbons drop by 16% with control. Overall, NO(x)'s are reduced by over 80% compared with stoichiometric levels.

  1. Self-learning control system for plug-in hybrid vehicles

    Science.gov (United States)

    DeVault, Robert C [Knoxville, TN

    2010-12-14

    A system is provided to instruct a plug-in hybrid electric vehicle how optimally to use electric propulsion from a rechargeable energy storage device to reach an electric recharging station, while maintaining as high a state of charge (SOC) as desired along the route prior to arriving at the recharging station at a minimum SOC. The system can include the step of calculating a straight-line distance and/or actual distance between an orientation point and the determined instant present location to determine when to initiate optimally a charge depleting phase. The system can limit extended driving on a deeply discharged rechargeable energy storage device and reduce the number of deep discharge cycles for the rechargeable energy storage device, thereby improving the effective lifetime of the rechargeable energy storage device. This "Just-in-Time strategy can be initiated automatically without operator input to accommodate the unsophisticated operator and without needing a navigation system/GPS input.

  2. Importance Of Quality Control in Reducing System Risk, a Lesson Learned From The Shuttle and a Recommendation for Future Launch Vehicles

    Science.gov (United States)

    Safie, Fayssal M.; Messer, Bradley P.

    2006-01-01

    This paper presents lessons learned from the Space Shuttle return to flight experience and the importance of these lessons learned in the development of new the NASA Crew Launch Vehicle (CLV). Specifically, the paper discusses the relationship between process control and system risk, and the importance of process control in improving space vehicle flight safety. It uses the External Tank (ET) Thermal Protection System (TPS) experience and lessons learned from the redesign and process enhancement activities performed in preparation for Return to Flight after the Columbia accident. The paper also, discusses in some details, the Probabilistic engineering physics based risk assessment performed by the Shuttle program to evaluate the impact of TPS failure on system risk and the application of the methodology to the CLV.

  3. Instance-based Policy Learning by Real-coded Genetic Algorithms and Its Application to Control of Nonholonomic Systems

    Science.gov (United States)

    Miyamae, Atsushi; Sakuma, Jun; Ono, Isao; Kobayashi, Shigenobu

    The stabilization control of nonholonomic systems have been extensively studied because it is essential for nonholonomic robot control problems. The difficulty in this problem is that the theoretical derivation of control policy is not necessarily guaranteed achievable. In this paper, we present a reinforcement learning (RL) method with instance-based policy (IBP) representation, in which control policies for this class are optimized with respect to user-defined cost functions. Direct policy search (DPS) is an approach for RL; the policy is represented by parametric models and the model parameters are directly searched by optimization techniques including genetic algorithms (GAs). In IBP representation an instance consists of a state and an action pair; a policy consists of a set of instances. Several DPSs with IBP have been previously proposed. In these methods, sometimes fail to obtain optimal control policies when state-action variables are continuous. In this paper, we present a real-coded GA for DPSs with IBP. Our method is specifically designed for continuous domains. Optimization of IBP has three difficulties; high-dimensionality, epistasis, and multi-modality. Our solution is designed for overcoming these difficulties. The policy search with IBP representation appears to be high-dimensional optimization; however, instances which can improve the fitness are often limited to active instances (instances used for the evaluation). In fact, the number of active instances is small. Therefore, we treat the search problem as a low dimensional problem by restricting search variables only to active instances. It has been commonly known that functions with epistasis can be efficiently optimized with crossovers which satisfy the inheritance of statistics. For efficient search of IBP, we propose extended crossover-like mutation (extended XLM) which generates a new instance around an instance with satisfying the inheritance of statistics. For overcoming multi-modality, we

  4. Supervised Learning for Dynamical System Learning.

    Science.gov (United States)

    Hefny, Ahmed; Downey, Carlton; Gordon, Geoffrey J

    2015-01-01

    Recently there has been substantial interest in spectral methods for learning dynamical systems. These methods are popular since they often offer a good tradeoff between computational and statistical efficiency. Unfortunately, they can be difficult to use and extend in practice: e.g., they can make it difficult to incorporate prior information such as sparsity or structure. To address this problem, we present a new view of dynamical system learning: we show how to learn dynamical systems by solving a sequence of ordinary supervised learning problems, thereby allowing users to incorporate prior knowledge via standard techniques such as L 1 regularization. Many existing spectral methods are special cases of this new framework, using linear regression as the supervised learner. We demonstrate the effectiveness of our framework by showing examples where nonlinear regression or lasso let us learn better state representations than plain linear regression does; the correctness of these instances follows directly from our general analysis.

  5. Self-learning fuzzy logic controllers based on reinforcement

    International Nuclear Information System (INIS)

    Wang, Z.; Shao, S.; Ding, J.

    1996-01-01

    This paper proposes a new method for learning and tuning Fuzzy Logic Controllers. The self-learning scheme in this paper is composed of Bucket-Brigade and Genetic Algorithm. The proposed method is tested on the cart-pole system. Simulation results show that our approach has good learning and control performance

  6. Complexity control in statistical learning

    Indian Academy of Sciences (India)

    Then we describe how the method of regularization is used to control complexity in learning. We discuss two examples of regularization, one in which the function space used is finite dimensional, and another in which it is a reproducing kernel Hilbert space. Our exposition follows the formulation of Cucker and Smale.

  7. Digital control for nuclear reactors - lessons learned

    International Nuclear Information System (INIS)

    Bernard, J.A.; Aviles, B.N.; Lanning, D.D.

    1992-01-01

    Lessons learned during the course of the now decade-old MIT program on the digital control of nuclear reactors are enumerated. Relative to controller structure, these include the importance of a separate safety system, the need for signal validation, the role of supervisory algorithms, the significance of command validation, and the relevance of automated reasoning. Relative to controller implementation, these include the value of nodal methods to the creation of real-time reactor physics and thermal hydraulic models, the advantages to be gained from the use of real-time system models, and the importance of a multi-tiered structure to the simultaneous achievement of supervisory, global, and local control. Block diagrams are presented of proposed controllers and selected experimental and simulation-study results are shown. In addition, a history is given of the MIT program on reactor digital control

  8. Modeling learning technology systems as business systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papaspyrou, Nikolaos

    2003-01-01

    The design of Learning Technology Systems, and the Software Systems that support them, is largely conducted on an intuitive, ad hoc basis, thus resulting in inefficient systems that defectively support the learning process. There is now justifiable, increasing effort in formalizing the engineering

  9. Predictive Variable Gain Iterative Learning Control for PMSM

    Directory of Open Access Journals (Sweden)

    Huimin Xu

    2015-01-01

    Full Text Available A predictive variable gain strategy in iterative learning control (ILC is introduced. Predictive variable gain iterative learning control is constructed to improve the performance of trajectory tracking. A scheme based on predictive variable gain iterative learning control for eliminating undesirable vibrations of PMSM system is proposed. The basic idea is that undesirable vibrations of PMSM system are eliminated from two aspects of iterative domain and time domain. The predictive method is utilized to determine the learning gain in the ILC algorithm. Compression mapping principle is used to prove the convergence of the algorithm. Simulation results demonstrate that the predictive variable gain is superior to constant gain and other variable gains.

  10. Optimal and Autonomous Control Using Reinforcement Learning: A Survey.

    Science.gov (United States)

    Kiumarsi, Bahare; Vamvoudakis, Kyriakos G; Modares, Hamidreza; Lewis, Frank L

    2018-06-01

    This paper reviews the current state of the art on reinforcement learning (RL)-based feedback control solutions to optimal regulation and tracking of single and multiagent systems. Existing RL solutions to both optimal and control problems, as well as graphical games, will be reviewed. RL methods learn the solution to optimal control and game problems online and using measured data along the system trajectories. We discuss Q-learning and the integral RL algorithm as core algorithms for discrete-time (DT) and continuous-time (CT) systems, respectively. Moreover, we discuss a new direction of off-policy RL for both CT and DT systems. Finally, we review several applications.

  11. Automatic control systems engineering

    International Nuclear Information System (INIS)

    Shin, Yun Gi

    2004-01-01

    This book gives descriptions of automatic control for electrical electronics, which indicates history of automatic control, Laplace transform, block diagram and signal flow diagram, electrometer, linearization of system, space of situation, state space analysis of electric system, sensor, hydro controlling system, stability, time response of linear dynamic system, conception of root locus, procedure to draw root locus, frequency response, and design of control system.

  12. Tunnel Ventilation Control Using Reinforcement Learning Methodology

    Science.gov (United States)

    Chu, Baeksuk; Kim, Dongnam; Hong, Daehie; Park, Jooyoung; Chung, Jin Taek; Kim, Tae-Hyung

    The main purpose of tunnel ventilation system is to maintain CO pollutant concentration and VI (visibility index) under an adequate level to provide drivers with comfortable and safe driving environment. Moreover, it is necessary to minimize power consumption used to operate ventilation system. To achieve the objectives, the control algorithm used in this research is reinforcement learning (RL) method. RL is a goal-directed learning of a mapping from situations to actions without relying on exemplary supervision or complete models of the environment. The goal of RL is to maximize a reward which is an evaluative feedback from the environment. In the process of constructing the reward of the tunnel ventilation system, two objectives listed above are included, that is, maintaining an adequate level of pollutants and minimizing power consumption. RL algorithm based on actor-critic architecture and gradient-following algorithm is adopted to the tunnel ventilation system. The simulations results performed with real data collected from existing tunnel ventilation system and real experimental verification are provided in this paper. It is confirmed that with the suggested controller, the pollutant level inside the tunnel was well maintained under allowable limit and the performance of energy consumption was improved compared to conventional control scheme.

  13. Recommendation System for Adaptive Learning.

    Science.gov (United States)

    Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

    2018-01-01

    An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

  14. Precision digital control systems

    Science.gov (United States)

    Vyskub, V. G.; Rozov, B. S.; Savelev, V. I.

    This book is concerned with the characteristics of digital control systems of great accuracy. A classification of such systems is considered along with aspects of stabilization, programmable control applications, digital tracking systems and servomechanisms, and precision systems for the control of a scanning laser beam. Other topics explored are related to systems of proportional control, linear devices and methods for increasing precision, approaches for further decreasing the response time in the case of high-speed operation, possibilities for the implementation of a logical control law, and methods for the study of precision digital control systems. A description is presented of precision automatic control systems which make use of electronic computers, taking into account the existing possibilities for an employment of computers in automatic control systems, approaches and studies required for including a computer in such control systems, and an analysis of the structure of automatic control systems with computers. Attention is also given to functional blocks in the considered systems.

  15. BSF control system

    International Nuclear Information System (INIS)

    Irie, Y.; Ishii, K.; Ninomiya, S.; Sasaki, H.; Sakai, I.

    1982-08-01

    The booster synchrotron utilization facility (BSF) is a facility which utilizes the four fifths of available beam pulses from the KEK booster synchrotron. The BSF control system includes the beam line control, interactions with the PS central control room and the experimental facilities, and the access control system. A brief description of the various components in the control system is given. (author)

  16. Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

    Science.gov (United States)

    Chan, Tak-Wai

    1996-01-01

    Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

  17. The control of tonic pain by active relief learning.

    Science.gov (United States)

    Zhang, Suyi; Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W; Seymour, Ben

    2018-02-27

    Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty ('associability') signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. © 2018, Zhang et al.

  18. The control of tonic pain by active relief learning

    Science.gov (United States)

    Mano, Hiroaki; Lee, Michael; Yoshida, Wako; Kawato, Mitsuo; Robbins, Trevor W

    2018-01-01

    Tonic pain after injury characterises a behavioural state that prioritises recovery. Although generally suppressing cognition and attention, tonic pain needs to allow effective relief learning to reduce the cause of the pain. Here, we describe a central learning circuit that supports learning of relief and concurrently suppresses the level of ongoing pain. We used computational modelling of behavioural, physiological and neuroimaging data in two experiments in which subjects learned to terminate tonic pain in static and dynamic escape-learning paradigms. In both studies, we show that active relief-seeking involves a reinforcement learning process manifest by error signals observed in the dorsal putamen. Critically, this system uses an uncertainty (‘associability’) signal detected in pregenual anterior cingulate cortex that both controls the relief learning rate, and endogenously and parametrically modulates the level of tonic pain. The results define a self-organising learning circuit that reduces ongoing pain when learning about potential relief. PMID:29482716

  19. Control system design method

    Science.gov (United States)

    Wilson, David G [Tijeras, NM; Robinett, III, Rush D.

    2012-02-21

    A control system design method and concomitant control system comprising representing a physical apparatus to be controlled as a Hamiltonian system, determining elements of the Hamiltonian system representation which are power generators, power dissipators, and power storage devices, analyzing stability and performance of the Hamiltonian system based on the results of the determining step and determining necessary and sufficient conditions for stability of the Hamiltonian system, creating a stable control system based on the results of the analyzing step, and employing the resulting control system to control the physical apparatus.

  20. FFTF control system experience

    International Nuclear Information System (INIS)

    Warrick, R.P.

    1981-01-01

    The FFTF control systems provide control equipment for safe and efficient operation of the plant. For convenience, these systems will be divided into three parts for discussions: (1) Plant Protection System (PPS); (2) Plant Control System (PCS); and (3) General Observations. Performance of each of these systems is discussed

  1. CLASSIFICATION OF LEARNING MANAGEMENT SYSTEMS

    Directory of Open Access Journals (Sweden)

    Yu. B. Popova

    2016-01-01

    Full Text Available Using of information technologies and, in particular, learning management systems, increases opportunities of teachers and students in reaching their goals in education. Such systems provide learning content, help organize and monitor training, collect progress statistics and take into account the individual characteristics of each user. Currently, there is a huge inventory of both paid and free systems are physically located both on college servers and in the cloud, offering different features sets of different licensing scheme and the cost. This creates the problem of choosing the best system. This problem is partly due to the lack of comprehensive classification of such systems. Analysis of more than 30 of the most common now automated learning management systems has shown that a classification of such systems should be carried out according to certain criteria, under which the same type of system can be considered. As classification features offered by the author are: cost, functionality, modularity, keeping the customer’s requirements, the integration of content, the physical location of a system, adaptability training. Considering the learning management system within these classifications and taking into account the current trends of their development, it is possible to identify the main requirements to them: functionality, reliability, ease of use, low cost, support for SCORM standard or Tin Can API, modularity and adaptability. According to the requirements at the Software Department of FITR BNTU under the guidance of the author since 2009 take place the development, the use and continuous improvement of their own learning management system.

  2. Adaptive Trajectory Tracking Control using Reinforcement Learning for Quadrotor

    Directory of Open Access Journals (Sweden)

    Wenjie Lou

    2016-02-01

    Full Text Available Inaccurate system parameters and unpredicted external disturbances affect the performance of non-linear controllers. In this paper, a new adaptive control algorithm under the reinforcement framework is proposed to stabilize a quadrotor helicopter. Based on a command-filtered non-linear control algorithm, adaptive elements are added and learned by policy-search methods. To predict the inaccurate system parameters, a new kernel-based regression learning method is provided. In addition, Policy learning by Weighting Exploration with the Returns (PoWER and Return Weighted Regression (RWR are utilized to learn the appropriate parameters for adaptive elements in order to cancel the effect of external disturbance. Furthermore, numerical simulations under several conditions are performed, and the ability of adaptive trajectory-tracking control with reinforcement learning are demonstrated.

  3. Wisdom Appliance Control System

    Science.gov (United States)

    Hendrick; Jheng, Jyun-Teng; Tsai, Chen-Chai; Liou, Jia-Wei; Wang, Zhi-Hao; Jong, Gwo-Jia

    2017-07-01

    Intelligent appliances wisdom involves security, home care, convenient and energy saving, but the home automation system is still one of the core unit, and also using micro-processing electronics technology to centralized and control the home electrical products and systems, such as: lighting, television, fan, air conditioning, stereo, it composed of front-controller systems and back-controller panels, user using front-controller to control command, and then through the back-controller to powered the device.

  4. Intelligent fractions learning system: implementation

    CSIR Research Space (South Africa)

    Smith, Andrew C

    2011-05-01

    Full Text Available Conference Proceedings Paul Cunningham and Miriam Cunningham (Eds) IIMC International Information Management Corporation, 2011 ISBN: 978-1-905824-24-3 An Intelligent Fractions Learning System: Implementation Andrew Cyrus SMITH1, Teemu H. LAINE2 1CSIR... to fractions. Our aim with the current research project is to extend the existing UFractions learning system to incorporate automatic data capturing. ?Intelligent UFractions? allows a teacher to remotely monitor the children?s progress during...

  5. Personal exposure control system

    International Nuclear Information System (INIS)

    Tanabe, Ken-ichi; Akashi, Michio

    1994-01-01

    Nuclear power stations are under strict radiation control. Exposure control for nuclear workers is the most important operation, and so carefully thought out measures are taken. This paper introduces Fuji Electric's personal exposure control system that meets strict exposure control and rationalizes control operations. The system has a merit that it can provide required information in an optimum form using the interconnection of a super minicomputer and exposure control facilities and realizes sophisticated exposure control operations. (author)

  6. Statistical learning methods: Basics, control and performance

    Energy Technology Data Exchange (ETDEWEB)

    Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de

    2006-04-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.

  7. Statistical learning methods: Basics, control and performance

    International Nuclear Information System (INIS)

    Zimmermann, J.

    2006-01-01

    The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms

  8. State-space approaches for modelling and control in financial engineering systems theory and machine learning methods

    CERN Document Server

    Rigatos, Gerasimos G

    2017-01-01

    The book conclusively solves problems associated with the control and estimation of nonlinear and chaotic dynamics in financial systems when these are described in the form of nonlinear ordinary differential equations. It then addresses problems associated with the control and estimation of financial systems governed by partial differential equations (e.g. the Black–Scholes partial differential equation (PDE) and its variants). Lastly it an offers optimal solution to the problem of statistical validation of computational models and tools used to support financial engineers in decision making. The application of state-space models in financial engineering means that the heuristics and empirical methods currently in use in decision-making procedures for finance can be eliminated. It also allows methods of fault-free performance and optimality in the management of assets and capitals and methods assuring stability in the functioning of financial systems to be established. Covering the following key are...

  9. A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control

    Science.gov (United States)

    Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu

    This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.

  10. The organization of an autonomous learning system

    Science.gov (United States)

    Kanerva, Pentti

    1988-01-01

    The organization of systems that learn from experience is examined, human beings and animals being prime examples of such systems. How is their information processing organized. They build an internal model of the world and base their actions on the model. The model is dynamic and predictive, and it includes the systems' own actions and their effects. In modeling such systems, a large pattern of features represents a moment of the system's experience. Some of the features are provided by the system's senses, some control the system's motors, and the rest have no immediate external significance. A sequence of such patterns then represents the system's experience over time. By storing such sequences appropriately in memory, the system builds a world model based on experience. In addition to the essential function of memory, fundamental roles are played by a sensory system that makes raw information about the world suitable for memory storage and by a motor system that affects the world. The relation of sensory and motor systems to the memory is discussed, together with how favorable actions can be learned and unfavorable actions can be avoided. Results in classical learning theory are explained in terms of the model, more advanced forms of learning are discussed, and the relevance of the model to the frame problem of robotics is examined.

  11. Reinforcement Learning for Ramp Control: An Analysis of Learning Parameters

    Directory of Open Access Journals (Sweden)

    Chao Lu

    2016-08-01

    Full Text Available Reinforcement Learning (RL has been proposed to deal with ramp control problems under dynamic traffic conditions; however, there is a lack of sufficient research on the behaviour and impacts of different learning parameters. This paper describes a ramp control agent based on the RL mechanism and thoroughly analyzed the influence of three learning parameters; namely, learning rate, discount rate and action selection parameter on the algorithm performance. Two indices for the learning speed and convergence stability were used to measure the algorithm performance, based on which a series of simulation-based experiments were designed and conducted by using a macroscopic traffic flow model. Simulation results showed that, compared with the discount rate, the learning rate and action selection parameter made more remarkable impacts on the algorithm performance. Based on the analysis, some suggestionsabout how to select suitable parameter values that can achieve a superior performance were provided.

  12. The remote control system

    International Nuclear Information System (INIS)

    Jansweijer, P.P.M.

    1988-01-01

    The remote-control system is applied in order to control various signals in the car of the spectrometer at distance. The construction (hardware and software) as well as the operation of the system is described. (author). 20 figs

  13. Control and automation systems

    International Nuclear Information System (INIS)

    Schmidt, R.; Zillich, H.

    1986-01-01

    A survey is given of the development of control and automation systems for energy uses. General remarks about control and automation schemes are followed by a description of modern process control systems along with process control processes as such. After discussing the particular process control requirements of nuclear power plants the paper deals with the reliability and availability of process control systems and refers to computerized simulation processes. The subsequent paragraphs are dedicated to descriptions of the operating floor, ergonomic conditions, existing systems, flue gas desulfurization systems, the electromagnetic influences on digital circuits as well as of light wave uses. (HAG) [de

  14. A fuzzy controller with a robust learning function

    International Nuclear Information System (INIS)

    Tanji, Jun-ichi; Kinoshita, Mitsuo

    1987-01-01

    A self-organizing fuzzy controller is able to use linguistic decision rules of control strategy and has a strong adaptive property by virture of its rule learning function. While a simple linguistic description of the learning algorithm first introduced by Procyk, et al. has much flexibility for applications to a wide range of different processes, its detailed formulation, in particular with control stability and learning process convergence, is not clear. In this paper, we describe the formulation of an analytical basis for a self-organizing fuzzy controller by using a method of model reference adaptive control systems (MRACS) for which stability in the adaptive loop is theoretically proven. A detailed formulation is described regarding performance evaluation and rule modification in the rule learning process of the controller. Furthermore, an improved learning algorithm using adaptive rule is proposed. An adaptive rule gives a modification coefficient for a rule change estimating the effect of disturbance occurrence in performance evaluation. The effect of introducing an adaptive rule to improve the learning convergency is described by using a simple iterative formulation. Simulation tests are presented for an application of the proposed self-organizing fuzzy controller to the pressure control system in a Boiling Water Reactor (BWR) plant. Results with the tests confirm the improved learning algorithm has strong convergent properties, even in a very disturbed environment. (author)

  15. Iterative learning control an optimization paradigm

    CERN Document Server

    Owens, David H

    2016-01-01

    This book develops a coherent theoretical approach to algorithm design for iterative learning control based on the use of optimization concepts. Concentrating initially on linear, discrete-time systems, the author gives the reader access to theories based on either signal or parameter optimization. Although the two approaches are shown to be related in a formal mathematical sense, the text presents them separately because their relevant algorithm design issues are distinct and give rise to different performance capabilities. Together with algorithm design, the text demonstrates that there are new algorithms that are capable of incorporating input and output constraints, enable the algorithm to reconfigure systematically in order to meet the requirements of different reference signals and also to support new algorithms for local convergence of nonlinear iterative control. Simulation and application studies are used to illustrate algorithm properties and performance in systems like gantry robots and other elect...

  16. ISABELLE control system

    International Nuclear Information System (INIS)

    Humphrey, J.W.; Frankel, R.S.; Niederer, J.A.

    1980-01-01

    Design principles for the Brookhaven ISABELLE control intersecting storage ring accelerator are described. Principal features include a locally networked console and control computer complex, a system wide process data highway, and intelligent local device controllers. Progress to date is summarized

  17. Methods for control over learning individual trajectory

    Science.gov (United States)

    Mitsel, A. A.; Cherniaeva, N. V.

    2015-09-01

    The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects.

  18. Reactor control system. PWR

    International Nuclear Information System (INIS)

    2009-01-01

    At present, 23 units of PWR type reactors have been operated in Japan since the start of Mihama Unit 1 operation in 1970 and various improvements have been made to upgrade operability of power stations as well as reliability and safety of power plants. As the share of nuclear power increases, further improvements of operating performance such as load following capability will be requested for power stations with more reliable and safer operation. This article outlined the reactor control system of PWR type reactors and described the control performance of power plants realized with those systems. The PWR control system is characterized that the turbine power is automatic or manually controlled with request of the electric power system and then the nuclear power is followingly controlled with the change of core reactivity. The system mainly consists of reactor automatic control system (control rod control system), pressurizer pressure control system, pressurizer water level control system, steam generator water level control system and turbine bypass control system. (T. Tanaka)

  19. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  20. Integrated control systems

    International Nuclear Information System (INIS)

    Smith, D.J.

    1991-01-01

    This paper reports that instrument manufacturers must develop standard network interfaces to pull together interrelated systems such as automatic start-up, optimization programs, and online diagnostic systems. In the past individual control system manufacturers have developed their own data highways with proprietary hardware and software designs. In the future, electric utilities will require that future systems, irrespective of manufacturer, should be able to communicate with each other. Until now the manufactures of control systems have not agreed on the standard high-speed data highway system. Currently, the Electric Power Research Institute (EPRI), in conjunction with several electric utilities and equipment manufactures, is working on developing a standard protocol for communicating between various manufacturers' control systems. According to N. Michael of Sargent and Lundy, future control room designs will require that more of the control and display functions be accessible from the control room through CRTs. There will be less emphasis on traditional hard-wired control panels

  1. LONS: Learning Object Negotiation System

    Science.gov (United States)

    García, Antonio; García, Eva; de-Marcos, Luis; Martínez, José-Javier; Gutiérrez, José-María; Gutiérrez, José-Antonio; Barchino, Roberto; Otón, Salvador; Hilera, José-Ramón

    This system comes up as a result of the increase of e-learning systems. It manages all relevant modules in this context, such as the association of digital rights with the contents (courses), management and payment processing on rights. There are three blocks:

  2. A national control system

    International Nuclear Information System (INIS)

    Larsson, A.

    1975-01-01

    An effective control of nuclear fissionable material is dependent on three different kinds of control, the industry - laboratory management, a national control system and an international safeguards system. The national systems of control differ greatly between various industrialized countries. Two principal reasons for fact can be mentioned. The type and the amounts for nuclear material may be different depending upon the stage of development of the nuclear industry in the country in question. Another reason may be that the country may wish to establish a very elaborate national system of control in order to minimize the IAEA control as much as possible. The two safeguards agreements between the Agency and Sweden on one hand and the Agency and Japan on the other hand can serve as examples for the understanding of the latitude of the IAEA safeguards system under NPT due to the influence of the national control system. If it thus is apparent that the national control system is strongly interrelated to the international safeguards system it is equally influenced by the control and accountancy systems which exist at the nuclear plants and development laboratories. A detailed study of national control systems and their relations to plant management control would fall outside the scope of this article. Some important features will however be examined. (author)

  3. YF22 Model With On-Board On-Line Learning Microprocessors-Based Neural Algorithms for Autopilot and Fault-Tolerant Flight Control Systems

    National Research Council Canada - National Science Library

    Napolitano, Marcello

    2002-01-01

    This project focused on investigating the potential of on-line learning 'hardware-based' neural approximators and controllers to provide fault tolerance capabilities following sensor and actuator failures...

  4. Learning in Artificial Neural Systems

    Science.gov (United States)

    Matheus, Christopher J.; Hohensee, William E.

    1987-01-01

    This paper presents an overview and analysis of learning in Artificial Neural Systems (ANS's). It begins with a general introduction to neural networks and connectionist approaches to information processing. The basis for learning in ANS's is then described, and compared with classical Machine learning. While similar in some ways, ANS learning deviates from tradition in its dependence on the modification of individual weights to bring about changes in a knowledge representation distributed across connections in a network. This unique form of learning is analyzed from two aspects: the selection of an appropriate network architecture for representing the problem, and the choice of a suitable learning rule capable of reproducing the desired function within the given network. The various network architectures are classified, and then identified with explicit restrictions on the types of functions they are capable of representing. The learning rules, i.e., algorithms that specify how the network weights are modified, are similarly taxonomized, and where possible, the limitations inherent to specific classes of rules are outlined.

  5. Intelligent control systems 1990

    International Nuclear Information System (INIS)

    Shoureshi, R.

    1991-01-01

    The field of artificial intelligence (Al) has generated many useful ideas and techniques that can be integrated into the design of control systems. It is believed and, for special cases, has been demonstrated, that integration of Al into control systems would provide the necessary tools for solving many of the complex problems that present control techniques and Al algorithms are unable to do, individually. However, this integration requires the development of basic understanding and new fundamentals to provide scientific bases for achievement of its potential. This book presents an overview of some of the latest research studies in the area of intelligent control systems. These papers present techniques for formulation of intelligent control, and development of the rule-based control systems. Papers present applications of control systems in nuclear power plants and HVAC systems

  6. Changing pulse-shape basis for molecular learning control

    International Nuclear Information System (INIS)

    Cardoza, David; Langhojer, Florian; Trallero-Herrero, Carlos; Weinacht, Thomas; Monti, Oliver L.A.

    2004-01-01

    We interpret the results of a molecular fragmentation learning control experiment. We show that in the case of a system where control can be related to the structure of the optimal pulse matching the vibrational dynamics of the molecule, a simple change of pulse-shape basis in which the learning algorithm performs the search can reduce the dimensionality of the search space to one or two degrees of freedom

  7. ALFA Detector Control System

    CERN Document Server

    Oleiro Seabra, Luis Filipe; The ATLAS collaboration

    2015-01-01

    ALFA (Absolute Luminosity For ATLAS) is one of the sub-detectors of ATLAS (A Toroidal LHC Apparatus). The ALFA system is composed by four stations installed in the LHC tunnel 240 m away from the ATLAS interaction point. Each station has a vacuum and ventilation system, movement control and all the required electronics for signal processing. The Detector Control System (DCS) provides control and monitoring of several components and ensures the safe operation of the detector contributing to good Data Quality. This paper describes the ALFA DCS system including a detector overview, operation aspects and hardware control through a SCADA system, WinCC OA.

  8. ALFA Detector Control System

    CERN Document Server

    Oleiro Seabra, Luis Filipe; The ATLAS collaboration

    2015-01-01

    ALFA (Absolute Luminosity For ATLAS) is one of the sub-detectors of ATLAS/LHC. The ALFA system is composed by two stations installed in the LHC tunnel 240 m away from each side of the ATLAS interaction point. Each station has a vacuum and ventilation system, movement control and all the required electronic for signal processing. The Detector Control System (DCS) provides control and monitoring of several components and ensures the safe operation of the detector contributing to good Data Quality. This paper describes the ALFA DCS system including a detector overview, operation aspects and hardware control through a SCADA system, WinCC OA.

  9. Designing E-learning Model to Learn About Transportation Management System to Support Supply Chain Management with Simulation Problems

    OpenAIRE

    Wiyono, Didiek Sri; Pribadi, Sidigdoyo; Permana, Ryan

    2011-01-01

    Focus of this research is designing Transportation Management System (TMS) as e-learning media for logistic education. E-learning is the use of Internet technologies to enhance knowledge and performance. E-learning technologies offer learners control over content, learning sequence, pace of learning, time, and often media, allowing them to tailor their experiences to meet their personal learning objectives. E-learning appears to be at least as effective as classical lectures. Students do not ...

  10. Social software: E-learning beyond learning management systems

    DEFF Research Database (Denmark)

    Dalsgaard, Christian

    2006-01-01

    The article argues that it is necessary to move e-learning beyond learning management systems and engage students in an active use of the web as a resource for their self-governed, problem-based and collaborative activities. The purpose of the article is to discuss the potential of social software...... to move e-learning beyond learning management systems. An approach to use of social software in support of a social constructivist approach to e-learning is presented, and it is argued that learning management systems do not support a social constructivist approach which emphasizes self-governed learning...... activities of students. The article suggests a limitation of the use of learning management systems to cover only administrative issues. Further, it is argued that students' self-governed learning processes are supported by providing students with personal tools and engaging them in different kinds of social...

  11. An iterative learning controller for nonholonomic mobile robots

    International Nuclear Information System (INIS)

    Oriolo, G.; Panzieri, S.; Ulivi, G.

    1998-01-01

    The authors present an iterative learning controller that applies to nonholonomic mobile robots, as well as other systems that can be put in chained form. The learning algorithm exploits the fact that chained-form. The learning algorithm exploits the fact that chained-form systems are linear under piecewise-constant inputs. The proposed control scheme requires the execution of a small number of experiments to drive the system to the desired state in finite time, with nice convergence and robustness properties with respect to modeling inaccuracies as well as disturbances. To avoid the necessity of exactly reinitializing the system at each iteration, the basic method is modified so as to obtain a cyclic controller, by which the system is cyclically steered through an arbitrary sequence of states. As a case study, a carlike mobile robot is considered. Both simulation and experimental results are reported to show the performance of the method

  12. Mosaic model for sensorimotor learning and control.

    Science.gov (United States)

    Haruno, M; Wolpert, D M; Kawato, M

    2001-10-01

    Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

  13. A modular control system

    International Nuclear Information System (INIS)

    Cruz, B.; Drexler, J.; Olcese, G.; Santome, D.

    1990-01-01

    The main objective of the modular control system is to provide the requirements to most of the processes supervision and control applications within the industrial automatization area. The design is based on distribution, modulation and expansion concepts. (Author) [es

  14. Applied Control Systems Design

    CERN Document Server

    Mahmoud, Magdi S

    2012-01-01

    Applied Control System Design examines several methods for building up systems models based on real experimental data from typical industrial processes and incorporating system identification techniques. The text takes a comparative approach to the models derived in this way judging their suitability for use in different systems and under different operational circumstances. A broad spectrum of control methods including various forms of filtering, feedback and feedforward control is applied to the models and the guidelines derived from the closed-loop responses are then composed into a concrete self-tested recipe to serve as a check-list for industrial engineers or control designers. System identification and control design are given equal weight in model derivation and testing to reflect their equality of importance in the proper design and optimization of high-performance control systems. Readers’ assimilation of the material discussed is assisted by the provision of problems and examples. Most of these e...

  15. Learning styles: The learning methods of air traffic control students

    Science.gov (United States)

    Jackson, Dontae L.

    In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.

  16. The ILC control system

    International Nuclear Information System (INIS)

    Carwardine, J.; Saunders, C.; Arnold, N.; Lenkszus, F.; Rehlich, K.; Simrock, S.; Banerjee, b.; Chase, B.; Gottschalk, E.; Joireman, P.; Kasley, P.; Lackey, S.; McBride, P.; Pavlicek, V.; Patrick, J.; Votava, M.; Wolbers, S.; Furukawa, K.; Michizono, S.; Larson, R.S.; Downing, R.

    2007-01-01

    Since the last ICALEPCS, a small multi-region team has developed a reference design model for a control system for the International Linear Collider as part of the ILC Global Design Effort. The scale and performance parameters of the ILC accelerator require new thinking in regards to control system design. Technical challenges include the large number of accelerator systems to be controlled, the large scale of the accelerator facility, the high degree of automation needed during accelerator operations, and control system equipment requiring 'Five Nines' availability. The R and D path for high availability touches the control system hardware, software, and overall architecture, and extends beyond traditional interfaces into the technical systems. Software considerations for HA include fault detection through exhaustive out-of-band monitoring and automatic state migration to redundant systems, while the telecom industry's emerging ATCA standard - conceived, specified, and designed for High Availability - is being evaluated for suitability for ILC front-end electronics.

  17. Control systems engineering

    CERN Document Server

    Nise, Norman S

    1995-01-01

    This completely updated new edition shows how to use MATLAB to perform control-system calculations. Designed for the professional or engineering student who needs a quick and readable update on designing control systems, the text features a series of tightly focused examples that clearly illustrate each concept of designing control systems. Most chapters conclude with a detailed application from the two case studies that run throughout the book: an antenna asimuth control system and a submarine. The author also refers to many examples of design methods.

  18. Development of an E-learning System for the Endoscopic Diagnosis of Early Gastric Cancer: An International Multicenter Randomized Controlled Trial

    Directory of Open Access Journals (Sweden)

    K. Yao

    2016-07-01

    Interpretation: This global study clearly demonstrated the efficacy of an e-learning system to expand knowledge and provide invaluable experience regarding the endoscopic detection of early gastric cancer (R000012039.

  19. Towards autonomous neuroprosthetic control using Hebbian reinforcement learning.

    Science.gov (United States)

    Mahmoudi, Babak; Pohlmeyer, Eric A; Prins, Noeline W; Geng, Shijia; Sanchez, Justin C

    2013-12-01

    Our goal was to design an adaptive neuroprosthetic controller that could learn the mapping from neural states to prosthetic actions and automatically adjust adaptation using only a binary evaluative feedback as a measure of desirability/undesirability of performance. Hebbian reinforcement learning (HRL) in a connectionist network was used for the design of the adaptive controller. The method combines the efficiency of supervised learning with the generality of reinforcement learning. The convergence properties of this approach were studied using both closed-loop control simulations and open-loop simulations that used primate neural data from robot-assisted reaching tasks. The HRL controller was able to perform classification and regression tasks using its episodic and sequential learning modes, respectively. In our experiments, the HRL controller quickly achieved convergence to an effective control policy, followed by robust performance. The controller also automatically stopped adapting the parameters after converging to a satisfactory control policy. Additionally, when the input neural vector was reorganized, the controller resumed adaptation to maintain performance. By estimating an evaluative feedback directly from the user, the HRL control algorithm may provide an efficient method for autonomous adaptation of neuroprosthetic systems. This method may enable the user to teach the controller the desired behavior using only a simple feedback signal.

  20. Discrete control systems

    CERN Document Server

    Okuyama, Yoshifumi

    2014-01-01

    Discrete Control Systems establishes a basis for the analysis and design of discretized/quantized control systemsfor continuous physical systems. Beginning with the necessary mathematical foundations and system-model descriptions, the text moves on to derive a robust stability condition. To keep a practical perspective on the uncertain physical systems considered, most of the methods treated are carried out in the frequency domain. As part of the design procedure, modified Nyquist–Hall and Nichols diagrams are presented and discretized proportional–integral–derivative control schemes are reconsidered. Schemes for model-reference feedback and discrete-type observers are proposed. Although single-loop feedback systems form the core of the text, some consideration is given to multiple loops and nonlinearities. The robust control performance and stability of interval systems (with multiple uncertainties) are outlined. Finally, the monograph describes the relationship between feedback-control and discrete ev...

  1. Biogas plant control system

    International Nuclear Information System (INIS)

    Balasevicius, L.; Dervinis, G.; Macerauskas, V.

    2002-01-01

    This paper presents intelligent control system for the pig farm biogas production process. The system uses a fuzzy logic models based on knowledge of experts and operators. Four fuzzy models are introduced. The adequacy of fuzzy models is verified using real data and MATLAB simulation. Proposed expert system is implemented into traditional SCADA system for biogas process prediction and failure analyzing. (authors)

  2. Knowledge Acquisition and Memory Effects Involving an Expert System Designed as a Learning Tool for Internal Control Assessment

    Science.gov (United States)

    Lenard, Mary Jane

    2003-01-01

    The assessment of internal control is a consideration in all financial statement audits, as stressed by the Statement on Auditing Standards (SAS) No. 78. According to this statement, "the auditor should obtain an understanding of internal control sufficient to plan the audit" (Accounting Standards Board, 1995, p. 1). Therefore, an…

  3. Control system design guide

    Energy Technology Data Exchange (ETDEWEB)

    Sellers, David; Friedman, Hannah; Haasl, Tudi; Bourassa, Norman; Piette, Mary Ann

    2003-05-01

    The ''Control System Design Guide'' (Design Guide) provides methods and recommendations for the control system design process and control point selection and installation. Control systems are often the most problematic system in a building. A good design process that takes into account maintenance, operation, and commissioning can lead to a smoothly operating and efficient building. To this end, the Design Guide provides a toolbox of templates for improving control system design and specification. HVAC designers are the primary audience for the Design Guide. The control design process it presents will help produce well-designed control systems that achieve efficient and robust operation. The spreadsheet examples for control valve schedules, damper schedules, and points lists can streamline the use of the control system design concepts set forth in the Design Guide by providing convenient starting points from which designers can build. Although each reader brings their own unique questions to the text, the Design Guide contains information that designers, commissioning providers, operators, and owners will find useful.

  4. Control rod shutdown system

    International Nuclear Information System (INIS)

    Miyamoto, Yoshiyuki; Higashigawa, Yuichi.

    1996-01-01

    The present invention provides a control rod terminating system in a BWR type nuclear power plant, which stops an induction electric motor as rapidly as possible to terminate the control rods. Namely, the control rod stopping system controls reactor power by inserting/withdrawing control rods into a reactor by driving them by the induction electric motor. The system is provided with a control device for controlling the control rods and a control device for controlling the braking device. The control device outputs a braking operation signal for actuating the braking device during operation of the control rods to stop the operation of the control rods. Further, the braking device has at least two kinds of breaks, namely, a first and a second brakes. The two kinds of brakes are actuated by receiving the brake operation signals at different timings. The brake device is used also for keeping the control rods after the stopping. Even if a stopping torque of each of the breaks is small, different two kinds of brakes are operated at different timings thereby capable of obtaining a large stopping torque as a total. (I.S.)

  5. An Intelligent System for Determining Learning Style

    Science.gov (United States)

    Ozdemir, Ali; Alaybeyoglu, Aysegul; Mulayim, Naciye; Uysal, Muhammed

    2018-01-01

    In this study, an intelligent system which determines learning style of the students is developed to increase success in effective and easy learning. The importance of the proposed software system is to determine convenience degree of the student's learning style. Personal information form and Dunn Learning Style Preference Survey are used to…

  6. Systems and Control Engineering

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 5. Systems and Control Engineering - Control Systems-Analysis and Design. A Rama Kalyan J R Vengateswaran. General Article Volume 4 Issue 5 May 1999 pp 88-94 ...

  7. A new subspace based approach to iterative learning control

    NARCIS (Netherlands)

    Nijsse, G.; Verhaegen, M.; Doelman, N.J.

    2001-01-01

    This paper1 presents an iterative learning control (ILC) procedure based on an inverse model of the plant under control. Our first contribution is that we formulate the inversion procedure as a Kalman smoothing problem: based on a compact state space model of a possibly non-minimum phase system,

  8. Spacecraft momentum control systems

    CERN Document Server

    Leve, Frederick A; Peck, Mason A

    2015-01-01

    The goal of this book is to serve both as a practical technical reference and a resource for gaining a fuller understanding of the state of the art of spacecraft momentum control systems, specifically looking at control moment gyroscopes (CMGs). As a result, the subject matter includes theory, technology, and systems engineering. The authors combine material on system-level architecture of spacecraft that feature momentum-control systems with material about the momentum-control hardware and software. This also encompasses material on the theoretical and algorithmic approaches to the control of space vehicles with CMGs. In essence, CMGs are the attitude-control actuators that make contemporary highly agile spacecraft possible. The rise of commercial Earth imaging, the advances in privately built spacecraft (including small satellites), and the growing popularity of the subject matter in academic circles over the past decade argues that now is the time for an in-depth treatment of the topic. CMGs are augmented ...

  9. Neutron generator control system

    International Nuclear Information System (INIS)

    Peelman, H.E.; Bridges, J.R.

    1981-01-01

    A method is described of controlling the neutron output of a neutron generator tube used in neutron well logging. The system operates by monitoring the target beam current and comparing a function of this current with a reference voltage level to develop a control signal used in a series regulator to control the replenisher current of the neutron generator tube. (U.K.)

  10. Learning Management Systems and Comparison of Open Source Learning Management Systems and Proprietary Learning Management Systems

    Directory of Open Access Journals (Sweden)

    Yücel Yılmaz

    2016-04-01

    Full Text Available The concept of learning has been increasingly gaining importance for individuals, businesses and communities in the age of information. On the other hand, developments in information and communication technologies take effect in the field of learning activities. With these technologies, barriers of time and space against the learning activities largely disappear and these technologies make it easier to carry out these activities more effectively. There remain a lot of questions regarding selection of learning management system (LMS to be used for the management of e-learning processes by all organizations conducing educational practices including universities, companies, non-profit organizations, etc. The main questions are as follows: Shall we choose open source LMS or commercial LMS? Can the selected LMS meet existing needs and future potential needs for the organization? What are the possibilities of technical support in the management of LMS? What kind of problems may be experienced in the use of LMS and how can these problems be solved? How much effective can officials in the organization be in the management of LMS? In this study, primarily e-learning and the concept of LMS will be discussed, and in the next section, as for answers to these questions, open source LMSs and centrally developed LMSs will be examined and their advantages and disadvantages relative to each other will be discussed.

  11. Toward A Dual-Learning Systems Model of Speech Category Learning

    Directory of Open Access Journals (Sweden)

    Bharath eChandrasekaran

    2014-07-01

    Full Text Available More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article we describe a neurobiologically-constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. We find an age related deficit in reflective-optimal but not reflexive-optimal auditory category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, uni-dimensional rules to more complex, reflexive, multi-dimensional rules. In a second application we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions.

  12. Dynamic Systems and Control Engineering

    International Nuclear Information System (INIS)

    Kim, Jong Seok

    1994-02-01

    This book deals with introduction of dynamic system and control engineering, frequency domain modeling of dynamic system, temporal modeling of dynamic system, typical dynamic system and automatic control device, performance and stability of control system, root locus analysis, analysis of frequency domain dynamic system, design of frequency domain dynamic system, design and analysis of space, space of control system and digital control system such as control system design of direct digital and digitalization of consecutive control system.

  13. Dynamic Systems and Control Engineering

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Jong Seok

    1994-02-15

    This book deals with introduction of dynamic system and control engineering, frequency domain modeling of dynamic system, temporal modeling of dynamic system, typical dynamic system and automatic control device, performance and stability of control system, root locus analysis, analysis of frequency domain dynamic system, design of frequency domain dynamic system, design and analysis of space, space of control system and digital control system such as control system design of direct digital and digitalization of consecutive control system.

  14. Learning, Leading and Letting go of Control

    DEFF Research Database (Denmark)

    Jensen, Annie Aarup; Kjær-Rasmussen, Lone Krogh; Iversen, Ann-Merete

    Learning, leading and letting go of control – Learner Led Approaches in Education Annie Aarup Jensen, Lone Krogh Kjær-Rasmussen, Ann-Merete Iversen and Anni Stavnskær Pedersen Abstract The aim of the paper is to introduce a new term in teaching in Higher Education: Learner Led Approaches...... in Education: LED. The sources of inspiration are many as are the experiences we draw from. Problem-based project work (PBL) being one, various classical teacher centered methods, and last but not least a variety of methods aiming towards developing creativity, innovational skills and entrepreneurship. LED...... is inspired by collaboration between professors from Aalborg University, Cornwall College and University College of Northern Denmark. Moravec (2008) claims that educational systems still operate in 1.0 or perhaps 2.0 mode while the surrounding cultures and societies operate in 3.0 mode. The amount...

  15. Drone Control System

    Science.gov (United States)

    1983-01-01

    Drones, subscale vehicles like the Firebees, and full scale retired military aircraft are used to test air defense missile systems. The DFCS (Drone Formation Control System) computer, developed by IBM (International Business Machines) Federal Systems Division, can track ten drones at once. A program called ORACLS is used to generate software to track and control Drones. It was originally developed by Langley and supplied by COSMIC (Computer Software Management and Information Center). The program saved the company both time and money.

  16. Magnetic spectrometer control system

    International Nuclear Information System (INIS)

    Lecca, L.A.; Di Paolo, Hugo; Fernandez Niello, Jorge O.; Marti, Guillermo V; Pacheco, Alberto J.; Ramirez, Marcelo

    2003-01-01

    The design and implementation of a new computerized control system for the several devices of the magnetic spectrometer at TANDAR Laboratory is described. This system, as a main difference from the preexisting one, is compatible with almost any operating systems of wide spread use available in PC. This allows on-line measurement and control of all signals from any terminal of a computer network. (author)

  17. HYBRID VEHICLE CONTROL SYSTEM

    Directory of Open Access Journals (Sweden)

    V. Dvadnenko

    2016-06-01

    Full Text Available The hybrid vehicle control system includes a start–stop system for an internal combustion engine. The system works in a hybrid mode and normal vehicle operation. To simplify the start–stop system, there were user new possibilities of a hybrid car, which appeared after the conversion. Results of the circuit design of the proposed system of basic blocks are analyzed.

  18. The control system

    International Nuclear Information System (INIS)

    1988-01-01

    The present control system has matured both in terms of age and capacity. Thus a new system based on a local area network (LAN) is being developed. A pilot project has been started but, owing to difficulties encountered with the present operating system used with the microprocessors, it has become necessary to reconsider the choice of operating system. A recently-released multi-tasking operating system that runs on the existing hardware has been chosen. 1 fig

  19. System control and communication

    International Nuclear Information System (INIS)

    Bindner, H.; Oestergaard, J.

    2005-01-01

    Rapid and ongoing development in the energy sector has consequences for system control at all levels. In relation to system control and communication the control system is challenged in five important ways: 1) Expectations for security of supply, robustness and vulnerability are becoming more stringent, and the control system plays a big part in meeting these expectations. 2) Services are becoming increasingly based on markets that involve the transmission system operators (TSOs), generators and distribution companies. Timely, accurate and secure communication is essential to the smooth running of the markets. 3) Adding large amounts of renewable energy (RE) to the mix is a challenge for control systems because of the intermittent availability of many RE sources. 4) Increasing the number of active components in the system, such as small CHP plants, micro-CHP and intelligent loads, means that the system control will be much more complex. 5) In the future it is likely that power, heat, gas, transport and communication systems will be tighter coupled and interact much more. (au)

  20. Accelerator control systems without minicomputers

    International Nuclear Information System (INIS)

    Altaber, J.; Beck, F.; Rausch, R.

    1980-01-01

    A paper given last year described in general terms a plan for the control of a large machine using assemblies of microcomputer units which simulate a conventional minicomputer by multiprocessing. In every other way the SPS control philosophy is followed. The design of a model assembly has allowed us to learn something about the protocols needed inside and between assemblies, as well as to assess more accurately what level of technology it is reasonable to apply. In any control system of this kind it would be desirable to allow engineering contributions from a variety of sources, and yet ensure the homogeneity needed for the system to remain reliable and comprehensible. Methods of achieving this are discussed. (Auth.)

  1. The CEBAF control system

    International Nuclear Information System (INIS)

    Watson, W.A. III.

    1995-01-01

    CEBAF has recently upgraded its accelerator control system to use EPICS, a control system toolkit being developed by a collaboration among laboratories in the US and Europe. The migration to EPICS has taken place during a year of intense commissioning activity, with new and old control systems operating concurrently. Existing CAMAC hardware was preserved by adding a CAMAC serial highway link to VME; newer hardware developments are now primarily in VME. Software is distributed among three tiers of computers: first, workstations and X terminals for operator interfaces and high level applications; second, VME single board computers for distributed access to hardware and for local control processing; third, embedded processors where needed for faster closed loop operation. This system has demonstrated the ability to scale EPICS to controlling thousands of devices, including hundreds of embedded processors, with control distributed among dozens of VME processors executing more than 125,000 EPICS database records. To deal with the large size of the control system, CEBAF has integrated an object oriented database, providing data management capabilities for both low level I/O and high level machine modeling. A new callable interface which is control system independent permits access to live EPICS data, data in other Unix processes, and data contained in the object oriented database

  2. Behavioural conditioning of immune functions: how the central nervous system controls peripheral immune responses by evoking associative learning processes.

    Science.gov (United States)

    Riether, Carsten; Doenlen, Raphaël; Pacheco-López, Gustavo; Niemi, Maj-Britt; Engler, Andrea; Engler, Harald; Schedlowski, Manfred

    2008-01-01

    During the last 30 years of psychoneuroimmunology research the intense bi-directional communication between the central nervous system (CNS) and the immune system has been demonstrated in studies on the interaction between the nervous-endocrine-immune systems. One of the most intriguing examples of such interaction is the capability of the CNS to associate an immune status with specific environmental stimuli. In this review, we systematically summarize experimental evidence demonstrating the behavioural conditioning of peripheral immune functions. In particular, we focus on the mechanisms underlying the behavioural conditioning process and provide a theoretical framework that indicates the potential feasibility of behaviourally conditioned immune changes in clinical situations.

  3. Load Control System Reliability

    Energy Technology Data Exchange (ETDEWEB)

    Trudnowski, Daniel [Montana Tech of the Univ. of Montana, Butte, MT (United States)

    2015-04-03

    This report summarizes the results of the Load Control System Reliability project (DOE Award DE-FC26-06NT42750). The original grant was awarded to Montana Tech April 2006. Follow-on DOE awards and expansions to the project scope occurred August 2007, January 2009, April 2011, and April 2013. In addition to the DOE monies, the project also consisted of matching funds from the states of Montana and Wyoming. Project participants included Montana Tech; the University of Wyoming; Montana State University; NorthWestern Energy, Inc., and MSE. Research focused on two areas: real-time power-system load control methodologies; and, power-system measurement-based stability-assessment operation and control tools. The majority of effort was focused on area 2. Results from the research includes: development of fundamental power-system dynamic concepts, control schemes, and signal-processing algorithms; many papers (including two prize papers) in leading journals and conferences and leadership of IEEE activities; one patent; participation in major actual-system testing in the western North American power system; prototype power-system operation and control software installed and tested at three major North American control centers; and, the incubation of a new commercial-grade operation and control software tool. Work under this grant certainly supported the DOE-OE goals in the area of “Real Time Grid Reliability Management.”

  4. ISTTOK control system upgrade

    Energy Technology Data Exchange (ETDEWEB)

    Carvalho, Ivo S., E-mail: ivoc@ipfn.ist.utl.pt; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Carvalho, Bernardo B.

    2013-10-15

    Highlights: •ISTTOK fast controller. •All real-time diagnostic and actuators were integrated in the control platform. •100 μs control cycle under the MARTe framework. •The ISTTOK control system upgrade provides reliable operation with an improved operational space. -- Abstract: The ISTTOK tokamak (Ip = 4 kA, BT = 0.5 T, R = 0.46 m, a = 0.085 m) is one of the few tokamaks with regular alternate plasma current (AC) discharges scientific programme. In order to improve the discharge stability and to increase the number of AC discharge cycles a novel control system was developed. The controller acquires data from 50 analog-to-digital converter (ADC) channels of real-time diagnostics and measurements: tomography, Mirnov coils, interferometer, electric probes, sine and cosine probes, bolometer, current delivered by the power supplies, loop voltage and plasma current. The system has a control cycle of 100 μs during which it reads all the diagnostics connected to the advanced telecommunications computing architecture (ATCA) digitizers and sends the control reference to ISTTOK actuators. The controller algorithms are executed on an Intel{sup ®} Q8200 chip with 4 cores running at 2.33 GHz and connected to the I/O interfaces through an ATCA based environment. The real-time control system was programmed in C++ on top of the Multi-threaded Application Real-Time executor (MARTe). To extend the duration of the AC discharges and the plasma stability a new magnetising field power supply was commissioned and the horizontal and vertical field power supplies were also upgraded. The new system also features a user-friendly interface based on HyperText Markup Language (HTML) and Javascript to configure the controller parameters. This paper presents the ISTTOK control system and the consequent update of real-time diagnostics and actuators.

  5. ISTTOK control system upgrade

    International Nuclear Information System (INIS)

    Carvalho, Ivo S.; Duarte, Paulo; Fernandes, Horácio; Valcárcel, Daniel F.; Carvalho, Pedro J.; Silva, Carlos; Duarte, André S.; Neto, André; Sousa, Jorge; Batista, António J.N.; Carvalho, Bernardo B.

    2013-01-01

    Highlights: •ISTTOK fast controller. •All real-time diagnostic and actuators were integrated in the control platform. •100 μs control cycle under the MARTe framework. •The ISTTOK control system upgrade provides reliable operation with an improved operational space. -- Abstract: The ISTTOK tokamak (Ip = 4 kA, BT = 0.5 T, R = 0.46 m, a = 0.085 m) is one of the few tokamaks with regular alternate plasma current (AC) discharges scientific programme. In order to improve the discharge stability and to increase the number of AC discharge cycles a novel control system was developed. The controller acquires data from 50 analog-to-digital converter (ADC) channels of real-time diagnostics and measurements: tomography, Mirnov coils, interferometer, electric probes, sine and cosine probes, bolometer, current delivered by the power supplies, loop voltage and plasma current. The system has a control cycle of 100 μs during which it reads all the diagnostics connected to the advanced telecommunications computing architecture (ATCA) digitizers and sends the control reference to ISTTOK actuators. The controller algorithms are executed on an Intel ® Q8200 chip with 4 cores running at 2.33 GHz and connected to the I/O interfaces through an ATCA based environment. The real-time control system was programmed in C++ on top of the Multi-threaded Application Real-Time executor (MARTe). To extend the duration of the AC discharges and the plasma stability a new magnetising field power supply was commissioned and the horizontal and vertical field power supplies were also upgraded. The new system also features a user-friendly interface based on HyperText Markup Language (HTML) and Javascript to configure the controller parameters. This paper presents the ISTTOK control system and the consequent update of real-time diagnostics and actuators

  6. VIRTUAL LABORATORY IN DISTANCE LEARNING SYSTEM

    Directory of Open Access Journals (Sweden)

    Е. Kozlovsky

    2011-11-01

    Full Text Available Questions of designing and a choice of technologies of creation of virtual laboratory for the distance learning system are considered. Distance learning system «Kherson Virtual University» is used as illustration.

  7. Mechatronic control engineering and electro-mechanical system design - two mechatronic curricula at Aalborg University based on problem oriented and project based learning

    DEFF Research Database (Denmark)

    Pedersen, Henrik C.; Andersen, Torben Ole; Rasmussen, Peter Omand

    2009-01-01

    , it is addressed how a mechatronic education is structured so courses and projects are aligned, to utilize the full benefits of the Problem Oriented Project Based Learning (POPBL) system practiced at AalborgUniversity (AAU). This is followed by a presentation of the two complementary educations in Mechatronicsat...... using a subsystem based approach. The challenges related to teaching and learning mechatronics are addressed, discussing how mechatronics is typically taught around the world also illustrating the trends and applications of mechatronic engineering and research. This is followed by an outline...... Based Learning environment....

  8. Control system integration

    CERN Document Server

    Shea, T J

    2008-01-01

    This lecture begins with a definition of an accelerator control system, and then reviews the control system architectures that have been deployed at the larger accelerator facilities. This discussion naturally leads to identification of the major subsystems and their interfaces. We shall explore general strategies for integrating intelligent devices and signal processing subsystems based on gate arrays and programmable DSPs. The following topics will also be covered: physical packaging; timing and synchronization; local and global communication technologies; interfacing to machine protection systems; remote debugging; configuration management and source code control; and integration of commercial software tools. Several practical realizations will be presented.

  9. Measuring strategic control in artificial grammar learning.

    Science.gov (United States)

    Norman, Elisabeth; Price, Mark C; Jones, Emma

    2011-12-01

    In response to concerns with existing procedures for measuring strategic control over implicit knowledge in artificial grammar learning (AGL), we introduce a more stringent measurement procedure. After two separate training blocks which each consisted of letter strings derived from a different grammar, participants either judged the grammaticality of novel letter strings with respect to only one of these two grammars (pure-block condition), or had the target grammar varying randomly from trial to trial (novel mixed-block condition) which required a higher degree of conscious flexible control. Random variation in the colour and font of letters was introduced to disguise the nature of the rule and reduce explicit learning. Strategic control was observed both in the pure-block and mixed-block conditions, and even among participants who did not realise the rule was based on letter identity. This indicated detailed strategic control in the absence of explicit learning. Copyright © 2011 Elsevier Inc. All rights reserved.

  10. On equivalence classes in iterative learning control

    NARCIS (Netherlands)

    Verwoerd, M.H.A.; Meinsma, Gjerrit; de Vries, Theodorus J.A.

    2003-01-01

    This paper advocates a new approach to study the relation between causal iterative learning control (ILC) and conventional feedback control. Central to this approach is the introduction of the set of admissible pairs (of operators) defined with respect to a family of iterations. Considered are two

  11. The Epicure Control System

    International Nuclear Information System (INIS)

    Dambik, E.; Kline, D.; West, R.

    1993-09-01

    The Epicure Control System supports the Fermilab fixed target physics program. The system is distributed across a network of many different types of components. The use of multiple layers on interfaces for communication between logical tasks fits the client-server model. Physical devices are read and controlled using symbolic references entered into a database with an editor utility. The database system consists of a central portion containing all device information and optimized portions distributed among many nodes. Updates to the database are available throughout the system within minutes after being requested

  12. Control systems under attack?

    CERN Document Server

    Lüders, Stefan

    2005-01-01

    The enormous growth of the Internet during the last decade offers new means to share and distribute both information and data. In Industry, this results in a rapprochement of the production facilities, i.e. their Process Control and Automation Systems, and the data warehouses. At CERN, the Internet opens the possibility to monitor and even control (parts of) the LHC and its four experiments remotely from anywhere in the world. However, the adoption of standard IT technologies to Distributed Process Control and Automation Systems exposes inherent vulnerabilities to the world. The Teststand On Control System Security at CERN (TOCSSiC) is dedicated to explore the vulnerabilities of arbitrary Commercial-Of-The-Shelf hardware devices connected to standard Ethernet. As such, TOCSSiC should discover their vulnerabilities, point out areas of lack of security, and address areas of improvement which can then be confidentially communicated to manufacturers. This paper points out risks of accessing the Control and Automa...

  13. Tautological control systems

    CERN Document Server

    Lewis, Andrew D

    2014-01-01

    This brief presents a description of a new modelling framework for nonlinear/geometric control theory. The framework is intended to be—and shown to be—feedback-invariant. As such, Tautological Control Systems provides a platform for understanding fundamental structural problems in geometric control theory. Part of the novelty of the text stems from the variety of regularity classes, e.g., Lipschitz, finitely differentiable, smooth, real analytic, with which it deals in a comprehensive and unified manner. The treatment of the important real analytic class especially reflects recent work on real analytic topologies by the author. Applied mathematicians interested in nonlinear and geometric control theory will find this brief of interest as a starting point for work in which feedback invariance is important. Graduate students working in control theory may also find Tautological Control Systems to be a stimulating starting point for their research.

  14. Reset Control Systems

    CERN Document Server

    Baños, Alfonso

    2012-01-01

    Reset Control Systems addresses the analysis for reset control treating both its basic form which requires only that the state of the controller be reinitialized to zero (the reset action) each time the tracking error crosses zero (the reset condition), and some useful variations of the reset action (partial reset with fixed or variable reset percentage) and of the reset condition (fixed or variable reset band and anticipative reset). The issues regarding reset control – concepts and motivation; analysis tools; and the application of design methodologies to real-world examples – are given comprehensive coverage. The text opens with an historical perspective which moves from the seminal work of the Clegg integrator and Horowitz FORE to more recent approaches based on impulsive/hybrid control systems and explains the motivation for reset compensation. Preliminary material dealing with notation, basic definitions and results, and with the definition of the control problem under study is also included. The fo...

  15. Flight control actuation system

    Science.gov (United States)

    Wingett, Paul T. (Inventor); Gaines, Louie T. (Inventor); Evans, Paul S. (Inventor); Kern, James I. (Inventor)

    2006-01-01

    A flight control actuation system comprises a controller, electromechanical actuator and a pneumatic actuator. During normal operation, only the electromechanical actuator is needed to operate a flight control surface. When the electromechanical actuator load level exceeds 40 amps positive, the controller activates the pneumatic actuator to offset electromechanical actuator loads to assist the manipulation of flight control surfaces. The assistance from the pneumatic load assist actuator enables the use of an electromechanical actuator that is smaller in size and mass, requires less power, needs less cooling processes, achieves high output forces and adapts to electrical current variations. The flight control actuation system is adapted for aircraft, spacecraft, missiles, and other flight vehicles, especially flight vehicles that are large in size and travel at high velocities.

  16. Reactor limit control system

    International Nuclear Information System (INIS)

    Rubbel, F.E.

    1982-01-01

    The very extensive use of limitations in the operational field between protection system and closed-loop controls is an important feature of German understanding of operational safety. The design of limitations is based on very large activities in the computational field but mostly on the high level of the plant-wide own commissioning experience of a turnkey contractor. Limitations combine intelligence features of closed-loop controls with the high availability of protection systems. (orig.)

  17. Fluid flow control system

    International Nuclear Information System (INIS)

    Rion, Jacky.

    1982-01-01

    Fluid flow control system featuring a series of grids placed perpendicular to the fluid flow direction, characterized by the fact that it is formed of a stack of identical and continuous grids, each of which consists of identical meshes forming a flat lattice. The said meshes are offset from one grid to the next. This system applies in particular to flow control of the coolant flowing at the foot of an assembly of a liquid metal cooled nuclear reactor [fr

  18. Internal control system

    OpenAIRE

    Pavésková, Ivana

    2014-01-01

    Dissertation focuse on the internal control system in the enterprises, aims to map the control system by focusing on the purchasing department. I focused on the purchasing process, because with an increasing trends of outsourcing services and the increasing interconnectedness of enterprises increases the risk of fraud currently in the purchasing process. To the research was selected the sample of companies from the banking and non-banking environment, to which were sent a questionnaire focusi...

  19. Systems and Control Engineering

    Indian Academy of Sciences (India)

    Home; Journals; Resonance – Journal of Science Education; Volume 4; Issue 1. Systems and Control Engineering - Notions of Control. A Rama Kalyan J R Vengateswaran. General Article Volume 4 Issue 1 January 1999 pp 45-52. Fulltext. Click here to view fulltext PDF. Permanent link:

  20. Controllability of nilpotent systems

    International Nuclear Information System (INIS)

    Bravo, V.A.; Martin, L.S.

    1993-02-01

    The purpose of this paper is to investigate algebraic conditions which give information about the controllability of invariant control systems on nilpotent Lie groups. With the same purpose, the authors use the co-adjoint representation and define the concept of symplectic vectors. We study the existence of these objects to analyze the controllability. In particular, we obtain a characterization when G is simply connected. (author). 9 refs

  1. AMYGDALA MICROCIRCUITS CONTROLLING LEARNED FEAR

    Science.gov (United States)

    Duvarci, Sevil; Pare, Denis

    2014-01-01

    We review recent work on the role of intrinsic amygdala networks in the regulation of classically conditioned defensive behaviors, commonly known as conditioned fear. These new developments highlight how conditioned fear depends on far more complex networks than initially envisioned. Indeed, multiple parallel inhibitory and excitatory circuits are differentially recruited during the expression versus extinction of conditioned fear. Moreover, shifts between expression and extinction circuits involve coordinated interactions with different regions of the medial prefrontal cortex. However, key areas of uncertainty remain, particularly with respect to the connectivity of the different cell types. Filling these gaps in our knowledge is important because much evidence indicates that human anxiety disorders results from an abnormal regulation of the networks supporting fear learning. PMID:24908482

  2. Technological learning in bioenergy systems

    International Nuclear Information System (INIS)

    Junginger, Martin; Visser, Erika de; Hjort-Gregersen, Kurt; Koornneef, Joris; Raven, Rob; Faaij, Andre; Turkenburg, Wim

    2006-01-01

    The main goal of this article is to determine whether cost reductions in different bioenergy systems can be quantified using the experience curve approach, and how specific issues (arising from the complexity of biomass energy systems) can be addressed. This is pursued by case studies on biofuelled combined heat and power (CHP) plants in Sweden, global development of fluidized bed boilers and Danish biogas plants. As secondary goal, the aim is to identify learning mechanisms behind technology development and cost reduction for the biomass energy systems investigated. The case studies reveal large difficulties to devise empirical experience curves for investment costs of biomass-fuelled power plants. To some extent, this is due to lack of (detailed) data. The main reason, however, are varying plant costs due to differences in scale, fuel type, plant layout, region etc. For fluidized bed boiler plants built on a global level, progress ratios (PRs) for the price of entire plants lies approximately between 90-93% (which is typical for large plant-like technologies). The costs for the boiler section alone was found to decline much faster. The experience curve approach delivers better results, when the production costs of the final energy carrier are analyzed. Electricity from biofuelled CHP-plants yields PRs of 91-92%, i.e. an 8-9% reduction of electricity production costs with each cumulative doubling of electricity production. The experience curve for biogas production displays a PR of 85% from 1984 to the beginning of 1990, and then levels to approximately 100% until 2002. For technologies developed on a local level (e.g. biogas plants), learning-by-using and learning-by-interacting are important learning mechanism, while for CHP plants utilizing fluidized bed boilers, upscaling is probably one of the main mechanisms behind cost reductions

  3. Self-teaching neural network learns difficult reactor control problem

    International Nuclear Information System (INIS)

    Jouse, W.C.

    1989-01-01

    A self-teaching neural network used as an adaptive controller quickly learns to control an unstable reactor configuration. The network models the behavior of a human operator. It is trained by allowing it to operate the reactivity control impulsively. It is punished whenever either the power or fuel temperature stray outside technical limits. Using a simple paradigm, the network constructs an internal representation of the punishment and of the reactor system. The reactor is constrained to small power orbits

  4. Amygdala subsystems and control of feeding behavior by learned cues.

    Science.gov (United States)

    Petrovich, Gorica D; Gallagher, Michela

    2003-04-01

    A combination of behavioral studies and a neural systems analysis approach has proven fruitful in defining the role of the amygdala complex and associated circuits in fear conditioning. The evidence presented in this chapter suggests that this approach is also informative in the study of other adaptive functions that involve the amygdala. In this chapter we present a novel model to study learning in an appetitive context. Furthermore, we demonstrate that long-recognized connections between the amygdala and the hypothalamus play a crucial role in allowing learning to modulate feeding behavior. In the first part we describe a behavioral model for motivational learning. In this model a cue that acquires motivational properties through pairings with food delivery when an animal is hungry can override satiety and promote eating in sated rats. Next, we present evidence that a specific amygdala subsystem (basolateral area) is responsible for allowing such learned cues to control eating (override satiety and promote eating in sated rats). We also show that basolateral amygdala mediates these actions via connectivity with the lateral hypothalamus. Lastly, we present evidence that the amygdalohypothalamic system is specific for the control of eating by learned motivational cues, as it does not mediate another function that depends on intact basolateral amygdala, namely, the ability of a conditioned cue to support new learning based on its acquired value. Knowledge about neural systems through which food-associated cues specifically control feeding behavior provides a defined model for the study of learning. In addition, this model may be informative for understanding mechanisms of maladaptive aspects of learned control of eating that contribute to eating disorders and more moderate forms of overeating.

  5. CEBAF control system

    International Nuclear Information System (INIS)

    Bork, R.; Grubb, C.; Lahti, G.; Navarro, E.; Sage, J.

    1989-01-01

    A logic-based computer control system is in development at CEBAF. This Unix/C language software package, running on a distributed, hierarchical system of workstation and supervisory minicomputers, interfaces to hardware via CAMAC. Software aspects to be covered are ladder logic, interactive database generation, networking, and graphic user interfaces. 1 fig

  6. PSR control system

    International Nuclear Information System (INIS)

    Clout, P.N.; Conley, A.P.; Bair, S.S.; Fuka, M.A.; Sandford, E.L.; Lander, R.F.; Wells, F.D.

    1985-01-01

    The control system for the Proton Storage Ring at Los Alamos has been essentially completed. Modifications are being applied that are required in the light of machine physics and operating experience. The present design of the system is described and future planned modifications are indicated

  7. Environment control system

    International Nuclear Information System (INIS)

    Sammarone, D.G.

    1978-01-01

    Disclosed is a system for controlling the environment of an enclosed area in nuclear reactor installations. The system permits the changing of the environment from nitrogen to air, or from air to nitrogen, without the release of any radioactivity or process gas to the outside atmosphere

  8. Multi Car Elevator Control by using Learning Automaton

    Science.gov (United States)

    Shiraishi, Kazuaki; Hamagami, Tomoki; Hirata, Hironori

    We study an adaptive control technique for multi car elevators (MCEs) by adopting learning automatons (LAs.) The MCE is a high performance and a near-future elevator system with multi shafts and multi cars. A strong point of the system is that realizing a large carrying capacity in small shaft area. However, since the operation is too complicated, realizing an efficient MCE control is difficult for top-down approaches. For example, “bunching up together" is one of the typical phenomenon in a simple traffic environment like the MCE. Furthermore, an adapting to varying environment in configuration requirement is a serious issue in a real elevator service. In order to resolve these issues, having an autonomous behavior is required to the control system of each car in MCE system, so that the learning automaton, as the solutions for this requirement, is supposed to be appropriate for the simple traffic control. First, we assign a stochastic automaton (SA) to each car control system. Then, each SA varies its stochastic behavior distributions for adapting to environment in which its policy is evaluated with each passenger waiting times. That is LA which learns the environment autonomously. Using the LA based control technique, the MCE operation efficiency is evaluated through simulation experiments. Results show the technique enables reducing waiting times efficiently, and we confirm the system can adapt to the dynamic environment.

  9. The ISOLDE control system

    Science.gov (United States)

    Deloose, I.; Pace, A.

    1994-12-01

    The two CERN isotope separators named ISOLDE have been running on the new Personal Computer (PC) based control system since April 1992. The new architecture that makes heavy use of the commercial software and hardware of the PC market has been implemented on the 1700 geographically distributed control channels of the two separators and their experimental area. Eleven MSDOS Intel-based PCs with approximately 80 acquisition and control boards are used to access the equipment and are controlled from three PCs running Microsoft Windows used as consoles through a Novell Local Area Network. This paper describes the interesting solutions found and discusses the reduced programming workload and costs that have been obtained.

  10. Learning Management Systems on Blended Learning Courses

    DEFF Research Database (Denmark)

    Kuran, Mehmet Şükrü; Pedersen, Jens Myrup; Elsner, Raphael

    2017-01-01

    LMSes, Moodle, Blackboard Learn, Canvas, and Stud.IP with respect to these. We explain how these features were utilized to increase the efficiency, tractability, and quality of experience of the course. We found that an LMS with advanced features such as progress tracking, modular course support...

  11. Reinforcement learning for optimal control of low exergy buildings

    International Nuclear Information System (INIS)

    Yang, Lei; Nagy, Zoltan; Goffin, Philippe; Schlueter, Arno

    2015-01-01

    Highlights: • Implementation of reinforcement learning control for LowEx Building systems. • Learning allows adaptation to local environment without prior knowledge. • Presentation of reinforcement learning control for real-life applications. • Discussion of the applicability for real-life situations. - Abstract: Over a third of the anthropogenic greenhouse gas (GHG) emissions stem from cooling and heating buildings, due to their fossil fuel based operation. Low exergy building systems are a promising approach to reduce energy consumption as well as GHG emissions. They consists of renewable energy technologies, such as PV, PV/T and heat pumps. Since careful tuning of parameters is required, a manual setup may result in sub-optimal operation. A model predictive control approach is unnecessarily complex due to the required model identification. Therefore, in this work we present a reinforcement learning control (RLC) approach. The studied building consists of a PV/T array for solar heat and electricity generation, as well as geothermal heat pumps. We present RLC for the PV/T array, and the full building model. Two methods, Tabular Q-learning and Batch Q-learning with Memory Replay, are implemented with real building settings and actual weather conditions in a Matlab/Simulink framework. The performance is evaluated against standard rule-based control (RBC). We investigated different neural network structures and find that some outperformed RBC already during the learning phase. Overall, every RLC strategy for PV/T outperformed RBC by over 10% after the third year. Likewise, for the full building, RLC outperforms RBC in terms of meeting the heating demand, maintaining the optimal operation temperature and compensating more effectively for ground heat. This allows to reduce engineering costs associated with the setup of these systems, as well as decrease the return-of-invest period, both of which are necessary to create a sustainable, zero-emission building

  12. E-Learning Systems, Environments and Approaches

    OpenAIRE

    Isaias, P.; Spector, J.M.; Ifenthaler, D.; Sampson, D.G.

    2015-01-01

    The volume consists of twenty-five chapters selected from among peer-reviewed papers presented at the CELDA (Cognition and Exploratory Learning in the Digital Age) 2013 Conference held in Fort Worth, Texas, USA, in October 2013 and also from world class scholars in e-learning systems, environments and approaches. The following sub-topics are included: Exploratory Learning Technologies (Part I), e-Learning social web design (Part II), Learner communities through e-Learning implementations (Par...

  13. TMX magnet control system

    International Nuclear Information System (INIS)

    Goerz, D.A.

    1978-01-01

    A control system utilizing a microcomputer has been developed that controls the power supplies driving the Tandem Mirror Experiment (TMX) magnet set and monitors magnet coil operation. The magnet set consists of 18 magnet coils that are driven by 26 dc power supplies. There are two possible modes of operation with this system: a pulse mode where the coils are pulsed on for several seconds with a dc power consumption of 16 MW; and a continuous mode where the coils can run steady state at 10 percent of maximum current ratings. The processor has been given an active control role and serves as an interface between the operator and electronic circuitry that controls the magnet power supplies. This microcomputer also collects and processes data from many analog singal monitors in the coil circuits and numerous status signals from the supplies. Placing the microcomputer in an active control role has yielded a compact, cost effective system that simplifies the magnet system operation and has proven to be very reliable. This paper will describe the TMX magnet control sytem and discuss its development

  14. The role of interactive control systems in obtaining internal consistency in the management control system package

    DEFF Research Database (Denmark)

    Toldbod, Thomas; Israelsen, Poul

    2014-01-01

    Companies rely on multiple Management Control Systems to obtain their short and long term objectives. When applying a multifaceted perspective on Management Control System the concept of internal consistency has been found to be important in obtaining goal congruency in the company. However, to d...... management is aware of this shortcoming they use the cybernetic controls more interactively to overcome this shortcoming, whereby the cybernetic controls are also used as a learning platform and not just for performance control....

  15. System control and display

    International Nuclear Information System (INIS)

    Jacobs, J.

    1977-01-01

    The system described was designed, developed, and installed on short time scales and primarily utilized of-the-shelf military and commercial hardware. The system was designed to provide security-in-depth and multiple security options with several stages of redundancy. Under normal operating conditions, the system is computer controlled with manual backup during abnormal conditions. Sensor alarm data are processed in conjunction with weather data to reduce nuisance alarms. A structured approach is used to order alarmed sectors for assessment. Alarm and video information is presented to security personnel in an interactive mode. Historical operational data are recorded for system evaluation

  16. IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING

    Data.gov (United States)

    National Aeronautics and Space Administration — IMPROVING CAUSE DETECTION SYSTEMS WITH ACTIVE LEARNING ISAAC PERSING AND VINCENT NG Abstract. Active learning has been successfully applied to many natural language...

  17. Ion implantation control system

    International Nuclear Information System (INIS)

    Gault, R. B.; Keutzer, L. L.

    1985-01-01

    A control system is disclosed for an ion implantation system of the type in which the wafers to be implanted are mounted around the periphery of a disk which rotates and also moves in a radial direction relative to an ion beam to expose successive sections of each wafer to the radiation. The control system senses beam current which passes through one or more apertures in the disk and is collected by a Faraday cup. This current is integrated to obtain a measure of charge which is compared with a calculated value based upon the desired ion dosage and other parameters. The resultant controls the number of incremental steps the rotating disk moves radially to expose the adjacent sections of each wafer. This process is continued usually with two or more traverses until the entire surface of each wafer has been implanted with the proper ion dosage

  18. Personalised Learning Object System Based on Self-Regulated Learning Theories

    Directory of Open Access Journals (Sweden)

    Ali Alharbi

    2014-06-01

    Full Text Available Self-regulated learning has become an important construct in education research in the last few years. Selfregulated learning in its simple form is the learner’s ability to monitor and control the learning process. There is increasing research in the literature on how to support students become more self-regulated learners. However, the advancement in the information technology has led to paradigm changes in the design and development of educational content. The concept of learning object instructional technology has emerged as a result of this shift in educational technology paradigms. This paper presents the results of a study that investigated the potential educational effectiveness of a pedagogical framework based on the self-regulated learning theories to support the design of learning object systems to help computer science students. A prototype learning object system was developed based on the contemporary research on self-regulated learning. The system was educationally evaluated in a quasi-experimental study over two semesters in a core programming languages concepts course. The evaluation revealed that a learning object system that takes into consideration contemporary research on self-regulated learning can be an effective learning environment to support computer science education.

  19. Biological Systems Thinking for Control Engineering Design

    Directory of Open Access Journals (Sweden)

    D. J. Murray-Smith

    2004-01-01

    Full Text Available Artificial neural networks and genetic algorithms are often quoted in discussions about the contribution of biological systems thinking to engineering design. This paper reviews work on the neuromuscular system, a field in which biological systems thinking could make specific contributions to the development and design of automatic control systems for mechatronics and robotics applications. The paper suggests some specific areas in which a better understanding of this biological control system could be expected to contribute to control engineering design methods in the future. Particular emphasis is given to the nonlinear nature of elements within the neuromuscular system and to processes of neural signal processing, sensing and system adaptivity. Aspects of the biological system that are of particular significance for engineering control systems include sensor fusion, sensor redundancy and parallelism, together with advanced forms of signal processing for adaptive and learning control

  20. Optimal Control via Reinforcement Learning with Symbolic Policy Approximation

    NARCIS (Netherlands)

    Kubalìk, Jiřì; Alibekov, Eduard; Babuska, R.; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

    2017-01-01

    Model-based reinforcement learning (RL) algorithms can be used to derive optimal control laws for nonlinear dynamic systems. With continuous-valued state and input variables, RL algorithms have to rely on function approximators to represent the value function and policy mappings. This paper

  1. The TRISTAN control system

    International Nuclear Information System (INIS)

    Kurokawa, Shinichi; Akiyama, Atsuyoshi; Ishii, Kazuhiro; Kadokura, Eiichi; Katoh, Tadahiko; Kawamoto, Takashi; Kikutani, Eiji; Kimura, Yoshitaka; Koiso, Haruyo; Komada, Ichitaka; Kudo, Kikuo; Naito, Takashi; Oide, Katsunobu; Takeda, Shigeru; Uchino, Kenji; Urakawa, Junji; Shinomoto, Manabu; Kurihara, Michio; Abe, Kenichi

    1986-01-01

    The 8 GeV accumulation ring and the 30 GeV main ring of TRISTAN, an accelerator-storage ring complex at KEK, are controlled by a highly computerized control system. Twenty-four minicomputers are linked by optical fiber cables to form an N-to-N token ring network. The transmission speed on the cables is 10 Mbps. From each minicomputer, a CAMAC serial highway extends to the controlled equipment. At present, twenty minicomputers are connected to the network and are used to control the accumulation ring. The software system is based on the NODAL language devised at the CERN SPS. The KEK NODAL system retains main features of the original NODAL: the interpretive scheme, the multi-computer programming facility, and the data-module concept. In addition, it has the following features: (1) fast execution due to the compiler-interpreter method, (2) a multi-computer file system (3), a full-screen editing facility, and (4) a dynamic linkage scheme for data modules and NODAL functions. The accelerators are operated through five operator consoles, each of which is mangaged by one minicomputer in the network. An operator console contains two 20-inch high-resolution color graphic displays, a pair of touch-panels, and ten small TV monitors. One touch-panel is used to select a program and a piece of equipment to be controlled; the other is used mainly to perform the console actions. (orig.)

  2. A neural fuzzy controller learning by fuzzy error propagation

    Science.gov (United States)

    Nauck, Detlef; Kruse, Rudolf

    1992-01-01

    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.

  3. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Dong Yun Kim; Poong Hyun Seong; .

    1997-01-01

    In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate gains, which minimize the error of system. The proposed algorithm can reduce the time and effort required for obtaining the fuzzy rules through the intelligent learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller. (author)

  4. Machine Learning for Flapping Wing Flight Control

    NARCIS (Netherlands)

    Goedhart, Menno; van Kampen, E.; Armanini, S.F.; de Visser, C.C.; Chu, Q.

    2018-01-01

    Flight control of Flapping Wing Micro Air Vehicles is challenging, because of their complex dynamics and variability due to manufacturing inconsistencies. Machine Learning algorithms can be used to tackle these challenges. A Policy Gradient algorithm is used to tune the gains of a

  5. Approaches to Learning to Control Dynamic Uncertainty

    Directory of Open Access Journals (Sweden)

    Magda Osman

    2015-10-01

    Full Text Available In dynamic environments, when faced with a choice of which learning strategy to adopt, do people choose to mostly explore (maximizing their long term gains or exploit (maximizing their short term gains? More to the point, how does this choice of learning strategy influence one’s later ability to control the environment? In the present study, we explore whether people’s self-reported learning strategies and levels of arousal (i.e., surprise, stress correspond to performance measures of controlling a Highly Uncertain or Moderately Uncertain dynamic environment. Generally, self-reports suggest a preference for exploring the environment to begin with. After which, those in the Highly Uncertain environment generally indicated they exploited more than those in the Moderately Uncertain environment; this difference did not impact on performance on later tests of people’s ability to control the dynamic environment. Levels of arousal were also differentially associated with the uncertainty of the environment. Going beyond behavioral data, our model of dynamic decision-making revealed that, in actual fact, there was no difference in exploitation levels between those in the highly uncertain or moderately uncertain environments, but there were differences based on sensitivity to negative reinforcement. We consider the implications of our findings with respect to learning and strategic approaches to controlling dynamic uncertainty.

  6. RHIC control system

    Energy Technology Data Exchange (ETDEWEB)

    Barton, D.S. E-mail: dsbarton@bnl.gov; Binello, S.; Buxton, W.; Clifford, T.; D' Ottavio, T.; Hartmann, H.; Hoff, L.T.; Katz, R.; Kennell, S.; Kerner, T.; Laster, J.; Lee, R.C.; Marusic, A.; Michnoff, R.; Morris, J.; Oerter, B.R.; Olsen, R.; Piacentino, J.; Skelly, J.F

    2003-03-01

    The RHIC control system architecture is hierarchical and consists of two physical layers with a fiber-optic network connection. The Front-End Level systems consist of VME chassis with processors running a real-time operating system and both VME I/O modules and remote bus interfaces. Accelerator device software interfaces are implemented as objects in C++. The network implementation uses high speed, switched Ethernet technology. Specialized hardware modules were built for waveform control of power supplies, multiplexed signal acquisition, and timing services. The Console Level systems are Unix workstations. A strong emphasis has been given to developing highly reusable, standard software tools for use in building physics and diagnostic application software.

  7. RHIC control system

    International Nuclear Information System (INIS)

    Barton, D.S.; Binello, S.; Buxton, W.; Clifford, T.; D'Ottavio, T.; Hartmann, H.; Hoff, L.T.; Katz, R.; Kennell, S.; Kerner, T.; Laster, J.; Lee, R.C.; Marusic, A.; Michnoff, R.; Morris, J.; Oerter, B.R.; Olsen, R.; Piacentino, J.; Skelly, J.F.

    2003-01-01

    The RHIC control system architecture is hierarchical and consists of two physical layers with a fiber-optic network connection. The Front-End Level systems consist of VME chassis with processors running a real-time operating system and both VME I/O modules and remote bus interfaces. Accelerator device software interfaces are implemented as objects in C++. The network implementation uses high speed, switched Ethernet technology. Specialized hardware modules were built for waveform control of power supplies, multiplexed signal acquisition, and timing services. The Console Level systems are Unix workstations. A strong emphasis has been given to developing highly reusable, standard software tools for use in building physics and diagnostic application software

  8. Learning in tele-autonomous systems using Soar

    Science.gov (United States)

    Laird, John E.; Yager, Eric S.; Tuck, Christopher M.; Hucka, Michael

    1989-01-01

    Robo-Soar is a high-level robot arm control system implemented in Soar. Robo-Soar learns to perform simple block manipulation tasks using advice from a human. Following learning, the system is able to perform similar tasks without external guidance. It can also learn to correct its knowledge, using its own problem solving in addition to outside guidance. Robo-Soar corrects its knowledge by accepting advice about relevance of features in its domain, using a unique integration of analytic and empirical learning techniques.

  9. ZEUS hardware control system

    Science.gov (United States)

    Loveless, R.; Erhard, P.; Ficenec, J.; Gather, K.; Heath, G.; Iacovacci, M.; Kehres, J.; Mobayyen, M.; Notz, D.; Orr, R.; Orr, R.; Sephton, A.; Stroili, R.; Tokushuku, K.; Vogel, W.; Whitmore, J.; Wiggers, L.

    1989-12-01

    The ZEUS collaboration is building a system to monitor, control and document the hardware of the ZEUS detector. This system is based on a network of VAX computers and microprocessors connected via ethernet. The database for the hardware values will be ADAMO tables; the ethernet connection will be DECNET, TCP/IP, or RPC. Most of the documentation will also be kept in ADAMO tables for easy access by users.

  10. ZEUS hardware control system

    International Nuclear Information System (INIS)

    Loveless, R.; Erhard, P.; Ficenec, J.; Gather, K.; Heath, G.; Iacovacci, M.; Kehres, J.; Mobayyen, M.; Notz, D.; Orr, R.; Sephton, A.; Stroili, R.; Tokushuku, K.; Vogel, W.; Whitmore, J.; Wiggers, L.

    1989-01-01

    The ZEUS collaboration is building a system to monitor, control and document the hardware of the ZEUS detector. This system is based on a network of VAX computers and microprocessors connected via ethernet. The database for the hardware values will be ADAMO tables; the ethernet connection will be DECNET, TCP/IP, or RPC. Most of the documentation will also be kept in ADAMO tables for easy access by users. (orig.)

  11. Critical Points in Distance Learning System

    Directory of Open Access Journals (Sweden)

    Airina Savickaitė

    2013-08-01

    Full Text Available Purpose – This article presents the results of distance learning system analysis, i.e. the critical elements of the distance learning system. The critical points of distance learning are a part of distance education online environment interactivity/community process model. The most important is the fact that the critical point is associated with distance learning participants. Design/methodology/approach – Comparative review of articles and analysis of distance learning module. Findings – A modern man is a lifelong learner and distance learning is a way to be a modern person. The focus on a learner and feedback is the most important thing of learning distance system. Also, attention should be paid to the lecture-appropriate knowledge and ability to convey information. Distance system adaptation is the way to improve the learner’s learning outcomes. Research limitations/implications – Different learning disciplines and learning methods may have different critical points. Practical implications – The information of analysis could be important for both lecturers and students, who studies distance education systems. There are familiar critical points which may deteriorate the quality of learning. Originality/value – The study sought to develop remote systems for applications in order to improve the quality of knowledge. Keywords: distance learning, process model, critical points. Research type: review of literature and general overview.

  12. Control of complex systems

    CERN Document Server

    Albertos, Pedro; Blanke, Mogens; Isidori, Alberto; Schaufelberger, Walter; Sanz, Ricardo

    2001-01-01

    The world of artificial systems is reaching complexity levels that es­ cape human understanding. Surface traffic, electricity distribution, air­ planes, mobile communications, etc. , are examples that demonstrate that we are running into problems that are beyond classical scientific or engi­ neering knowledge. There is an ongoing world-wide effort to understand these systems and develop models that can capture its behavior. The reason for this work is clear, if our lack of understanding deepens, we will lose our capability to control these systems and make they behave as we want. Researchers from many different fields are trying to understand and develop theories for complex man-made systems. This book presents re­ search from the perspective of control and systems theory. The book has grown out of activities in the research program Control of Complex Systems (COSY). The program has been sponsored by the Eu­ ropean Science Foundation (ESF) which for 25 years has been one of the leading players in stimula...

  13. Applications of learning based systems at AREVA group

    International Nuclear Information System (INIS)

    Jeanmart, F.; Leclerc, C.

    2006-01-01

    As part of its work on advanced information systems, AREVA is exploring the use of computerized tools based on 'machine learning' techniques. Some of these studies are being carried out by EURIWARE - continuing on from previous work done by AREVA NC - focused on the supervision of complex systems. Systems based on machine learning techniques are one of the possible solutions being investigated by AREVA: knowing that the stakes are high and involve better anticipation and control and high financial considerations. (authors)

  14. Authoring Systems Delivering Reusable Learning Objects

    Directory of Open Access Journals (Sweden)

    George Nicola Sammour

    2009-10-01

    Full Text Available A three layer e-learning course development model has been defined based on a conceptual model of learning content object. It starts by decomposing the learning content into small chunks which are initially placed in a hierarchic structure of units and blocks. The raw content components, being the atomic learning objects (ALO, were linked to the blocks and are structured in the database. We set forward a dynamic generation of LO's using re-usable e-learning raw materials or ALO’s In that view we need a LO authoring/ assembling system fitting the requirements of interoperability and reusability and starting from selecting the raw learning content from the learning materials content database. In practice authoring systems are used to develop e-learning courses. The company EDUWEST has developed an authoring system that is database based and will be SCORM compliant in the near future.

  15. Establishment of a Learning Management System

    International Nuclear Information System (INIS)

    Han, K. W.; Kim, Y. T.; Lee, E. J.; Min, B. J.

    2006-01-01

    A web-based learning management system (LMS) has been established to address the need of customized education and training of Nuclear Training Center (NTC) of KAERI. The LMS is designed to deal with various learning types (e.g. on-line, off-line and blended) and a practically comprehensive learning activity cycle (e.g. course preparation, registration, learning, and postlearning) as well as to be user-friendly. A test with an example course scenario on the established system has shown its satisfactory performance. This paper discusses details of the established webbased learning management system in terms of development approach and functions of the LMS

  16. HESYRL control system status

    International Nuclear Information System (INIS)

    Yao Chihyuan

    1992-01-01

    HESYRL synchrotron radiation storage ring was completed in 1989 and has been in commissioning since then. Now it has met its design specification and is ready for synchrotron light experiments. Control system of the project was completed in 1989 and some modifications were made during commissioning. This paper describes its present configuration, status and upgrading plan. (author)

  17. Fault Tolerant Control Systems

    DEFF Research Database (Denmark)

    Bøgh, S. A.

    This thesis considered the development of fault tolerant control systems. The focus was on the category of automated processes that do not necessarily comprise a high number of identical sensors and actuators to maintain safe operation, but still have a potential for improving immunity to component...

  18. Lighting Control Systems Handbook.

    Science.gov (United States)

    1985-06-01

    cost, both initial and operating. Initially, the control system designer must collect in- formation and then study and weigh several areas including...8217odLe 045. Pearl Harbor. III: Code 11 Pearl Harbor ar ho I ir I L ’ odk 402. R IYI& [’. Plearl II arbor I II: Li bra ry. Pearl HaIitrbor. I ai

  19. GLCTA control system

    International Nuclear Information System (INIS)

    Terunuma, N.; Hayano, H.; Higo, T.; Saeki, T.; Suehara, T.; Watanabe, K.

    2004-01-01

    Research and development for the high power X-band RF technologies have been performed on the GLC Test Accelerator, GLCTA, since fall of 2003. The control system of this facility is based on the PC-Linux servers that handle the CAMAC, VME and PLC modules. Automated RF processing and data accumulation of the RF breakdown have been performed. (author)

  20. Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control

    Directory of Open Access Journals (Sweden)

    Takashi Watanabe

    2010-01-01

    Full Text Available Feedforward controller would be useful for hybrid Functional Electrical Stimulation (FES system using powered orthotic devices. In this paper, Feedback Error Learning (FEL controller for FES (FEL-FES controller was examined using an inverse statics model (ISM with an inverse dynamics model (IDM to realize a feedforward FES controller. For FES application, the ISM was tested in learning off line using training data obtained by PID control of very slow movements. Computer simulation tests in controlling wrist joint movements showed that the ISM performed properly in positioning task and that IDM learning was improved by using the ISM showing increase of output power ratio of the feedforward controller. The simple ISM learning method and the FEL-FES controller using the ISM would be useful in controlling the musculoskeletal system that has nonlinear characteristics to electrical stimulation and therefore is expected to be useful in applying to hybrid FES system using powered orthotic device.

  1. Emotional Learning Based Intelligent Controllers for Rotor Flux Oriented Control of Induction Motor

    Science.gov (United States)

    Abdollahi, Rohollah; Farhangi, Reza; Yarahmadi, Ali

    2014-08-01

    This paper presents design and evaluation of a novel approach based on emotional learning to improve the speed control system of rotor flux oriented control of induction motor. The controller includes a neuro-fuzzy system with speed error and its derivative as inputs. A fuzzy critic evaluates the present situation, and provides the emotional signal (stress). The controller modifies its characteristics so that the critics stress is reduced. The comparative simulation results show that the proposed controller is more robust and hence found to be a suitable replacement of the conventional PI controller for the high performance industrial drive applications.

  2. Internet Congestion Control System

    Directory of Open Access Journals (Sweden)

    Pranoto Rusmin

    2010-10-01

    Full Text Available Internet congestion occurs when resource demands exceeds the network capacity. But, it is not the only reason. Congestion can happen on some users because some others user has higher sending rate. Then some users with lower sending rate will experience congestion. This partial congestion is caused by inexactly feedback. At this moment congestion are solved by the involvement of two controlling mechanisms. These mechanisms are flow/congestion control in the TCP source and Active Queue Management (AQM in the router. AQM will provide feedback to the source a kind of indication for the occurrence of the congestion in the router, whereas the source will adapt the sending rate appropriate with the feedback. These mechanisms are not enough to solve internet congestion problem completely. Therefore, this paper will explain internet congestion causes, weakness, and congestion control technique that researchers have been developed. To describe congestion system mechanisms and responses, the system will be simulated by Matlab.

  3. PEP computer control system

    International Nuclear Information System (INIS)

    1979-03-01

    This paper describes the design and performance of the computer system that will be used to control and monitor the PEP storage ring. Since the design is essentially complete and much of the system is operational, the system is described as it is expected to 1979. Section 1 of the paper describes the system hardware which includes the computer network, the CAMAC data I/O system, and the operator control consoles. Section 2 describes a collection of routines that provide general services to applications programs. These services include a graphics package, data base and data I/O programs, and a director programm for use in operator communication. Section 3 describes a collection of automatic and semi-automatic control programs, known as SCORE, that contain mathematical models of the ring lattice and are used to determine in real-time stable paths for changing beam configuration and energy and for orbit correction. Section 4 describes a collection of programs, known as CALI, that are used for calibration of ring elements

  4. The ISOLDE control system

    International Nuclear Information System (INIS)

    Deloose, I.; Pace, A.

    1994-01-01

    The two CERN isotope separators named ISOLDE have been running on the new Personal Computer (PC) based control system since April 1992. The new architecture that makes heavy use of the commercial software and hardware of the PC market has been implemented on the 1700 geographically distributed control channels of the two separators and their experimental area. Eleven MSDOS Intel-based PCs with approximately 80 acquisition and control boards are used to access the equipment and are controlled from three PCs running Microsoft Windows used as consoles through a Novell Local Area Network. This paper describes the interesting solutions found and discusses the reduced programming workload and costs that have been obtained. ((orig.))

  5. Game-Theoretic Learning in Distributed Control

    KAUST Repository

    Marden, Jason R.

    2018-01-05

    In distributed architecture control problems, there is a collection of interconnected decision-making components that seek to realize desirable collective behaviors through local interactions and by processing local information. Applications range from autonomous vehicles to energy to transportation. One approach to control of such distributed architectures is to view the components as players in a game. In this approach, two design considerations are the components’ incentives and the rules that dictate how components react to the decisions of other components. In game-theoretic language, the incentives are defined through utility functions, and the reaction rules are online learning dynamics. This chapter presents an overview of this approach, covering basic concepts in game theory, special game classes, measures of distributed efficiency, utility design, and online learning rules, all with the interpretation of using game theory as a prescriptive paradigm for distributed control design.

  6. Instructional control of reinforcement learning: a behavioral and neurocomputational investigation.

    Science.gov (United States)

    Doll, Bradley B; Jacobs, W Jake; Sanfey, Alan G; Frank, Michael J

    2009-11-24

    Humans learn how to behave directly through environmental experience and indirectly through rules and instructions. Behavior analytic research has shown that instructions can control behavior, even when such behavior leads to sub-optimal outcomes (Hayes, S. (Ed.). 1989. Rule-governed behavior: cognition, contingencies, and instructional control. Plenum Press.). Here we examine the control of behavior through instructions in a reinforcement learning task known to depend on striatal dopaminergic function. Participants selected between probabilistically reinforced stimuli, and were (incorrectly) told that a specific stimulus had the highest (or lowest) reinforcement probability. Despite experience to the contrary, instructions drove choice behavior. We present neural network simulations that capture the interactions between instruction-driven and reinforcement-driven behavior via two potential neural circuits: one in which the striatum is inaccurately trained by instruction representations coming from prefrontal cortex/hippocampus (PFC/HC), and another in which the striatum learns the environmentally based reinforcement contingencies, but is "overridden" at decision output. Both models capture the core behavioral phenomena but, because they differ fundamentally on what is learned, make distinct predictions for subsequent behavioral and neuroimaging experiments. Finally, we attempt to distinguish between the proposed computational mechanisms governing instructed behavior by fitting a series of abstract "Q-learning" and Bayesian models to subject data. The best-fitting model supports one of the neural models, suggesting the existence of a "confirmation bias" in which the PFC/HC system trains the reinforcement system by amplifying outcomes that are consistent with instructions while diminishing inconsistent outcomes.

  7. Dynamitron control systems

    International Nuclear Information System (INIS)

    Lisanti, Thomas F.

    2005-01-01

    The Dynamitron control system utilizes the latest personal computer technology in control circuitry and components. Both the DPC-2000 and newer Millennium series of control systems make use of their modular architecture in both software and hardware to keep up with customer and engineering demands. This also allows the main structure of the software to remain constant for the user while software drivers are easily changed as hardware demands are modified and improved. The system is presented as four units; the Remote I/O (Input/Output), Local Analog and Digital I/O, Operator Interface and the Main Computer. The operator is provided with a selection of many informative screen displays. The control program handles all graphic screen displays and the updating of these screens directly; it does not communicate to a display terminal. This adds to the quick response and excellent operator feedback received while operating the accelerator. The CPU also has the ability to store and record all process variable setpoints for each product that will be treated. All process parameters are printed to a report at regular intervals during a process run for record keeping

  8. Wireless Remote Control System

    Directory of Open Access Journals (Sweden)

    Adrian Tigauan

    2012-06-01

    Full Text Available This paper presents the design of a wireless remote control system based on the ZigBee communication protocol. Gathering data from sensors or performing control tasks through wireless communication is advantageous in situations in which the use of cables is impractical. An Atmega328 microcontroller (from slave device is used for gathering data from the sensors and transmitting it to a coordinator device with the help of the XBee modules. The ZigBee standard is suitable for low-cost, low-data-rate and low-power wireless networks implementations. The XBee-PRO module, designed to meet ZigBee standards, requires minimal power for reliable data exchange between devices over a distance of up to 1600m outdoors. A key component of the ZigBee protocol is the ability to support networking and this can be used in a wireless remote control system. This system may be employed e.g. to control temperature and humidity (SHT11 sensor and light intensity (TSL230 sensor levels inside a commercial greenhouse.

  9. Management control system description

    Energy Technology Data Exchange (ETDEWEB)

    Bence, P. J.

    1990-10-01

    This Management Control System (MCS) description describes the processes used to manage the cost and schedule of work performed by Westinghouse Hanford Company (Westinghouse Hanford) for the US Department of Energy, Richland Operations Office (DOE-RL), Richland, Washington. Westinghouse Hanford will maintain and use formal cost and schedule management control systems, as presented in this document, in performing work for the DOE-RL. This MCS description is a controlled document and will be modified or updated as required. This document must be approved by the DOE-RL; thereafter, any significant change will require DOE-RL concurrence. Westinghouse Hanford is the DOE-RL operations and engineering contractor at the Hanford Site. Activities associated with this contract (DE-AC06-87RL10930) include operating existing plant facilities, managing defined projects and programs, and planning future enhancements. This document is designed to comply with Section I-13 of the contract by providing a description of Westinghouse Hanford's cost and schedule control systems used in managing the above activities. 5 refs., 22 figs., 1 tab.

  10. Expert Students in Social Learning Management Systems

    Science.gov (United States)

    Avogadro, Paolo; Calegari, Silvia; Dominoni, Matteo Alessandro

    2016-01-01

    Purpose: A social learning management system (social LMS) is a tool which favors social interactions and allows scholastic institutions to supervise and guide the learning process. The inclusion of the social feature to a "normal" LMS leads to the creation of educational social networks (EduSN), where the students interact and learn. The…

  11. Access control system operation

    International Nuclear Information System (INIS)

    Barnes, L.D.

    1981-06-01

    An automated method for the control and monitoring of personnel movement throughout the site was developed under contract to the Department of Energy by Allied-General Nuclear Services (AGNS) at the Barnwell Nuclear Fuel Plant (BNFP). These automated features provide strict enforcement of personnel access policy without routine patrol officer involvement. Identification methods include identification by employee ID number, identification by voice verification and identification by physical security officer verification. The ability to grant each level of access authority is distributed over the organization to prevent any single individual at any level in the organization from being capable of issuing an authorization for entry into sensitive areas. Each access event is recorded. As access events occur, the inventory of both the entered and the exited control area is updated so that a current inventory is always available for display. The system has been operated since 1979 in a development mode and many revisions have been implemented in hardware and software as areas were added to the system. Recent changes have involved the installation of backup systems and other features required to achieve a high reliability. The access control system and recent operating experience are described

  12. The COSY control system

    International Nuclear Information System (INIS)

    Bongers, N.; Hacker, U.; Henn, K.; Richert, A.; Simon, M.; Sobotta, K.; Stephan, M.; Vashegyi, T.; Weinert, A.

    1992-01-01

    The COSY control system architecture is organized strongly hierarchically with distributed intelligence and extensive use of standards. At the top level of computer control hardware work stations give the operator graphical access to the process. For these tasks Hewlett Packard HP 9000 Series 700 computers with HP-UX and X-Windows/Motif are in use. Also used as work-cells this RISC computers give computing power for model calculations and long term databases. This computers are interconnected using Ethernet and TCP/IP to the next layer of hardware. (author) 3 refs.; 5 figs

  13. Micro Learning: A Modernized Education System

    Directory of Open Access Journals (Sweden)

    Omer Jomah

    2016-03-01

    Full Text Available Learning is an understanding of how the human brain is wired to learning rather than to an approach or a system. It is one of the best and most frequent approaches for the 21st century learners. Micro learning is more interesting due to its way of teaching and learning the content in a small, very specific burst. Here the learners decide what and when to learn. Content, time, curriculum, form, process, mediality, and learning type are the dimensions of micro learning. Our paper will discuss about micro learning and about the micro-content management system. The study will reflect the views of different users, and will analyze the collected data. Finally, it will be concluded with its pros and cons. 

  14. Steering the dynamics within reduced space through quantum learning control

    International Nuclear Information System (INIS)

    Kim, Young Sik

    2003-01-01

    In quantum dynamics of many-body systems, to identify the Hamiltonian becomes more difficult very rapidly as the number of degrees of freedom increases. In order to simplify the dynamics and to deduce dynamically relevant Hamiltonian information, it is desirable to control the dynamics to lie within a reduced space. With a judicious choice for the cost functional, the closed loop optimal control experiments can be manipulated efficiently to steer the dynamics to lie within a subspace of the system eigenstates without requiring any prior detailed knowledge about the system Hamiltonian. The procedure is simulated for optimally controlled population transfer experiments in the system of two degrees of freedom. To show the feasibility of steering the dynamics to lie in a specified subspace, the learning algorithms guiding the dynamics are presented along with frequency filtering. The results demonstrate that the optimal control fields derive the system to the desired target state through the desired subspace

  15. Concurrent Learning of Control in Multi agent Sequential Decision Tasks

    Science.gov (United States)

    2018-04-17

    Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views

  16. Computer Simulation Tests of Feedback Error Learning Controller with IDM and ISM for Functional Electrical Stimulation in Wrist Joint Control

    OpenAIRE

    Watanabe, Takashi; Sugi, Yoshihiro

    2010-01-01

    Feedforward controller would be useful for hybrid Functional Electrical Stimulation (FES) system using powered orthotic devices. In this paper, Feedback Error Learning (FEL) controller for FES (FEL-FES controller) was examined using an inverse statics model (ISM) with an inverse dynamics model (IDM) to realize a feedforward FES controller. For FES application, the ISM was tested in learning off line using training data obtained by PID control of very slow movements. Computer simulation tests ...

  17. The UNK control system

    International Nuclear Information System (INIS)

    Alferov, V.N.; Brook, V.L.; Dunaitsev, A.F.

    1992-01-01

    The IHEP proton Accelerating and Storage Complex (UNK) includes in its first stage a 400 GeV conventional and a 3000 GeV superconducting ring placed in the same underground tunnel of 20.7 km circumference. The beam will be injected into UNK from the existing 70 GeV accelerator U-70. The experimental programme which is planned to start in 1995, will include 3000 GeV fixed target and 400 + 3000 GeV colliding beams physics. The size and complexity of the UNK dictate a distributed multiprocessor architecture of the control system. About 4000 of 8/16 bit controllers, directly attached to the UNK equipment will perform low level control and data acquisition tasks. The equipment controllers will be connected via the MIL-1553 field bus to VME based 32-bit front end computers. The TCP/IP network will interconnect front end computers in the UNK equipment buildings with UNIX workstations and servers in the Main Control Room. The report presents the general architecture and current status of the UNK control. (author)

  18. Learning-based position control of a closed-kinematic chain robot end-effector

    Science.gov (United States)

    Nguyen, Charles C.; Zhou, Zhen-Lei

    1990-01-01

    A trajectory control scheme whose design is based on learning theory, for a six-degree-of-freedom (DOF) robot end-effector built to study robotic assembly of NASA hardwares in space is presented. The control scheme consists of two control systems: the feedback control system and the learning control system. The feedback control system is designed using the concept of linearization about a selected operating point, and the method of pole placement so that the closed-loop linearized system is stabilized. The learning control scheme consisting of PD-type learning controllers, provides additional inputs to improve the end-effector performance after each trial. Experimental studies performed on a 2 DOF end-effector built at CUA, for three tracking cases show that actual trajectories approach desired trajectories as the number of trials increases. The tracking errors are substantially reduced after only five trials.

  19. Automatic heating control system

    Energy Technology Data Exchange (ETDEWEB)

    Whittle, A.J.

    1989-11-15

    A heating control system for buildings comprises at least one heater incorporating heat storage means, a first sensor for detecting temperature within the building, means for setting a demand temperature, a second sensor for detecting outside temperature, a timer, and means for determining the switch on time of the heat storage means on the basis of the demand temperature and the internal and external temperatures. The system may additionally base the switch on time of the storage heater(s) on the heating and cooling rates of the building (as determined from the sensed temperatures); or on the anticipated daytime temperature (determined from the sensed night time temperature). (author).

  20. ENGINEERING OF UNIVERSITY INTELLIGENT LEARNING SYSTEMS

    Directory of Open Access Journals (Sweden)

    Vasiliy M. Trembach

    2016-01-01

    Full Text Available In the article issues of engineering intelligent tutoring systems of University with adaptation are considered. The article also dwells on some modern approaches to engineering of information systems. It shows the role of engineering e-learning devices (systems in system engineering. The article describes the basic principles of system engineering and these principles are expanded regarding to intelligent information systems. The structure of intelligent learning systems with adaptation of the individual learning environments based on services is represented in the article.

  1. Learning and the Instructional System

    Science.gov (United States)

    Kozma, Robert B.

    1977-01-01

    Faculty members can use information about six components of the learning situation to increase student learning. The nature, function, and interrelationships of the following elements are described: instructor, content, medium, student, evaluation, environment, and implementation. (Editor/LBH)

  2. Intelligent Lighting Control System

    OpenAIRE

    García, Elena; Rodríguez González, Sara; de Paz Santana, Juan F.; Bajo Pérez, Javier

    2014-01-01

    This paper presents an adaptive architecture that allows centralized control of public lighting and intelligent management, in order to economise on lighting and maintain maximum comfort status of the illuminated areas. To carry out this management, architecture merges various techniques of artificial intelligence (AI) and statistics such as artificial neural networks (ANN), multi-agent systems (MAS), EM algorithm, methods based on ANOVA and a Service Oriented Aproach (SOA). It performs optim...

  3. Controlling chaotic systems via nonlinear feedback control

    International Nuclear Information System (INIS)

    Park, Ju H.

    2005-01-01

    In this article, a new method to control chaotic systems is proposed. Using Lyapunov method, we design a nonlinear feedback controller to make the controlled system be stabilized. A numerical example is given to illuminate the design procedure and advantage of the result derived

  4. NSLS control system upgrade

    International Nuclear Information System (INIS)

    Smith, J.D.; Ramamoorthy, Susila; Tang, Y.N.

    1994-01-01

    The NSLS consists of two storage rings, a booster and a linac. A major upgrade of the control system (installed in 1978) was undertaken and has been completed. The computer architecture is being changed from a three level star-network to a two level distributed system. The microprocessor subsystem, host computer and workstations, communication link and the main software components are being upgraded or replaced. Since the NSLS rings operate twenty four hours a day a year with minimum maintenance time, the key requirement during the upgrade phase is a non-disruptive transition with minimum downtime. Concurrent with the upgrade, some immediate improvements were required. This paper describes the various components of the upgraded system and outlines the future plans. ((orig.))

  5. NSLS control system upgrade

    International Nuclear Information System (INIS)

    Smith, J.D.; Ramamoorthy, S.; Tang, Yong N.

    1995-01-01

    The NSLS consists of two storage rings, a booster and a linac. A major upgrade of the control system (installed in 1978) was undertaken and has been completed. The computer architecture is being changed from a three level star-network to a two level distributed system. The microprocessor subsystem, host computer and workstations, communication link and the main software components are being upgraded or replaced. Since the NSLS rings operate twenty four hours a day a year with minimum maintenance time, the key requirement during the upgrade phase is a non-disruptive transition with minimum downtime. Concurrent with the upgrade, some immediate improvements were required. This paper describes the various components of the upgraded system and outlines the future plans

  6. Cost Estimation and Control for Flight Systems

    Science.gov (United States)

    Hammond, Walter E.; Vanhook, Michael E. (Technical Monitor)

    2002-01-01

    Good program management practices, cost analysis, cost estimation, and cost control for aerospace flight systems are interrelated and depend upon each other. The best cost control process cannot overcome poor design or poor systems trades that lead to the wrong approach. The project needs robust Technical, Schedule, Cost, Risk, and Cost Risk practices before it can incorporate adequate Cost Control. Cost analysis both precedes and follows cost estimation -- the two are closely coupled with each other and with Risk analysis. Parametric cost estimating relationships and computerized models are most often used. NASA has learned some valuable lessons in controlling cost problems, and recommends use of a summary Project Manager's checklist as shown here.

  7. Incoherent control of locally controllable quantum systems

    International Nuclear Information System (INIS)

    Dong Daoyi; Zhang Chenbin; Rabitz, Herschel; Pechen, Alexander; Tarn, T.-J.

    2008-01-01

    An incoherent control scheme for state control of locally controllable quantum systems is proposed. This scheme includes three steps: (1) amplitude amplification of the initial state by a suitable unitary transformation, (2) projective measurement of the amplified state, and (3) final optimization by a unitary controlled transformation. The first step increases the amplitudes of some desired eigenstates and the corresponding probability of observing these eigenstates, the second step projects, with high probability, the amplified state into a desired eigenstate, and the last step steers this eigenstate into the target state. Within this scheme, two control algorithms are presented for two classes of quantum systems. As an example, the incoherent control scheme is applied to the control of a hydrogen atom by an external field. The results support the suggestion that projective measurements can serve as an effective control and local controllability information can be used to design control laws for quantum systems. Thus, this scheme establishes a subtle connection between control design and controllability analysis of quantum systems and provides an effective engineering approach in controlling quantum systems with partial controllability information.

  8. Crawling the Control System

    International Nuclear Information System (INIS)

    Larrieu, Theodore

    2009-01-01

    Information about accelerator operations and the control system resides in various formats in a variety of places on the lab network. There are operating procedures, technical notes, engineering drawings, and other formal controlled documents. There are programmer references and API documentation generated by tools such as doxygen and javadoc. There are the thousands of electronic records generated by and stored in databases and applications such as electronic logbooks, training materials, wikis, and bulletin boards and the contents of text-based configuration files and log files that can also be valuable sources of information. The obvious way to aggregate all these sources is to index them with a search engine that users can then query from a web browser. Toward this end, the Google 'mini' search appliance was selected and implemented because of its low cost and its simple web-based configuration and management. In addition to crawling and indexing electronic documents, the appliance provides an API that has been used to supplement search results with live control system data such as current values of EPICS process variables and graphs of recent data from the archiver.

  9. Radiation control system

    International Nuclear Information System (INIS)

    Murao, Mitsuo.

    1985-01-01

    Purpose: To rapidly and suitably performing planning and designation by radiation-working control systems in the radiation controlled area of nuclear power plant. Method: Various informations regarding radiation exposure are arranged and actual exposure data are statistically stored, to thereby perform forecasting calculation for the radiation exposure upon workings in the plurality of working regions in the radiation controlled area. Based on the forecast values and the registered workers' exposure dose in the past workings are alocated successively such that the total exposure does upon conducting the workings is less than the limited value, to prepare working plans in the areas. Further, procedures for preparing a series of documents regarding the workings in the radiation area are automated to rapidly and properly provide the informations serving to the planning and designation for the radiation workings. As a result, the radiation managers' burnden can be mitigated and an efficient working management system can be provided, in view of the exposure management and personal management. (Kamimura, M.)

  10. Agile Design of Sewer System Control

    NARCIS (Netherlands)

    Van Nooijen, R.P.; Kolechkina, A.G.; Van Leeuwen, P.E.R.M.; Van Velzen, E.

    2011-01-01

    We describe the first part of an attempt to include stakeholder participation in the design of a central automatic controller for a sewer system in a small pilot project (five subcatchments) and present lessons learned so far. The pilot is part of a project aimed at the improvement of water quality

  11. Control of optical systems

    Science.gov (United States)

    Founds, D.

    1988-01-01

    Some of the current and planned activities at the Air Force Systems Command in structures and controls for optical-type systems are summarized. Many of the activities are contracted to industry; one task is an in-house program which includes a hardware test program. The objective of the in-house program, referred to as the Aluminum Beam Expander Structure (ABES), is to address issues involved in on-orbit system identification. The structure, which appears similar to the LDR backup structure, is about 35 feet tall. The activity to date has been limited to acquisition of about 250 hours of test data. About 30 hours of data per excitation force is gathered in order to obtain sufficient data for a good statistical estimate of the structural parameters. The development of an Integrated Structural Modeling (ISM) computer program is being done by Boeing Aerospace Company. The objective of the contracted effort is to develop a combined optics, structures, thermal, controls, and multibody dynamics simulation code.

  12. Feedwater control system

    International Nuclear Information System (INIS)

    Cook, B.M.

    1982-01-01

    Excessive swing of the feedwater in nuclear reactor power supply apparatus on the occurrence of a transient is suppressed by injecting an anticipatory compensating signal (δWsub(fw)) into the control for the feedwater. Typical overshoot occurs on removal of a large part of the load, the steam flow is reduced so that the conventional control system reduces the flow of feedwater. At the same time there is a reduction of feedwater level in the steam generator because of the collapse of the bubbles under increased steam pressure. By the time the control responds to the drop in level, the apparatus has begun to stabilize so that there is overshoot. The anticipatory signal is derived from the boiling power (BP) which is a function of the nuclear power (Qsub(N)) developed, the enthalpy of saturated water (hsub(s)) and the enthalpy of the feedwater injected into the steam generator (hsub(fw)). From the boiling power (BP) and the increment in steam pressure resulting from the transient an anticipatory increment of feedwater flow is derived. This increment is added to the other parameters controlling the feedwater. (author)

  13. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Verbert, Katrien; Santos, Olga

    2010-01-01

    Manouselis, N., Drachsler, H., Verbert, K., & Santos, C. S. (Eds.) (2010). Recommender System in Technology Enhanced Learning. Elsevier Procedia Computer Science: Volume 1, Issue 2. Proceedings of the 1st Workshop on Recommender Systems for Technology Enhanced Learning (RecSysTEL). September, 29-30,

  14. Panorama of Recommender Systems to Support Learning

    NARCIS (Netherlands)

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga C.; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in TechnologyEnhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender

  15. Reconceptualizing Learning as a Dynamical System.

    Science.gov (United States)

    Ennis, Catherine D.

    1992-01-01

    Dynamical systems theory can increase our understanding of the constantly evolving learning process. Current research using experimental and interpretive paradigms focuses on describing the attractors and constraints stabilizing the educational process. Dynamical systems theory focuses attention on critical junctures in the learning process as…

  16. Divulging Personal Information within Learning Analytics Systems

    Science.gov (United States)

    Ifenthaler, Dirk; Schumacher, Clara

    2015-01-01

    The purpose of this study was to investigate if students are prepared to release any personal data in order to inform learning analytics systems. Besides the well-documented benefits of learning analytics, serious concerns and challenges are associated with the application of these data driven systems. Most notably, empirical evidence regarding…

  17. Adaptive e-learning system using ontology

    OpenAIRE

    Yarandi, Maryam; Tawil, Abdel-Rahman; Jahankhani, Hossein

    2011-01-01

    This paper proposes an innovative ontological approach to design a personalised e-learning system which creates a tailored workflow for individual learner. Moreover, the learning content and sequencing logic is separated into content model and pedagogical model to increase the reusability and flexibility of the system.

  18. Phase Control in Nonlinear Systems

    Science.gov (United States)

    Zambrano, Samuel; Seoane, Jesús M.; Mariño, Inés P.; Sanjuán, Miguel A. F.; Meucci, Riccardo

    The following sections are included: * Introduction * Phase Control of Chaos * Description of the model * Numerical exploration of phase control of chaos * Experimental evidence of phase control of chaos * Phase Control of Intermittency in Dynamical Systems * Crisis-induced intermittency and its control * Experimental setup and implementation of the phase control scheme * Phase control of the laser in the pre-crisis regime * Phase control of the intermittency after the crisis * Phase control of the intermittency in the quadratic map * Phase Control of Escapes in Open Dynamical Systems * Control of open dynamical systems * Model description * Numerical simulations and heuristic arguments * Experimental implementation in an electronic circuit * Conclusions and Discussions * Acknowledgments * References

  19. PEP instrumentation and control system

    Energy Technology Data Exchange (ETDEWEB)

    Melen, R.

    1980-06-01

    This paper describes the operating characteristics of the primary components that form the PEP Instrumentation and Control System. Descriptions are provided for the computer control system, beam monitors, and other support systems.

  20. PEP instrumentation and control system

    International Nuclear Information System (INIS)

    Melen, R.

    1980-06-01

    This paper describes the operating characteristics of the primary components that form the PEP Instrumentation and Control System. Descriptions are provided for the computer control system, beam monitors, and other support systems

  1. Recommender Systems in Technology Enhanced Learning

    NARCIS (Netherlands)

    Manouselis, Nikos; Drachsler, Hendrik; Vuorikari, Riina; Hummel, Hans; Koper, Rob

    2010-01-01

    Manouselis, N., Drachsler, H., Vuorikari, R., Hummel, H. G. K., & Koper, R. (2011). Recommender Systems in Technology Enhanced Learning. In P. B. Kantor, F. Ricci, L. Rokach, & B. Shapira (Eds.), Recommender Systems Handbook (pp. 387-415). Berlin: Springer.

  2. Environmental Control System Development

    Science.gov (United States)

    Flores Arroyo, Elvin A.

    2018-01-01

    Since before the first men landed on the moon, human beings have aspired to reach farther into space, to discover and answer the great mysteries that exist beyond imagination. To reach where no one has gone before. To able to see all the wonderful things that can be found in space and that only satellites have revealed to us during all this time. Considering the last trip to the moon, mankind has been evolving and improving their technology to reach destinations whose distances had been impossible to transit. To reach that goal, the National Aeronautics and Space Administration (NASA) has designed and developed the largest and most powerful rocket ever created by the human race, the Space Launch System - better known as the SLS. To be able to send this large rocket to space, Kennedy Space Center (KSC) is doing upgrades to their existing facilities and equipment. At Launch Pad 39B, they are setting up a new Environmental Control System (ECS) developed to supply the rocket with the correct gases and mixtures that will be needed for the rocket to launch. The ECS is similar to an air conditioning unit. The main functionality of it is to supply the SLS with the correct gas mixture for it to launch. Also the ECS has been required to reduce or eliminate the possibility of a complete system failure. The system is part of the Ground Support Equipment (GSE) for the SLS that will be going to the Moon and Mars.

  3. Automatically controlled training systems

    International Nuclear Information System (INIS)

    Milashenko, A.; Afanasiev, A.

    1990-01-01

    This paper reports that the computer system for NPP personnel training was developed for training centers in the Soviet Union. The system should be considered as the first step in training, taking into account that further steps are to be devoted to part-task and full scope simulator training. The training room consists of 8-12 IBM PC/AT personal computers combined into a network. A trainee accesses the system in a dialor manner. Software enables the instructor to determine the trainee's progress in different subjects of the program. The quality of any trainee preparedness may be evaluated by Knowledge Control operation. Simplified dynamic models are adopted for separate areas of the program. For example, the system of neutron flux monitoring has a dedicated model. Currently, training, requalification and support of professional qualifications of nuclear power plant operators is being emphasized. A significant number of emergency situations during work are occurring due to operator errors. Based on data from September-October 1989, more than half of all unplanned drops in power and stoppages of power plants were due to operator error. As a comparison, problems due to equipment malfunction accounted for no more than a third of the total. The role of personnel, especially of the operators, is significant during normal operations, since energy production costs as well as losses are influenced by the capability of the staff. These facts all point to the importance of quality training of personnel

  4. Panorama of recommender systems to support learning

    OpenAIRE

    Drachsler, Hendrik; Verbert, Katrien; Santos, Olga; Manouselis, Nikos

    2015-01-01

    This chapter presents an analysis of recommender systems in Technology-Enhanced Learning along their 15 years existence (2000-2014). All recommender systems considered for the review aim to support educational stakeholders by personalising the learning process. In this meta-review 82 recommender systems from 35 different countries have been investigated and categorised according to a given classification framework. The reviewed systems have been classified into 7 clusters according to their c...

  5. Learning Management Systems and E-Learning within Cyprus Universities

    Directory of Open Access Journals (Sweden)

    Amirkhanpour, Monaliz

    2011-01-01

    Full Text Available This paper presents an extensive research study and results on the use of existing open-source Learning Management Systems, or LMS within the public and private universities of Cyprus. The most significant objective of this research is the identification of the different types of E-Learning, i.e. Computer-Based Training (CBT, Technology-Based Learning (TBL, and Web-Based Training (WBT within Cyprus universities. The paper identifies the benefits and limitations of the main learning approaches used in higher educational institutions, i.e. synchronous and asynchronous learning, investigates the open-source LMS used in the Cypriot universities and compares their features with regards to students’ preferences for a collaborative E-Learning environment. The required data for this research study were collected from undergraduate and graduate students, alumni, faculty members, and IT professionals who currently work and/or study at the public and private universities of Cyprus. The most noteworthy recommendation of this study is the clear indication that most of the undergraduate students that extensively use the specific E-Learning platform of their university do not have a clear picture of the differences between an LMS and a VLE. This gap has to be gradually diminished in order to make optimum use of the different features offered by the specific E-Learning platform.

  6. Web-Based Learning Support System

    Science.gov (United States)

    Fan, Lisa

    Web-based learning support system offers many benefits over traditional learning environments and has become very popular. The Web is a powerful environment for distributing information and delivering knowledge to an increasingly wide and diverse audience. Typical Web-based learning environments, such as Web-CT, Blackboard, include course content delivery tools, quiz modules, grade reporting systems, assignment submission components, etc. They are powerful integrated learning management systems (LMS) that support a number of activities performed by teachers and students during the learning process [1]. However, students who study a course on the Internet tend to be more heterogeneously distributed than those found in a traditional classroom situation. In order to achieve optimal efficiency in a learning process, an individual learner needs his or her own personalized assistance. For a web-based open and dynamic learning environment, personalized support for learners becomes more important. This chapter demonstrates how to realize personalized learning support in dynamic and heterogeneous learning environments by utilizing Adaptive Web technologies. It focuses on course personalization in terms of contents and teaching materials that is according to each student's needs and capabilities. An example of using Rough Set to analyze student personal information to assist students with effective learning and predict student performance is presented.

  7. Systems approach for design control at Monitored Retrievable Storage Project

    International Nuclear Information System (INIS)

    Kumar, P.N.; Williams, J.R.

    1994-01-01

    This paper describes the systems approach in establishing design control for the Monitored Retrievable Storage Project design development. Key elements in design control are enumerated and systems engineering aspects are detailed. Application of lessons learned from the Yucca Mountain Project experience is addressed. An integrated approach combining quality assurance and systems engineering requirements is suggested to practice effective design control

  8. Intelligent control of an IPMC actuated manipulator using emotional learning-based controller

    Science.gov (United States)

    Shariati, Azadeh; Meghdari, Ali; Shariati, Parham

    2008-08-01

    In this research an intelligent emotional learning controller, Takagi- Sugeno- Kang (TSK) is applied to govern the dynamics of a novel Ionic-Polymer Metal Composite (IPMC) actuated manipulator. Ionic-Polymer Metal Composites are active actuators that show very large deformation in existence of low applied voltage. In this research, a new IPMC actuator is considered and applied to a 2-dof miniature manipulator. This manipulator is designed for miniature tasks. The control system consists of a set of neurofuzzy controller whose parameters are adapted according to the emotional learning rules, and a critic with task to assess the present situation resulted from the applied control action in terms of satisfactory achievement of the control goals and provides the emotional signal (the stress). The controller modifies its characteristics so that the critic's stress decreased.

  9. Reinforcement learning techniques for controlling resources in power networks

    Science.gov (United States)

    Kowli, Anupama Sunil

    As power grids transition towards increased reliance on renewable generation, energy storage and demand response resources, an effective control architecture is required to harness the full functionalities of these resources. There is a critical need for control techniques that recognize the unique characteristics of the different resources and exploit the flexibility afforded by them to provide ancillary services to the grid. The work presented in this dissertation addresses these needs. Specifically, new algorithms are proposed, which allow control synthesis in settings wherein the precise distribution of the uncertainty and its temporal statistics are not known. These algorithms are based on recent developments in Markov decision theory, approximate dynamic programming and reinforcement learning. They impose minimal assumptions on the system model and allow the control to be "learned" based on the actual dynamics of the system. Furthermore, they can accommodate complex constraints such as capacity and ramping limits on generation resources, state-of-charge constraints on storage resources, comfort-related limitations on demand response resources and power flow limits on transmission lines. Numerical studies demonstrating applications of these algorithms to practical control problems in power systems are discussed. Results demonstrate how the proposed control algorithms can be used to improve the performance and reduce the computational complexity of the economic dispatch mechanism in a power network. We argue that the proposed algorithms are eminently suitable to develop operational decision-making tools for large power grids with many resources and many sources of uncertainty.

  10. Learning Markov models for stationary system behaviors

    DEFF Research Database (Denmark)

    Chen, Yingke; Mao, Hua; Jaeger, Manfred

    2012-01-01

    to a single long observation sequence, and in these situations existing automatic learning methods cannot be applied. In this paper, we adapt algorithms for learning variable order Markov chains from a single observation sequence of a target system, so that stationary system properties can be verified using......Establishing an accurate model for formal verification of an existing hardware or software system is often a manual process that is both time consuming and resource demanding. In order to ease the model construction phase, methods have recently been proposed for automatically learning accurate...... the learned model. Experiments demonstrate that system properties (formulated as stationary probabilities of LTL formulas) can be reliably identified using the learned model....

  11. Research on intelligent algorithm of electro - hydraulic servo control system

    Science.gov (United States)

    Wang, Yannian; Zhao, Yuhui; Liu, Chengtao

    2017-09-01

    In order to adapt the nonlinear characteristics of the electro-hydraulic servo control system and the influence of complex interference in the industrial field, using a fuzzy PID switching learning algorithm is proposed and a fuzzy PID switching learning controller is designed and applied in the electro-hydraulic servo controller. The designed controller not only combines the advantages of the fuzzy control and PID control, but also introduces the learning algorithm into the switching function, which makes the learning of the three parameters in the switching function can avoid the instability of the system during the switching between the fuzzy control and PID control algorithms. It also makes the switch between these two control algorithm more smoother than that of the conventional fuzzy PID.

  12. Learning and Understanding System Stability Using Illustrative Dynamic Texture Examples

    Science.gov (United States)

    Liu, Huaping; Xiao, Wei; Zhao, Hongyan; Sun, Fuchun

    2014-01-01

    System stability is a basic concept in courses on dynamic system analysis and control for undergraduate students with computer science backgrounds. Typically, this was taught using a simple simulation example of an inverted pendulum. Unfortunately, many difficult issues arise in the learning and understanding of the concepts of stability,…

  13. Mountain Plains Learning Experience Guide: Automotive Repair. Course: Emission Systems.

    Science.gov (United States)

    Schramm, C.; Osland, Walt

    One of twelve individualized courses included in an automotive repair curriculum, this course covers the theory, testing, and servicing of automotive emission control systems. The course is comprised of one unit, Fundamentals of Emission Systems. The unit begins with a Unit Learning Experience Guide that gives directions for unit completion. The…

  14. Machine learning control taming nonlinear dynamics and turbulence

    CERN Document Server

    Duriez, Thomas; Noack, Bernd R

    2017-01-01

    This is the first book on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for optimal nonlinear control laws. This machine learning control (MLC) is motivated and detailed in Chapters 1 and 2. In Chapter 3, methods of linear control theory are reviewed. In Chapter 4, MLC is shown to reproduce known optimal control laws for linear dynamics (LQR, LQG). In Chapter 5, MLC detects and exploits a strongly nonlinear actuation mechanism of a low-dimensional dynamical system when linear control methods are shown to fail. Experimental control demonstrations from a laminar shear-layer to turbulent boundary-layers are reviewed in Chapter 6, followed by general good practices for experiments in Chapter 7. The book concludes with an outlook on the vast future applications of MLC in Chapter 8. Matlab codes are provided for easy reproducibility of the presented results. The book includes interviews with leading r...

  15. Human-level control through deep reinforcement learning

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A.; Veness, Joel; Bellemare, Marc G.; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K.; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-01

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  16. Human-level control through deep reinforcement learning.

    Science.gov (United States)

    Mnih, Volodymyr; Kavukcuoglu, Koray; Silver, David; Rusu, Andrei A; Veness, Joel; Bellemare, Marc G; Graves, Alex; Riedmiller, Martin; Fidjeland, Andreas K; Ostrovski, Georg; Petersen, Stig; Beattie, Charles; Sadik, Amir; Antonoglou, Ioannis; King, Helen; Kumaran, Dharshan; Wierstra, Daan; Legg, Shane; Hassabis, Demis

    2015-02-26

    The theory of reinforcement learning provides a normative account, deeply rooted in psychological and neuroscientific perspectives on animal behaviour, of how agents may optimize their control of an environment. To use reinforcement learning successfully in situations approaching real-world complexity, however, agents are confronted with a difficult task: they must derive efficient representations of the environment from high-dimensional sensory inputs, and use these to generalize past experience to new situations. Remarkably, humans and other animals seem to solve this problem through a harmonious combination of reinforcement learning and hierarchical sensory processing systems, the former evidenced by a wealth of neural data revealing notable parallels between the phasic signals emitted by dopaminergic neurons and temporal difference reinforcement learning algorithms. While reinforcement learning agents have achieved some successes in a variety of domains, their applicability has previously been limited to domains in which useful features can be handcrafted, or to domains with fully observed, low-dimensional state spaces. Here we use recent advances in training deep neural networks to develop a novel artificial agent, termed a deep Q-network, that can learn successful policies directly from high-dimensional sensory inputs using end-to-end reinforcement learning. We tested this agent on the challenging domain of classic Atari 2600 games. We demonstrate that the deep Q-network agent, receiving only the pixels and the game score as inputs, was able to surpass the performance of all previous algorithms and achieve a level comparable to that of a professional human games tester across a set of 49 games, using the same algorithm, network architecture and hyperparameters. This work bridges the divide between high-dimensional sensory inputs and actions, resulting in the first artificial agent that is capable of learning to excel at a diverse array of challenging tasks.

  17. Memory and cognitive control circuits in mathematical cognition and learning.

    Science.gov (United States)

    Menon, V

    2016-01-01

    Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal-frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal-frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. © 2016 Elsevier B.V. All rights reserved.

  18. Memory and cognitive control circuits in mathematical cognition and learning

    Science.gov (United States)

    Menon, V.

    2018-01-01

    Numerical cognition relies on interactions within and between multiple functional brain systems, including those subserving quantity processing, working memory, declarative memory, and cognitive control. This chapter describes recent advances in our understanding of memory and control circuits in mathematical cognition and learning. The working memory system involves multiple parietal–frontal circuits which create short-term representations that allow manipulation of discrete quantities over several seconds. In contrast, hippocampal–frontal circuits underlying the declarative memory system play an important role in formation of associative memories and binding of new and old information, leading to the formation of long-term memories that allow generalization beyond individual problem attributes. The flow of information across these systems is regulated by flexible cognitive control systems which facilitate the integration and manipulation of quantity and mnemonic information. The implications of recent research for formulating a more comprehensive systems neuroscience view of the neural basis of mathematical learning and knowledge acquisition in both children and adults are discussed. PMID:27339012

  19. Communication and control for networked complex systems

    CERN Document Server

    Peng, Chen; Han, Qing-Long

    2015-01-01

    This book reports on the latest advances in the study of Networked Control Systems (NCSs). It highlights novel research concepts on NCSs; the analysis and synthesis of NCSs with special attention to their networked character; self- and event-triggered communication schemes for conserving limited network resources; and communication and control co-design for improving the efficiency of NCSs. The book will be of interest to university researchers, control and network engineers, and graduate students in the control engineering, communication and network sciences interested in learning the core principles, methods, algorithms and applications of NCSs.

  20. Adaptive polymeric system for Hebbian type learning

    OpenAIRE

    2011-01-01

    Abstract We present the experimental realization of an adaptive polymeric system displaying a ?learning behaviour?. The system consists on a statistically organized networks of memristive elements (memory-resitors) based on polyaniline. In a such network the path followed by the current increments its conductivity, a property which makes the system able to mimic Hebbian type learning and have application in hardware neural networks. After discussing the working principle of ...

  1. Generic device controller for accelerator control systems

    International Nuclear Information System (INIS)

    Mariotti, R.; Buxton, W.; Frankel, R.; Hoff, L.

    1987-01-01

    Distributed intelligence for accelerator control systems has become possible as a result of advances in microprocessor technology. A system based on distributed intelligence is inherently versatile, readily expandable, and reduces both information flow across the system and software complexity in each unit

  2. Gaussian Processes for Data-Efficient Learning in Robotics and Control.

    Science.gov (United States)

    Deisenroth, Marc Peter; Fox, Dieter; Rasmussen, Carl Edward

    2015-02-01

    Autonomous learning has been a promising direction in control and robotics for more than a decade since data-driven learning allows to reduce the amount of engineering knowledge, which is otherwise required. However, autonomous reinforcement learning (RL) approaches typically require many interactions with the system to learn controllers, which is a practical limitation in real systems, such as robots, where many interactions can be impractical and time consuming. To address this problem, current learning approaches typically require task-specific knowledge in form of expert demonstrations, realistic simulators, pre-shaped policies, or specific knowledge about the underlying dynamics. In this paper, we follow a different approach and speed up learning by extracting more information from data. In particular, we learn a probabilistic, non-parametric Gaussian process transition model of the system. By explicitly incorporating model uncertainty into long-term planning and controller learning our approach reduces the effects of model errors, a key problem in model-based learning. Compared to state-of-the art RL our model-based policy search method achieves an unprecedented speed of learning. We demonstrate its applicability to autonomous learning in real robot and control tasks.

  3. ISO learning approximates a solution to the inverse-controller problem in an unsupervised behavioral paradigm.

    Science.gov (United States)

    Porr, Bernd; von Ferber, Christian; Wörgötter, Florentin

    2003-04-01

    In "Isotropic Sequence Order Learning" (pp. 831-864 in this issue), we introduced a novel algorithm for temporal sequence learning (ISO learning). Here, we embed this algorithm into a formal nonevaluating (teacher free) environment, which establishes a sensor-motor feedback. The system is initially guided by a fixed reflex reaction, which has the objective disadvantage that it can react only after a disturbance has occurred. ISO learning eliminates this disadvantage by replacing the reflex-loop reactions with earlier anticipatory actions. In this article, we analytically demonstrate that this process can be understood in terms of control theory, showing that the system learns the inverse controller of its own reflex. Thereby, this system is able to learn a simple form of feedforward motor control.

  4. Prototype learning and dissociable categorization systems in Alzheimer's disease.

    Science.gov (United States)

    Heindel, William C; Festa, Elena K; Ott, Brian R; Landy, Kelly M; Salmon, David P

    2013-08-01

    Recent neuroimaging studies suggest that prototype learning may be mediated by at least two dissociable memory systems depending on the mode of acquisition, with A/Not-A prototype learning dependent upon a perceptual representation system located within posterior visual cortex and A/B prototype learning dependent upon a declarative memory system associated with medial temporal and frontal regions. The degree to which patients with Alzheimer's disease (AD) can acquire new categorical information may therefore critically depend upon the mode of acquisition. The present study examined A/Not-A and A/B prototype learning in AD patients using procedures that allowed direct comparison of learning across tasks. Despite impaired explicit recall of category features in all tasks, patients showed differential patterns of category acquisition across tasks. First, AD patients demonstrated impaired prototype induction along with intact exemplar classification under incidental A/Not-A conditions, suggesting that the loss of functional connectivity within visual cortical areas disrupted the integration processes supporting prototype induction within the perceptual representation system. Second, AD patients demonstrated intact prototype induction but impaired exemplar classification during A/B learning under observational conditions, suggesting that this form of prototype learning is dependent on a declarative memory system that is disrupted in AD. Third, the surprisingly intact classification of both prototypes and exemplars during A/B learning under trial-and-error feedback conditions suggests that AD patients shifted control from their deficient declarative memory system to a feedback-dependent procedural memory system when training conditions allowed. Taken together, these findings serve to not only increase our understanding of category learning in AD, but to also provide new insights into the ways in which different memory systems interact to support the acquisition of

  5. Intelligent Web-Based Learning System with Personalized Learning Path Guidance

    Science.gov (United States)

    Chen, C. M.

    2008-01-01

    Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

  6. Coordination control of distributed systems

    CERN Document Server

    Villa, Tiziano

    2015-01-01

    This book describes how control of distributed systems can be advanced by an integration of control, communication, and computation. The global control objectives are met by judicious combinations of local and nonlocal observations taking advantage of various forms of communication exchanges between distributed controllers. Control architectures are considered according to  increasing degrees of cooperation of local controllers:  fully distributed or decentralized controlcontrol with communication between controllers,  coordination control, and multilevel control.  The book covers also topics bridging computer science, communication, and control, like communication for control of networks, average consensus for distributed systems, and modeling and verification of discrete and of hybrid systems. Examples and case studies are introduced in the first part of the text and developed throughout the book. They include: control of underwater vehicles, automated-guided vehicles on a container terminal, contro...

  7. Computer-aided auscultation learning system for nursing technique instruction.

    Science.gov (United States)

    Hou, Chun-Ju; Chen, Yen-Ting; Hu, Ling-Chen; Chuang, Chih-Chieh; Chiu, Yu-Hsien; Tsai, Ming-Shih

    2008-01-01

    Pulmonary auscultation is a physical assessment skill learned by nursing students for examining the respiratory system. Generally, a sound simulator equipped mannequin is used to group teach auscultation techniques via classroom demonstration. However, nursing students cannot readily duplicate this learning environment for self-study. The advancement of electronic and digital signal processing technologies facilitates simulating this learning environment. This study aims to develop a computer-aided auscultation learning system for assisting teachers and nursing students in auscultation teaching and learning. This system provides teachers with signal recording and processing of lung sounds and immediate playback of lung sounds for students. A graphical user interface allows teachers to control the measuring device, draw lung sound waveforms, highlight lung sound segments of interest, and include descriptive text. Effects on learning lung sound auscultation were evaluated for verifying the feasibility of the system. Fifteen nursing students voluntarily participated in the repeated experiment. The results of a paired t test showed that auscultative abilities of the students were significantly improved by using the computer-aided auscultation learning system.

  8. Patterns for Designing Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Symeon; Papasalouros, Andreas

    2003-01-01

    Learning Management Systems are sophisticated web-based applications that are being engineered today in increasing numbers by numerous institutions and companies that want to get involved in e-learning either for providing services to third parties, or for educating and training their own people.

  9. Process Systems Engineering Education: Learning by Research

    Science.gov (United States)

    Abbas, A.; Alhammadi, H. Y.; Romagnoli, J. A.

    2009-01-01

    In this paper, we discuss our approach in teaching the final-year course Process Systems Engineering. Students are given ownership of the course by transferring to them the responsibility of learning. A project-based group environment stimulates learning while solving a real engineering problem. We discuss postgraduate student involvement and how…

  10. Learning and Organizational Effectiveness: A Systems Perspective

    Science.gov (United States)

    Andreadis, Nicholas

    2009-01-01

    The challenge for leaders today is to create and develop the capability of their organization. Leaders must perceive and manage their organization as a dynamic, open system where learning is the core competence underlying innovation, growth, and sustainability. Creating a culture of learning is the first work of leadership. This article presents a…

  11. A Distributed Intelligent E-Learning System

    Science.gov (United States)

    Kristensen, Terje

    2016-01-01

    An E-learning system based on a multi-agent (MAS) architecture combined with the Dynamic Content Manager (DCM) model of E-learning, is presented. We discuss the benefits of using such a multi-agent architecture. Finally, the MAS architecture is compared with a pure service-oriented architecture (SOA). This MAS architecture may also be used within…

  12. Division 1137 property control system

    Energy Technology Data Exchange (ETDEWEB)

    Pastor, D.J.

    1982-01-01

    An automated data processing property control system was developed by Mobile and Remote Range Division 1137. This report describes the operation of the system and examines ways of using it in operational planning and control.

  13. Learning control of a flight simulator stick

    NARCIS (Netherlands)

    Velthuis, W.J.R.; de Vries, Theodorus J.A.; Vrielink, Koen H.J.; Wierda, G.J.; Borghuis, André

    1998-01-01

    Aimportant part of a flight simulator is its control loading system, which is the part that emulates the behaviour of an aircraft as experienced by the pilot through the stick. Such a system consists of a model of the aircraft that is to be simulated and a stick that is driven by an electric motor.

  14. Generic device controller for accelerator control systems

    International Nuclear Information System (INIS)

    Mariotti, R.; Buxton, W.; Frankel, R.; Hoff, L.

    1987-01-01

    A new distributed intelligence control system has become operational at the AGS for transport, injection, and acceleration of heavy ions. A brief description of the functionality of the physical devices making up the system is given. An attempt has been made to integrate the devices for accelerator specific interfacing into a standard microprocessor system, namely, the Universal Device Controller (UDC). The main goals for such a generic device controller are to provide: local computing power; flexibility to configure; and real time event handling. The UDC assemblies and software are described

  15. Biomimetic Hybrid Feedback Feedforward Neural-Network Learning Control.

    Science.gov (United States)

    Pan, Yongping; Yu, Haoyong

    2017-06-01

    This brief presents a biomimetic hybrid feedback feedforward neural-network learning control (NNLC) strategy inspired by the human motor learning control mechanism for a class of uncertain nonlinear systems. The control structure includes a proportional-derivative controller acting as a feedback servo machine and a radial-basis-function (RBF) NN acting as a feedforward predictive machine. Under the sufficient constraints on control parameters, the closed-loop system achieves semiglobal practical exponential stability, such that an accurate NN approximation is guaranteed in a local region along recurrent reference trajectories. Compared with the existing NNLC methods, the novelties of the proposed method include: 1) the implementation of an adaptive NN control to guarantee plant states being recurrent is not needed, since recurrent reference signals rather than plant states are utilized as NN inputs, which greatly simplifies the analysis and synthesis of the NNLC and 2) the domain of NN approximation can be determined a priori by the given reference signals, which leads to an easy construction of the RBF-NNs. Simulation results have verified the effectiveness of this approach.

  16. On Restructurable Control System Theory

    Science.gov (United States)

    Athans, M.

    1983-01-01

    The state of stochastic system and control theory as it impacts restructurable control issues is addressed. The multivariable characteristics of the control problem are addressed. The failure detection/identification problem is discussed as a multi-hypothesis testing problem. Control strategy reconfiguration, static multivariable controls, static failure hypothesis testing, dynamic multivariable controls, fault-tolerant control theory, dynamic hypothesis testing, generalized likelihood ratio (GLR) methods, and adaptive control are discussed.

  17. Building machine learning systems with Python

    CERN Document Server

    Richert, Willi

    2013-01-01

    This is a tutorial-driven and practical, but well-grounded book showcasing good Machine Learning practices. There will be an emphasis on using existing technologies instead of showing how to write your own implementations of algorithms. This book is a scenario-based, example-driven tutorial. By the end of the book you will have learnt critical aspects of Machine Learning Python projects and experienced the power of ML-based systems by actually working on them.This book primarily targets Python developers who want to learn about and build Machine Learning into their projects, or who want to pro

  18. Neural systems for control

    National Research Council Canada - National Science Library

    Omidvar, Omid; Elliott, David L

    1997-01-01

    ... is reprinted with permission from A. Barto, "Reinforcement Learning," Handbook of Brain Theory and Neural Networks, M.A. Arbib, ed.. The MIT Press, Cambridge, MA, pp. 804-809, 1995. Chapter 4, Figures 4-5 and 7-9 and Tables 2-5, are reprinted with permission, from S. Cho, "Map Formation in Proprioceptive Cortex," International Jour...

  19. Hybrid spacecraft attitude control system

    OpenAIRE

    Renuganth Varatharajoo; Ramly Ajir; Tamizi Ahmad

    2016-01-01

    The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS) consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl...

  20. The immune system, adaptation, and machine learning

    Science.gov (United States)

    Farmer, J. Doyne; Packard, Norman H.; Perelson, Alan S.

    1986-10-01

    The immune system is capable of learning, memory, and pattern recognition. By employing genetic operators on a time scale fast enough to observe experimentally, the immune system is able to recognize novel shapes without preprogramming. Here we describe a dynamical model for the immune system that is based on the network hypothesis of Jerne, and is simple enough to simulate on a computer. This model has a strong similarity to an approach to learning and artificial intelligence introduced by Holland, called the classifier system. We demonstrate that simple versions of the classifier system can be cast as a nonlinear dynamical system, and explore the analogy between the immune and classifier systems in detail. Through this comparison we hope to gain insight into the way they perform specific tasks, and to suggest new approaches that might be of value in learning systems.

  1. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    International Nuclear Information System (INIS)

    Dehkordi, Behzad Mirzaeian; Parsapoor, Amir; Moallem, Mehdi; Lucas, Caro

    2011-01-01

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  2. Sensorless speed control of switched reluctance motor using brain emotional learning based intelligent controller

    Energy Technology Data Exchange (ETDEWEB)

    Dehkordi, Behzad Mirzaeian, E-mail: mirzaeian@eng.ui.ac.i [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Parsapoor, Amir, E-mail: amirparsapoor@yahoo.co [Department of Electrical Engineering, Faculty of Engineering, University of Isfahan, Hezar-Jerib St., Postal code 8174673441, Isfahan (Iran, Islamic Republic of); Moallem, Mehdi, E-mail: moallem@cc.iut.ac.i [Department of Electrical Engineering, Isfahan University of Technology, Isfahan (Iran, Islamic Republic of); Lucas, Caro, E-mail: lucas@ut.ac.i [Centre of Excellence for Control and Intelligent Processing, Electrical and Computer Engineering Faculty, College of Engineering, University of Tehran, Tehran (Iran, Islamic Republic of)

    2011-01-15

    In this paper, a brain emotional learning based intelligent controller (BELBIC) is developed to control the switched reluctance motor (SRM) speed. Like other intelligent controllers, BELBIC is model free and is suitable to control nonlinear systems. Motor parameter changes, operating point changes, measurement noise, open circuit fault in one phase and asymmetric phases in SRM are also simulated to show the robustness and superior performance of BELBIC. To compare the BELBIC performance with other intelligent controllers, Fuzzy Logic Controller (FLC) is developed. System responses with BELBIC and FLC are compared. Furthermore, by eliminating the position sensor, a method is introduced to estimate the rotor position. This method is based on Adaptive Neuro Fuzzy Inference System (ANFIS). The estimator inputs are four phase flux linkages. Suggested rotor position estimator is simulated in different conditions. Simulation results confirm the accurate rotor position estimation in different loads and speeds.

  3. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Kim, Dong Yun

    1997-02-01

    In this research, we propose a fuzzy gain scheduler (FGS) with an intelligent learning algorithm for a reactor control. In the proposed algorithm, the gradient descent method is used in order to generate the rule bases of a fuzzy algorithm by learning. These rule bases are obtained by minimizing an objective function, which is called a performance cost function. The objective of the FGS with an intelligent learning algorithm is to generate adequate gains, which minimize the error of system. The proposed algorithm can reduce the time and efforts required for obtaining the fuzzy rules through the intelligent learning function. The evolutionary programming algorithm is modified and adopted as the method in order to find the optimal gains which are used as the initial gains of FGS with learning function. It is applied to reactor control of nuclear power plant (NPP), and the results are compared with those of a conventional PI controller with fixed gains. As a result, it is shown that the proposed algorithm is superior to the conventional PI controller

  4. SYSTEM APPROACH TO THE BLENDED LEARNING

    Directory of Open Access Journals (Sweden)

    Vladimir Kukharenko

    2015-10-01

    Full Text Available Currently, much attention is paid to the development of learning sour cream – a combination of traditional and distance (30-70% of training. Such training is sometimes called hybrid and referred to disruptive technologies. Purpose – to show that the use of systemic campaign in blended learning provides a high quality of education, and the technology can be devastating. The subject of the study – blended learning, object of study – Mixed learning process. The analysis results show that the combined training increases the motivation of students, qualification of teachers, personalized learning process. At the same time there are no reliable methods of assessing the quality of education and training standards. It is important that blended learning strategy to support the institutional goals and had an effective organizational model for support.

  5. Characterization of gradient control systems

    NARCIS (Netherlands)

    Cortés, Jorge; van der Schaft, Arjan; Crouch, Peter E.

    2005-01-01

    Given a general nonlinear affine control system with outputs and a torsion-free affine connection defined on its state space, we investigate the gradient realization problem: we give necessary and sufficient conditions under which the control system can be written as a gradient control system

  6. Characterization of Gradient Control Systems

    NARCIS (Netherlands)

    Cortés, Jorge; Schaft, Arjan van der; Crouch, Peter E.

    2005-01-01

    Given a general nonlinear affine control system with outputs and a torsion-free affine connection defined on its state space, we investigate the gradient realization problem: we give necessary and sufficient conditions under which the control system can be written as a gradient control system

  7. Learning to push and learning to move: The adaptive control of contact forces

    Directory of Open Access Journals (Sweden)

    Maura eCasadio

    2015-11-01

    Full Text Available To be successful at manipulating objects one needs to apply simultaneously well controlled movements and contact forces. We present a computational theory of how the brain may successfully generate a vast spectrum of interactive behaviors by combining two independent processes. One process is competent to control movements in free space and the other is competent to control contact forces against rigid constraints. Free space and rigid constraints are singularities at the boundaries of a continuum of mechanical impedance. Within this continuum, forces and motions occur in compatible pairs connected by the equations of Newtonian dynamics. The force applied to an object determines its motion. Conversely, inverse dynamics determine a unique force trajectory from a movement trajectory. In this perspective, we describe motor learning as a process leading to the discovery of compatible force/motion pairs. The learned compatible pairs constitute a local representation of the environment's mechanics. Experiments on force field adaptation have already provided us with evidence that the brain is able to predict and compensate the forces encountered when one is attempting to generate a motion. Here, we tested the theory in the dual case, i.e. when one attempts at applying a desired contact force against a simulated rigid surface. If the surface becomes unexpectedly compliant, the contact point moves as a function of the applied force and this causes the applied force to deviate from its desired value. We found that, through repeated attempts at generating the desired contact force, subjects discovered the unique compatible hand motion. When, after learning, the rigid contact was unexpectedly restored, subjects displayed after effects of learning, consistent with the concurrent operation of a motion control system and a force control system. Together, theory and experiment support a new and broader view of modularity in the coordinated control of forces and

  8. Networked control of microgrid system of systems

    Science.gov (United States)

    Mahmoud, Magdi S.; Rahman, Mohamed Saif Ur; AL-Sunni, Fouad M.

    2016-08-01

    The microgrid has made its mark in distributed generation and has attracted widespread research. However, microgrid is a complex system which needs to be viewed from an intelligent system of systems perspective. In this paper, a network control system of systems is designed for the islanded microgrid system consisting of three distributed generation units as three subsystems supplying a load. The controller stabilises the microgrid system in the presence of communication infractions such as packet dropouts and delays. Simulation results are included to elucidate the effectiveness of the proposed control strategy.

  9. Covariance upperbound controllers for networked control systems

    International Nuclear Information System (INIS)

    Ko, Sang Ho

    2012-01-01

    This paper deals with designing covariance upperbound controllers for a linear system that can be used in a networked control environment in which control laws are calculated in a remote controller and transmitted through a shared communication link to the plant. In order to compensate for possible packet losses during the transmission, two different techniques are often employed: the zero-input and the hold-input strategy. These use zero input and the latest control input, respectively, when a packet is lost. For each strategy, we synthesize a class of output covariance upperbound controllers for a given covariance upperbound and a packet loss probability. Existence conditions of the covariance upperbound controller are also provided for each strategy. Through numerical examples, performance of the two strategies is compared in terms of feasibility of implementing the controllers

  10. Entry-Control Systems Handbook

    International Nuclear Information System (INIS)

    1978-09-01

    The function of an entry-control system in a total Physical Protection System is to allow the movement of authorized personnel and material through normal access routes, yet detect and delay unauthorized movement of personnel and material from uncontrolled areas. The ten chapters of this handbook cover: introduction, credentials, personnel identity verification systems, special nuclear materials monitors, metal detectors, explosives sensors, package search systems, criteria for selection of entry-control equipment, machine-aided manual entry-control systems, and automated entry-control systems. A system example and its cost are included as an appendix

  11. Closed-Loop and Robust Control of Quantum Systems

    Directory of Open Access Journals (Sweden)

    Chunlin Chen

    2013-01-01

    Full Text Available For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA, and reinforcement learning (RL methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H∞ control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.

  12. Closed-loop and robust control of quantum systems.

    Science.gov (United States)

    Chen, Chunlin; Wang, Lin-Cheng; Wang, Yuanlong

    2013-01-01

    For most practical quantum control systems, it is important and difficult to attain robustness and reliability due to unavoidable uncertainties in the system dynamics or models. Three kinds of typical approaches (e.g., closed-loop learning control, feedback control, and robust control) have been proved to be effective to solve these problems. This work presents a self-contained survey on the closed-loop and robust control of quantum systems, as well as a brief introduction to a selection of basic theories and methods in this research area, to provide interested readers with a general idea for further studies. In the area of closed-loop learning control of quantum systems, we survey and introduce such learning control methods as gradient-based methods, genetic algorithms (GA), and reinforcement learning (RL) methods from a unified point of view of exploring the quantum control landscapes. For the feedback control approach, the paper surveys three control strategies including Lyapunov control, measurement-based control, and coherent-feedback control. Then such topics in the field of quantum robust control as H(∞) control, sliding mode control, quantum risk-sensitive control, and quantum ensemble control are reviewed. The paper concludes with a perspective of future research directions that are likely to attract more attention.

  13. Self-learning fuzzy controllers based on temporal back propagation

    Science.gov (United States)

    Jang, Jyh-Shing R.

    1992-01-01

    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.

  14. VOC emissions control systems

    International Nuclear Information System (INIS)

    Spessard, J.E.

    1993-01-01

    The air pollution control equipment marketplace offers many competing technologies for controlling emissions of volatile organic compounds (VOC) in air. If any technology was economically and technically superior under all conditions, it would be the only one on the market. In fact, each technology used to control VOCs is superior under some set of conditions. The reasons for choosing one control technology over another are situation-specific. Some general guidelines to VOC control technologies and the situations where each may be appropriate are presented in this article. The control technologies and applications are summarized in a table

  15. systemic approach to teaching and learning chemistry

    African Journals Online (AJOL)

    unesco

    2National Core Group in Chemistry, H.E.J Research Institute of Chemistry,. University of ... innovative way of teaching and learning through systemic approach (SATL) has been .... available to do useful work in a thermodynamic process.

  16. Status Checking System of Home Appliances using machine learning

    Directory of Open Access Journals (Sweden)

    Yoon Chi-Yurl

    2017-01-01

    Full Text Available This paper describes status checking system of home appliances based on machine learning, which can be applied to existing household appliances without networking function. Designed status checking system consists of sensor modules, a wireless communication module, cloud server, android application and a machine learning algorithm. The developed system applied to washing machine analyses and judges the four-kinds of appliance’s status such as staying, washing, rinsing and spin-drying. The measurements of sensor and transmission of sensing data are operated on an Arduino board and the data are transmitted to cloud server in real time. The collected data are parsed by an Android application and injected into the machine learning algorithm for learning the status of the appliances. The machine learning algorithm compares the stored learning data with collected real-time data from the appliances. Our results are expected to contribute as a base technology to design an automatic control system based on machine learning technology for household appliances in real-time.

  17. Locus of control and online learning

    Directory of Open Access Journals (Sweden)

    Suretha Esterhuysen

    2004-10-01

    Full Text Available The integration of online learning in university courses is considered to be both inevitable and necessary. Thus there is an increasing need to raise awareness among educators and course designers about the critical issues impacting on online learning. The aim of this study, therefore, was to assess the differences between two groups of first-year Business Sciences learners (online and conventional learners in terms of biographic and demographic characteristics and locus of control. The study population consisted of 586 first-year learners of whom 185 completed the Locus of Control Inventory (LCI. The results show that the two groups of learners do not differ statistically significantly from each other with respect to locus of control. The findings and their implications are also discussed. Opsomming Die integrasie van aanlyn-leer in universiteitskursusse word beskou as sowel onafwendbaar as noodsaaklik. Daar is dus ’n toenemende behoefte om bewustheid onder opvoedkundiges en kursusontwerpers te kweek oor die kritiese aspekte wat ’n impak op aanlyn-leer het (Morgan, 1996. Daarom was die doel van hierdie ondersoek om die verskille tussen twee groepe eerstejaarleerders in Bestuurs- en Ekonomiese Wetenskap (aanlyn en konvensionele leerders te bepaal ten opsigte van biografiese en demografiese eienskappe en lokus van beheer. Die populasie het bestaan uit 586 eerstejaarleerders waarvan 185 die Lokus van Beheer Vraelys voltooi het. Die resultate toon dat die twee groepe leerders nie statisties beduidend van mekaar verskil het met betrekking tot lokus van beheer nie. Die bevindinge en implikasies word ook bespreek.

  18. Online Adaptation and Over-Trial Learning in Macaque Visuomotor Control

    Science.gov (United States)

    Braun, Daniel A.; Aertsen, Ad; Paz, Rony; Vaadia, Eilon; Rotter, Stefan; Mehring, Carsten

    2011-01-01

    When faced with unpredictable environments, the human motor system has been shown to develop optimized adaptation strategies that allow for online adaptation during the control process. Such online adaptation is to be contrasted to slower over-trial learning that corresponds to a trial-by-trial update of the movement plan. Here we investigate the interplay of both processes, i.e., online adaptation and over-trial learning, in a visuomotor experiment performed by macaques. We show that simple non-adaptive control schemes fail to perform in this task, but that a previously suggested adaptive optimal feedback control model can explain the observed behavior. We also show that over-trial learning as seen in learning and aftereffect curves can be explained by learning in a radial basis function network. Our results suggest that both the process of over-trial learning and the process of online adaptation are crucial to understand visuomotor learning. PMID:21720526

  19. Systems and Control Engineering

    Indian Academy of Sciences (India)

    activities directed towards the students and the general public. Designed .... attention has been directed towards the use of control and automation to mitigate the effects of those ... The history of automatic control can be divided into four main.

  20. Fuzzy gain scheduling of velocity PI controller with intelligent learning algorithm for reactor control

    International Nuclear Information System (INIS)

    Kim, Dong Yun; Seong, Poong Hyun

    1996-01-01

    In this study, we proposed a fuzzy gain scheduler with intelligent learning algorithm for a reactor control. In the proposed algorithm, we used the gradient descent method to learn the rule bases of a fuzzy algorithm. These rule bases are learned toward minimizing an objective function, which is called a performance cost function. The objective of fuzzy gain scheduler with intelligent learning algorithm is the generation of adequate gains, which minimize the error of system. The condition of every plant is generally changed as time gose. That is, the initial gains obtained through the analysis of system are no longer suitable for the changed plant. And we need to set new gains, which minimize the error stemmed from changing the condition of a plant. In this paper, we applied this strategy for reactor control of nuclear power plant (NPP), and the results were compared with those of a simple PI controller, which has fixed gains. As a result, it was shown that the proposed algorithm was superior to the simple PI controller

  1. A Novel Extreme Learning Control Framework of Unmanned Surface Vehicles.

    Science.gov (United States)

    Wang, Ning; Sun, Jing-Chao; Er, Meng Joo; Liu, Yan-Cheng

    2016-05-01

    In this paper, an extreme learning control (ELC) framework using the single-hidden-layer feedforward network (SLFN) with random hidden nodes for tracking an unmanned surface vehicle suffering from unknown dynamics and external disturbances is proposed. By combining tracking errors with derivatives, an error surface and transformed states are defined to encapsulate unknown dynamics and disturbances into a lumped vector field of transformed states. The lumped nonlinearity is further identified accurately by an extreme-learning-machine-based SLFN approximator which does not require a priori system knowledge nor tuning input weights. Only output weights of the SLFN need to be updated by adaptive projection-based laws derived from the Lyapunov approach. Moreover, an error compensator is incorporated to suppress approximation residuals, and thereby contributing to the robustness and global asymptotic stability of the closed-loop ELC system. Simulation studies and comprehensive comparisons demonstrate that the ELC framework achieves high accuracy in both tracking and approximation.

  2. Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

    Science.gov (United States)

    Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

    2016-01-01

    Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

  3. Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

    Science.gov (United States)

    2008-09-01

    Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

  4. System for controlling apnea

    Science.gov (United States)

    Holzrichter, John F

    2015-05-05

    An implanted stimulation device or air control device are activated by an external radar-like sensor for controlling apnea. The radar-like sensor senses the closure of the air flow cavity, and associated control circuitry signals (1) a stimulator to cause muscles to open the air passage way that is closing or closed or (2) an air control device to open the air passage way that is closing or closed.

  5. SRS control system upgrade requirements

    International Nuclear Information System (INIS)

    Hill, L.F.

    1998-01-01

    This document defines requirements for an upgrade of the Sodium Removal System (SRS) control system. The upgrade is being performed to solve a number of maintainability and operability issues. The upgraded system will provide the same functions, controls and interlocks as the present system, and in addition provide enhanced functionality in areas discussed in this document

  6. The Development of Learning Management System Using Edmodo

    Science.gov (United States)

    Joko; Septia Wulandari, Gayuh

    2018-04-01

    The development of Learning Management System (LMS) can be used as an online learning media by managing the teacher in delivering the material and giving a task. This study aims to: 1) to know the validity of learning devices using LMS with Edmodo, 2) know the student’s response to LMS implementation using Edmodo, and 3) to know the difference of the learning outcome that is students who learned by using LMS with Edmodo and Direct Learning Model (DLM). This research method is quasi experimental by using control group pretest-posttest design. The population of the study was the student at SMKN 1 Sidoarjo. Research sample X TITL 1 class as control goup, and X TITL 2 class as experimental group. The researcher used scale rating to analyze the data validity and students’ respon, and t-test was used to examine the difference of learning outcomes with significant 0.05. The result of the research shows: 1) the average learning device validity use Edmodo 88.14%, lesson plan validity is 92.45%, pretest-posttest validity is 89.15%, learning material validity is 84.64%, and affective and psychomotor-portfolio observation sheets validity is 86.33 included very good criteria or very suitable to be used for research; 2) the result of students’ response questionnaire after taught by using LMS with Edmodo 86.03% in very good category and students agreed that Edmodo can be used in learning; and 3) the learning outcome of LMS by using Edmodo with DLM are: a) there are significant difference of the student cognitive learning outcome which is taught by using Edmodo with the student who use DLM. The average of student learning outcome that is taught LMS using Edmodo is 81.69 compared to student with DLM outcome 76.39, b) there is difference of affective learning outcome that is taught LMS using Edmodo compared to student using DLM. The average of student learning outcomeof affective that is taught LMS by using Edmodo is 83.50 compared students who use DLM 80.34, and c) there is

  7. Expert systems in process control systems

    International Nuclear Information System (INIS)

    Wittig, T.

    1987-01-01

    To illustrate where the fundamental difference between expert systems in classical diagnosis and in industrial control lie, the work of process control instrumentation is used as an example for the job of expert systems. Starting from the general process of problem-solving, two classes of expert systems can be defined accordingly. (orig.) [de

  8. New designing of E-Learning systems with using network learning

    OpenAIRE

    Malayeri, Amin Daneshmand; Abdollahi, Jalal

    2010-01-01

    One of the most applied learning in virtual spaces is using E-Learning systems. Some E-Learning methodologies has been introduced, but the main subject is the most positive feedback from E-Learning systems. In this paper, we introduce a new methodology of E-Learning systems entitle "Network Learning" with review of another aspects of E-Learning systems. Also, we present benefits and advantages of using these systems in educating and fast learning programs. Network Learning can be programmable...

  9. Feedback Design Patterns for Math Online Learning Systems

    Science.gov (United States)

    Inventado, Paul Salvador; Scupelli, Peter; Heffernan, Cristina; Heffernan, Neil

    2017-01-01

    Increasingly, computer-based learning systems are used by educators to facilitate learning. Evaluations of several math learning systems show that they result in significant student learning improvements. Feedback provision is one of the key features in math learning systems that contribute to its success. We have recently been uncovering feedback…

  10. Modernization of control system using the digital control system

    International Nuclear Information System (INIS)

    Carrasco, J. A.; Fernandez, L.; Jimenez, A.

    2002-01-01

    Nowadays, all plant automation tendencies are based on the use of Digital Control System. In big industrial plants the control systems employed are Distributed Control Systems (DCS). The addition of these systems in nuclear power plants,implies an important adaptation process, because most of them were installed using analog control systems. This paper presents the objectives and the first results obtained, in a modernization project, focused in obtaining an engineering platform for making test and analysis of changes prior to their implementation in a nuclear plant. Modernization, Upgrade, DCS, Automation, Simulation, Training. (Author)

  11. Distributed systems status and control

    Science.gov (United States)

    Kreidler, David; Vickers, David

    1990-01-01

    Concepts are investigated for an automated status and control system for a distributed processing environment. System characteristics, data requirements for health assessment, data acquisition methods, system diagnosis methods and control methods were investigated in an attempt to determine the high-level requirements for a system which can be used to assess the health of a distributed processing system and implement control procedures to maintain an accepted level of health for the system. A potential concept for automated status and control includes the use of expert system techniques to assess the health of the system, detect and diagnose faults, and initiate or recommend actions to correct the faults. Therefore, this research included the investigation of methods by which expert systems were developed for real-time environments and distributed systems. The focus is on the features required by real-time expert systems and the tools available to develop real-time expert systems.

  12. Upgrading the BEPC control system

    International Nuclear Information System (INIS)

    Yang Liping; Wang Lizheng; Liu Shiyao

    1992-01-01

    The BEPC control system has been put into operation and operated normally since the end of 1987. Three years's experience shows this system can satisfy basically the operation requirements, also exhibits some disadvantages araised from the original centralized system architecture based on the VAX-VCC-CAMAC, such as slow response, bottle neck of VCC, less CPU power for control etc.. This paper describes the method and procedure for upgrading the BEPC control system which will be based on DEC net and DEC-WS, and thus intend to upgrade the control system architecture from the centralized to the distributed and improve the integral system performance. (author)

  13. SPring-8 beamline control system.

    Science.gov (United States)

    Ohata, T; Konishi, H; Kimura, H; Furukawa, Y; Tamasaku, K; Nakatani, T; Tanabe, T; Matsumoto, N; Ishii, M; Ishikawa, T

    1998-05-01

    The SPring-8 beamline control system is now taking part in the control of the insertion device (ID), front end, beam transportation channel and all interlock systems of the beamline: it will supply a highly standardized environment of apparatus control for collaborative researchers. In particular, ID operation is very important in a third-generation synchrotron light source facility. It is also very important to consider the security system because the ID is part of the storage ring and is therefore governed by the synchrotron ring control system. The progress of computer networking systems and the technology of security control require the development of a highly flexible control system. An interlock system that is independent of the control system has increased the reliability. For the beamline control system the so-called standard model concept has been adopted. VME-bus (VME) is used as the front-end control system and a UNIX workstation as the operator console. CPU boards of the VME-bus are RISC processor-based board computers operated by a LynxOS-based HP-RT real-time operating system. The workstation and the VME are linked to each other by a network, and form the distributed system. The HP 9000/700 series with HP-UX and the HP 9000/743rt series with HP-RT are used. All the controllable apparatus may be operated from any workstation.

  14. Hybrid spacecraft attitude control system

    Directory of Open Access Journals (Sweden)

    Renuganth Varatharajoo

    2016-02-01

    Full Text Available The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.The hybrid subsystem design could be an attractive approach for futurespacecraft to cope with their demands. The idea of combining theconventional Attitude Control System and the Electrical Power System ispresented in this article. The Combined Energy and Attitude ControlSystem (CEACS consisting of a double counter rotating flywheel assemblyis investigated for small satellites in this article. Another hybrid systemincorporating the conventional Attitude Control System into the ThermalControl System forming the Combined Attitude and Thermal ControlSystem (CATCS consisting of a "fluid wheel" and permanent magnets isalso investigated for small satellites herein. The governing equationsdescribing both these novel hybrid subsystems are presented and theironboard architectures are numerically tested. Both the investigated novelhybrid spacecraft subsystems comply with the reference missionrequirements.

  15. Diagnostic, reliablility and control systems

    CERN Document Server

    Leondes

    2014-01-01

    1. Explicit-Model-Based Fault Detection Method in Industrial Plants 2. Soft Sensor: An Effective Approach to Improve Control 3. Techniques in Soft Computing and Their Utilization in Mechatronic Products 4. Techniques in the Control of Interconnected Plants 5. A Mechatronic Systems Approach to Controlling Robotic Systems with Actuator Dynamics 6. Process and Control Design for Fast Coordinate Measuring Machines 7. Techniques in the Stability of Mechatronic Systems with Sensor or Actuator Failure.

  16. Systems Thinking, Lean Production and Action Learning

    Science.gov (United States)

    Seddon, John; Caulkin, Simon

    2007-01-01

    Systems thinking underpins "lean" management and is best understood through action-learning as the ideas are counter-intuitive. The Toyota Production System is just that--a system; the failure to appreciate that starting-place and the advocacy of "tools" leads many to fail to grasp what is, without doubt, a significant…

  17. Robust Learning Control Design for Quantum Unitary Transformations.

    Science.gov (United States)

    Wu, Chengzhi; Qi, Bo; Chen, Chunlin; Dong, Daoyi

    2017-12-01

    Robust control design for quantum unitary transformations has been recognized as a fundamental and challenging task in the development of quantum information processing due to unavoidable decoherence or operational errors in the experimental implementation of quantum operations. In this paper, we extend the systematic methodology of sampling-based learning control (SLC) approach with a gradient flow algorithm for the design of robust quantum unitary transformations. The SLC approach first uses a "training" process to find an optimal control strategy robust against certain ranges of uncertainties. Then a number of randomly selected samples are tested and the performance is evaluated according to their average fidelity. The approach is applied to three typical examples of robust quantum transformation problems including robust quantum transformations in a three-level quantum system, in a superconducting quantum circuit, and in a spin chain system. Numerical results demonstrate the effectiveness of the SLC approach and show its potential applications in various implementation of quantum unitary transformations.

  18. HETDEX tracker control system design and implementation

    Science.gov (United States)

    Beno, Joseph H.; Hayes, Richard; Leck, Ron; Penney, Charles; Soukup, Ian

    2012-09-01

    To enable the Hobby-Eberly Telescope Dark Energy Experiment, The University of Texas at Austin Center for Electromechanics and McDonald Observatory developed a precision tracker and control system - an 18,000 kg robot to position a 3,100 kg payload within 10 microns of a desired dynamic track. Performance requirements to meet science needs and safety requirements that emerged from detailed Failure Modes and Effects Analysis resulted in a system of 13 precision controlled actuators and 100 additional analog and digital devices (primarily sensors and safety limit switches). Due to this complexity, demanding accuracy requirements, and stringent safety requirements, two independent control systems were developed. First, a versatile and easily configurable centralized control system that links with modeling and simulation tools during the hardware and software design process was deemed essential for normal operation including motion control. A second, parallel, control system, the Hardware Fault Controller (HFC) provides independent monitoring and fault control through a dedicated microcontroller to force a safe, controlled shutdown of the entire system in the event a fault is detected. Motion controls were developed in a Matlab-Simulink simulation environment, and coupled with dSPACE controller hardware. The dSPACE real-time operating system collects sensor information; motor commands are transmitted over a PROFIBUS network to servo amplifiers and drive motor status is received over the same network. To interface the dSPACE controller directly to absolute Heidenhain sensors with EnDat 2.2 protocol, a custom communication board was developed. This paper covers details of operational control software, the HFC, algorithms, tuning, debugging, testing, and lessons learned.

  19. Communication and control tools, systems, and new dimensions

    CERN Document Server

    MacDougall, Robert; Cummings, Kevin

    2015-01-01

    Communication and Control: Tools, Systems, and New Dimensions advocates a systems view of human communication in a time of intelligent, learning machines. This edited collection sheds new light on things as mundane yet still profoundly consequential (and seemingly "low-tech") today as push buttons, pagers and telemarketing systems. Contributors also investigate aspects of "remote control" related to education, organizational design, artificial intelligence, cyberwarfa

  20. Maze learning by a hybrid brain-computer system.

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-13

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  1. Maze learning by a hybrid brain-computer system

    Science.gov (United States)

    Wu, Zhaohui; Zheng, Nenggan; Zhang, Shaowu; Zheng, Xiaoxiang; Gao, Liqiang; Su, Lijuan

    2016-09-01

    The combination of biological and artificial intelligence is particularly driven by two major strands of research: one involves the control of mechanical, usually prosthetic, devices by conscious biological subjects, whereas the other involves the control of animal behaviour by stimulating nervous systems electrically or optically. However, to our knowledge, no study has demonstrated that spatial learning in a computer-based system can affect the learning and decision making behaviour of the biological component, namely a rat, when these two types of intelligence are wired together to form a new intelligent entity. Here, we show how rule operations conducted by computing components contribute to a novel hybrid brain-computer system, i.e., ratbots, exhibit superior learning abilities in a maze learning task, even when their vision and whisker sensation were blocked. We anticipate that our study will encourage other researchers to investigate combinations of various rule operations and other artificial intelligence algorithms with the learning and memory processes of organic brains to develop more powerful cyborg intelligence systems. Our results potentially have profound implications for a variety of applications in intelligent systems and neural rehabilitation.

  2. D0 Cryo System Control System Autodialer

    Energy Technology Data Exchange (ETDEWEB)

    Urbin, J.; /Fermilab

    1990-04-17

    The DO cryogenic system is controlled by a TI565-PLC based control system. This allows the system to be unmanned when in steady state operation. System experts will need to be contacted when system parameters exceed normal operating points and reach alarm setpoints. The labwide FIRUS system provides one alarm monitor and communication link. An autodialer provides a second and more flexible alarm monitor and communication link. The autodialer monitors contact points in the control system and after receiving indication of an alarm accesses a list of experts which it calls until it receives an acknowledgement. There are several manufacturers and distributors of autodialer systems. This EN explains the search process the DO cryo group used to fmd an autodialer system that fit the cryo system's needs and includes information and specs for the unit we chose.

  3. Optimal control in microgrid using multi-agent reinforcement learning.

    Science.gov (United States)

    Li, Fu-Dong; Wu, Min; He, Yong; Chen, Xin

    2012-11-01

    This paper presents an improved reinforcement learning method to minimize electricity costs on the premise of satisfying the power balance and generation limit of units in a microgrid with grid-connected mode. Firstly, the microgrid control requirements are analyzed and the objective function of optimal control for microgrid is proposed. Then, a state variable "Average Electricity Price Trend" which is used to express the most possible transitions of the system is developed so as to reduce the complexity and randomicity of the microgrid, and a multi-agent architecture including agents, state variables, action variables and reward function is formulated. Furthermore, dynamic hierarchical reinforcement learning, based on change rate of key state variable, is established to carry out optimal policy exploration. The analysis shows that the proposed method is beneficial to handle the problem of "curse of dimensionality" and speed up learning in the unknown large-scale world. Finally, the simulation results under JADE (Java Agent Development Framework) demonstrate the validity of the presented method in optimal control for a microgrid with grid-connected mode. Copyright © 2012 ISA. Published by Elsevier Ltd. All rights reserved.

  4. A Mobile Gamification Learning System for Improving the Learning Motivation and Achievements

    Science.gov (United States)

    Su, C-H.; Cheng, C-H.

    2015-01-01

    This paper aims to investigate how a gamified learning approach influences science learning, achievement and motivation, through a context-aware mobile learning environment, and explains the effects on motivation and student learning. A series of gamified learning activities, based on MGLS (Mobile Gamification Learning System), was developed and…

  5. A Neuro-Control Design Based on Fuzzy Reinforcement Learning

    DEFF Research Database (Denmark)

    Katebi, S.D.; Blanke, M.

    This paper describes a neuro-control fuzzy critic design procedure based on reinforcement learning. An important component of the proposed intelligent control configuration is the fuzzy credit assignment unit which acts as a critic, and through fuzzy implications provides adjustment mechanisms....... The fuzzy credit assignment unit comprises a fuzzy system with the appropriate fuzzification, knowledge base and defuzzification components. When an external reinforcement signal (a failure signal) is received, sequences of control actions are evaluated and modified by the action applier unit. The desirable...... ones instruct the neuro-control unit to adjust its weights and are simultaneously stored in the memory unit during the training phase. In response to the internal reinforcement signal (set point threshold deviation), the stored information is retrieved by the action applier unit and utilized for re...

  6. The ATLAS Detector Control System

    International Nuclear Information System (INIS)

    Lantzsch, K; Braun, H; Hirschbuehl, D; Kersten, S; Arfaoui, S; Franz, S; Gutzwiller, O; Schlenker, S; Tsarouchas, C A; Mindur, B; Hartert, J; Zimmermann, S; Talyshev, A; Oliveira Damazio, D; Poblaguev, A; Martin, T; Thompson, P D; Caforio, D; Sbarra, C; Hoffmann, D

    2012-01-01

    The ATLAS experiment is one of the multi-purpose experiments at the Large Hadron Collider (LHC) at CERN, constructed to study elementary particle interactions in collisions of high-energy proton beams. Twelve different sub detectors as well as the common experimental infrastructure are controlled and monitored by the Detector Control System (DCS) using a highly distributed system of 140 server machines running the industrial SCADA product PVSS. Higher level control system layers allow for automatic control procedures, efficient error recognition and handling, manage the communication with external systems such as the LHC controls, and provide a synchronization mechanism with the ATLAS data acquisition system. Different databases are used to store the online parameters of the experiment, replicate a subset used for physics reconstruction, and store the configuration parameters of the systems. This contribution describes the computing architecture and software tools to handle this complex and highly interconnected control system.

  7. The ATLAS Detector Control System

    Science.gov (United States)

    Lantzsch, K.; Arfaoui, S.; Franz, S.; Gutzwiller, O.; Schlenker, S.; Tsarouchas, C. A.; Mindur, B.; Hartert, J.; Zimmermann, S.; Talyshev, A.; Oliveira Damazio, D.; Poblaguev, A.; Braun, H.; Hirschbuehl, D.; Kersten, S.; Martin, T.; Thompson, P. D.; Caforio, D.; Sbarra, C.; Hoffmann, D.; Nemecek, S.; Robichaud-Veronneau, A.; Wynne, B.; Banas, E.; Hajduk, Z.; Olszowska, J.; Stanecka, E.; Bindi, M.; Polini, A.; Deliyergiyev, M.; Mandic, I.; Ertel, E.; Marques Vinagre, F.; Ribeiro, G.; Santos, H. F.; Barillari, T.; Habring, J.; Huber, J.; Arabidze, G.; Boterenbrood, H.; Hart, R.; Iakovidis, G.; Karakostas, K.; Leontsinis, S.; Mountricha, E.; Ntekas, K.; Filimonov, V.; Khomutnikov, V.; Kovalenko, S.; Grassi, V.; Mitrevski, J.; Phillips, P.; Chekulaev, S.; D'Auria, S.; Nagai, K.; Tartarelli, G. F.; Aielli, G.; Marchese, F.; Lafarguette, P.; Brenner, R.

    2012-12-01

    The ATLAS experiment is one of the multi-purpose experiments at the Large Hadron Collider (LHC) at CERN, constructed to study elementary particle interactions in collisions of high-energy proton beams. Twelve different sub detectors as well as the common experimental infrastructure are controlled and monitored by the Detector Control System (DCS) using a highly distributed system of 140 server machines running the industrial SCADA product PVSS. Higher level control system layers allow for automatic control procedures, efficient error recognition and handling, manage the communication with external systems such as the LHC controls, and provide a synchronization mechanism with the ATLAS data acquisition system. Different databases are used to store the online parameters of the experiment, replicate a subset used for physics reconstruction, and store the configuration parameters of the systems. This contribution describes the computing architecture and software tools to handle this complex and highly interconnected control system.

  8. Autorotation flight control system

    Science.gov (United States)

    Bachelder, Edward N. (Inventor); Lee, Dong-Chan (Inventor); Aponso, Bimal L. (Inventor)

    2011-01-01

    The present invention provides computer implemented methodology that permits the safe landing and recovery of rotorcraft following engine failure. With this invention successful autorotations may be performed from well within the unsafe operating area of the height-velocity profile of a helicopter by employing the fast and robust real-time trajectory optimization algorithm that commands control motion through an intuitive pilot display, or directly in the case of autonomous rotorcraft. The algorithm generates optimal trajectories and control commands via the direct-collocation optimization method, solved using a nonlinear programming problem solver. The control inputs computed are collective pitch and aircraft pitch, which are easily tracked and manipulated by the pilot or converted to control actuator commands for automated operation during autorotation in the case of an autonomous rotorcraft. The formulation of the optimal control problem has been carefully tailored so the solutions resemble those of an expert pilot, accounting for the performance limitations of the rotorcraft and safety concerns.

  9. Exploring Learner Autonomy: Language Learning Locus of Control in Multilinguals

    Science.gov (United States)

    Peek, Ron

    2016-01-01

    By using data from an online language learning beliefs survey (n?=?841), defining language learning experience in terms of participants' multilingualism, and using a domain-specific language learning locus of control (LLLOC) instrument, this article examines whether more experienced language learners can also be seen as more autonomous language…

  10. Framework for control system development

    International Nuclear Information System (INIS)

    Cork, C.; Nishimura, Hiroshi

    1992-01-01

    Control systems being developed for the present generation of accelerators will need to adapt to changing machine and operating state conditions. Such systems must also be capable of evolving over the life of the accelerator operation. In this paper we present a framework for the development of adaptive control systems

  11. Framework for control system development

    International Nuclear Information System (INIS)

    Cork, C.; Nishimura, Hiroshi.

    1991-11-01

    Control systems being developed for the present generation of accelerators will need to adapt to changing machine and operating state conditions. Such systems must also be capable of evolving over the life of the accelerator operation. In this paper we present a framework for the development of adaptive control systems

  12. The GSI control system

    International Nuclear Information System (INIS)

    Krause, U.; Schaa, V.; Steiner, R.

    1992-01-01

    The GSI accelerator facility consists of an old linac and two modern machines, a synchrotron and a storage ring. It is operated from one control room. Only three operators at a time have to keep it running with only little assistance from machine specialists in daytime. So the control tools must provide a high degree of abstraction and modeling to relieve the operators from details on the device level. The program structures to achieve this are described in this paper. A coarse overview of the control architecture is given. (author)

  13. Minicomputer controlled test system for process control and monitoring systems

    International Nuclear Information System (INIS)

    Worster, L.D.

    A minicomputer controlled test system for testing process control and monitoring systems is described. This system, in service for over one year, has demonstrated that computerized control of such testing has a real potential for expanding the scope of the testing, improving accuracy of testing, and significantly reducing the time required to do the testing. The test system is built around a 16-bit minicomputer with 12K of memory. The system programming language is BASIC with the addition of assembly level routines for communication with the peripheral devices. The peripheral devices include a 100 channel scanner, analog-to-digital converter, visual display, and strip printer. (auth)

  14. Systems and Control Engineering

    Indian Academy of Sciences (India)

    design of civil engineering structures has been noted. Protecting ci vil ... R despite disturbing forces such as wind gusts, changes in ambient temperature, etc .. Brief History of ... frequency regulation, boiler control for steam generation, electric.

  15. Controlling Uncertain Dynamical Systems

    Indian Academy of Sciences (India)

    Author Affiliations. N Ananthkrishnan1 Rashi Bansal2. Head, CAE Analysis & Design Zeus Numerix Pvt Ltd. M-03, SINE, IIT Bombay Powai Mumbai 400076, India. MTech (Aerospace Engineering) with specialization in Dynamics & Control from IIT Bombay.

  16. Delays and networked control systems

    CERN Document Server

    Hetel, Laurentiu; Daafouz, Jamal; Johansson, Karl

    2016-01-01

    This edited monograph includes state-of-the-art contributions on continuous time dynamical networks with delays. The book is divided into four parts. The first part presents tools and methods for the analysis of time-delay systems with a particular attention on control problems of large scale or infinite-dimensional systems with delays. The second part of the book is dedicated to the use of time-delay models for the analysis and design of Networked Control Systems. The third part of the book focuses on the analysis and design of systems with asynchronous sampling intervals which occur in Networked Control Systems. The last part of the book exposes several contributions dealing with the design of cooperative control and observation laws for networked control systems. The target audience primarily comprises researchers and experts in the field of control theory, but the book may also be beneficial for graduate students. .

  17. Control integral systems; Sistemas integrales de control

    Energy Technology Data Exchange (ETDEWEB)

    Burgos, Estrella [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1999-12-31

    Almost two third of the electric power generation in Mexico are obtained from hydrocarbons, for that reasons Comision Federal de Electricidad (CFE) dedicated special commitment in modernizing the operation of fossil fuel central stations. In attaining this objective the control systems play a fundamental roll, from them depend a good share of the reliability and the efficiency of the electric power generation process, as well as the extension of the equipment useful life. Since 1984 the Instituto de Investigaciones Electricas (IIE) has been working, upon the request of CFE, on the development of digital control systems. To date it has designed and implemented a logic control system for gas burners, which controls 32 burners of the Unit 4 boiler of the Generation Central of Valle de Mexico and two systems for distributed control for two combined cycle central stations, which are: Dos Bocas, Veracruz Combined cycle central, and Gomez Palacio, Durango combined cycle central. With these two developments the IIE enters the World tendency of implementing distributed control systems for the fossil fuel power central update [Espanol] Casi las dos terceras partes de la generacion electrica en Mexico se obtienen a partir de hidrocarburos, es por eso que la Comision Federal de Electricidad (CFE) puso especial empeno en modernizar la operacion de las centrales termoelectricas de combustibles fosiles. En el logro de este objetivo los sistemas de control desempenan un papel fundamental, de ellos depende una buena parte la confiabilidad y la eficiencia en el proceso de generacion de energia electrica, asi como la prolongacion de la vida util de los equipos. Desde 1984 el Instituto de Investigaciones Electricas (IIE) ha trabajado, a solicitud de la CFE, en el desarrollo de sistemas digitales de control. A la fecha se han disenado e implantado un sistema de control logico de quemadores de gas, el cual controla 32 quemadores de la caldera de la unidad 4 de la central de generacion

  18. Control integral systems; Sistemas integrales de control

    Energy Technology Data Exchange (ETDEWEB)

    Burgos, Estrella [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

    1998-12-31

    Almost two third of the electric power generation in Mexico are obtained from hydrocarbons, for that reasons Comision Federal de Electricidad (CFE) dedicated special commitment in modernizing the operation of fossil fuel central stations. In attaining this objective the control systems play a fundamental roll, from them depend a good share of the reliability and the efficiency of the electric power generation process, as well as the extension of the equipment useful life. Since 1984 the Instituto de Investigaciones Electricas (IIE) has been working, upon the request of CFE, on the development of digital control systems. To date it has designed and implemented a logic control system for gas burners, which controls 32 burners of the Unit 4 boiler of the Generation Central of Valle de Mexico and two systems for distributed control for two combined cycle central stations, which are: Dos Bocas, Veracruz Combined cycle central, and Gomez Palacio, Durango combined cycle central. With these two developments the IIE enters the World tendency of implementing distributed control systems for the fossil fuel power central update [Espanol] Casi las dos terceras partes de la generacion electrica en Mexico se obtienen a partir de hidrocarburos, es por eso que la Comision Federal de Electricidad (CFE) puso especial empeno en modernizar la operacion de las centrales termoelectricas de combustibles fosiles. En el logro de este objetivo los sistemas de control desempenan un papel fundamental, de ellos depende una buena parte la confiabilidad y la eficiencia en el proceso de generacion de energia electrica, asi como la prolongacion de la vida util de los equipos. Desde 1984 el Instituto de Investigaciones Electricas (IIE) ha trabajado, a solicitud de la CFE, en el desarrollo de sistemas digitales de control. A la fecha se han disenado e implantado un sistema de control logico de quemadores de gas, el cual controla 32 quemadores de la caldera de la unidad 4 de la central de generacion

  19. Active controllers and the time duration to learn a task

    Science.gov (United States)

    Repperger, D. W.; Goodyear, C.

    1986-01-01

    An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

  20. Asynchronous control for networked systems

    CERN Document Server

    Rubio, Francisco; Bencomo, Sebastián

    2015-01-01

    This book sheds light on networked control systems; it describes different techniques for asynchronous control, moving away from the periodic actions of classical control, replacing them with state-based decisions and reducing the frequency with which communication between subsystems is required. The text focuses specially on event-based control. Split into two parts, Asynchronous Control for Networked Systems begins by addressing the problems of single-loop networked control systems, laying out various solutions which include two alternative model-based control schemes (anticipatory and predictive) and the use of H2/H∞ robust control to deal with network delays and packet losses. Results on self-triggering and send-on-delta sampling are presented to reduce the need for feedback in the loop. In Part II, the authors present solutions for distributed estimation and control. They deal first with reliable networks and then extend their results to scenarios in which delays and packet losses may occur. The novel ...

  1. The Joint Lessons Learned System and Interoperability

    Science.gov (United States)

    1989-06-02

    Learned: 1988-1989 As mentioned in the introduction to this chaoter, the Organizacion of the JcinC Chiefs cf Staff .OJCS) ueren significant transformatioi...Organization and Functions Manual . Washington, D.C.: HQDA, Office of the Deputy Chief 0f Staff for Operations and Plans, June 1984. ’..S. Army. Concept...U.S. Department of Defense. Joint Universal Lessons Learned System (JULLS) User’s Manual . Orlando, Florida: University of Central Florida, Institute

  2. Standardization of detector control systems

    International Nuclear Information System (INIS)

    Fukunaga, Chikara

    2000-01-01

    Current and future detectors for high-energy and/or nuclear physics experiments require highly intelligent detector control systems. In order to reduce resources, the construction of a standardized template for the control systems based on the commercially available superviser control and data acquisition (SCADA) system has been proposed. The possibility of constructing this template is discussed and several key issues for evaluation of SCADA as the basis for such a template are presented. (author)

  3. Lighting Control System (ILCS)

    African Journals Online (AJOL)

    2017-08-08

    Aug 8, 2017 ... function blocks CNC machining protocol. Advanced Materials Research, 2014, 845:779-785. [2] Miki M, Nagano M, Yoshimi M, Yonemoto H, Yoshida K. Intelligent lighting system with an additional energy-saving mechanism. In IEEE International Conference on Systems,. Man, and Cybernetics, 2012, pp.

  4. Quantum Ensemble Classification: A Sampling-Based Learning Control Approach.

    Science.gov (United States)

    Chen, Chunlin; Dong, Daoyi; Qi, Bo; Petersen, Ian R; Rabitz, Herschel

    2017-06-01

    Quantum ensemble classification (QEC) has significant applications in discrimination of atoms (or molecules), separation of isotopes, and quantum information extraction. However, quantum mechanics forbids deterministic discrimination among nonorthogonal states. The classification of inhomogeneous quantum ensembles is very challenging, since there exist variations in the parameters characterizing the members within different classes. In this paper, we recast QEC as a supervised quantum learning problem. A systematic classification methodology is presented by using a sampling-based learning control (SLC) approach for quantum discrimination. The classification task is accomplished via simultaneously steering members belonging to different classes to their corresponding target states (e.g., mutually orthogonal states). First, a new discrimination method is proposed for two similar quantum systems. Then, an SLC method is presented for QEC. Numerical results demonstrate the effectiveness of the proposed approach for the binary classification of two-level quantum ensembles and the multiclass classification of multilevel quantum ensembles.

  5. An Improved Reinforcement Learning System Using Affective Factors

    Directory of Open Access Journals (Sweden)

    Takashi Kuremoto

    2013-07-01

    Full Text Available As a powerful and intelligent machine learning method, reinforcement learning (RL has been widely used in many fields such as game theory, adaptive control, multi-agent system, nonlinear forecasting, and so on. The main contribution of this technique is its exploration and exploitation approaches to find the optimal solution or semi-optimal solution of goal-directed problems. However, when RL is applied to multi-agent systems (MASs, problems such as “curse of dimension”, “perceptual aliasing problem”, and uncertainty of the environment constitute high hurdles to RL. Meanwhile, although RL is inspired by behavioral psychology and reward/punishment from the environment is used, higher mental factors such as affects, emotions, and motivations are rarely adopted in the learning procedure of RL. In this paper, to challenge agents learning in MASs, we propose a computational motivation function, which adopts two principle affective factors “Arousal” and “Pleasure” of Russell’s circumplex model of affects, to improve the learning performance of a conventional RL algorithm named Q-learning (QL. Compared with the conventional QL, computer simulations of pursuit problems with static and dynamic preys were carried out, and the results showed that the proposed method results in agents having a faster and more stable learning performance.

  6. Learning-based identification and iterative learning control of direct-drive robots

    NARCIS (Netherlands)

    Bukkems, B.H.M.; Kostic, D.; Jager, de A.G.; Steinbuch, M.

    2005-01-01

    A combination of model-based and Iterative Learning Control is proposed as a method to achieve high-quality motion control of direct-drive robots in repetitive motion tasks. We include both model-based and learning components in the total control law, as their individual properties influence the

  7. How Instructional Systems Will Manage Learning

    Science.gov (United States)

    Flanagan, John C.

    1970-01-01

    Discusses trends toward the systems approach in education including the development of effective instructional systems in government and industry; the introduction of teaching machines, programed learning, and computer- assisted instruction; and the increase in both the amount and sophistication of educational research and development. (JF)

  8. An Architecture for Open Learning Management Systems

    NARCIS (Netherlands)

    Avgeriou, Paris; Retalis, Simos; Skordalakis, Manolis

    2003-01-01

    There exists an urgent demand on defining architectures for Learning Management Systems, so that high-level frameworks for understanding these systems can be discovered, and quality attributes like portability, interoperability, reusability and modifiability can be achieved. In this paper we propose

  9. AUTOMATIC FREQUENCY CONTROL SYSTEM

    Science.gov (United States)

    Hansen, C.F.; Salisbury, J.D.

    1961-01-10

    A control is described for automatically matching the frequency of a resonant cavity to that of a driving oscillator. The driving oscillator is disconnected from the cavity and a secondary oscillator is actuated in which the cavity is the frequency determining element. A low frequency is mixed with the output of the driving oscillator and the resultant lower and upper sidebands are separately derived. The frequencies of the sidebands are compared with the secondary oscillator frequency. deriving a servo control signal to adjust a tuning element in the cavity and matching the cavity frequency to that of the driving oscillator. The driving oscillator may then be connected to the cavity.

  10. Reactor power control system

    International Nuclear Information System (INIS)

    Tomisawa, Teruaki.

    1981-01-01

    Purpose: To restore reactor-power condition in a minimum time after a termination of turbine bypass by reducing the throttling of the reactor power at the time of load-failure as low as possible. Constitution: The transient change of the internal pressure of condenser is continuously monitored. When a turbine is bypassed, a speed-control-command signal for a coolant recirculating pump is generated according as the internal pressure of the condenser. When the signal relating to the internal pressure of the condenser indicates insufficient power, a reactor-control-rod-drive signal is generated. (J.P.N.)

  11. Ground Control System Description Document

    International Nuclear Information System (INIS)

    Eric Loros

    2001-01-01

    The Ground Control System contributes to the safe construction and operation of the subsurface facility, including accesses and waste emplacement drifts, by maintaining the configuration and stability of the openings during construction, development, emplacement, and caretaker modes for the duration of preclosure repository life. The Ground Control System consists of ground support structures installed within the subsurface excavated openings, any reinforcement made to the rock surrounding the opening, and inverts if designed as an integral part of the system. The Ground Control System maintains stability for the range of geologic conditions expected at the repository and for all expected loading conditions, including in situ rock, construction, operation, thermal, and seismic loads. The system maintains the size and geometry of operating envelopes for all openings, including alcoves, accesses, and emplacement drifts. The system provides for the installation and operation of sensors and equipment for any required inspection and monitoring. In addition, the Ground Control System provides protection against rockfall for all subsurface personnel, equipment, and the engineered barrier system, including the waste package during the preclosure period. The Ground Control System uses materials that are sufficiently maintainable and that retain the necessary engineering properties for the anticipated conditions of the preclosure service life. These materials are also compatible with postclosure waste isolation performance requirements of the repository. The Ground Control System interfaces with the Subsurface Facility System for operating envelopes, drift orientation, and excavated opening dimensions, Emplacement Drift System for material compatibility, Monitored Geologic Repository Operations Monitoring and Control System for ground control instrument readings, Waste Emplacement/Retrieval System to support waste emplacement operations, and the Subsurface Excavation System

  12. Fuzzy control in robot-soccer, evolutionary learning in the first layer of control

    Directory of Open Access Journals (Sweden)

    Peter J Thomas

    2003-02-01

    Full Text Available In this paper an evolutionary algorithm is developed to learn a fuzzy knowledge base for the control of a soccer playing micro-robot from any configuration belonging to a grid of initial configurations to hit the ball along the ball to goal line of sight. The knowledge base uses relative co-ordinate system including left and right wheel velocities of the robot. Final path positions allow forward and reverse facing robot to ball and include its physical dimensions.

  13. Control Allocation for Overactuated Systems

    National Research Council Canada - National Science Library

    Oppenheimer, Michael W; Doman, David B

    2006-01-01

    Much emphasis has been placed on overactuated systems for air vehicles. Overactuating an air vehicle provides a certain amount of redundancy for the flight control system, thus potentially allowing for recovery from off-nominal conditions...

  14. Transitioning from learning healthcare systems to learning health care communities.

    Science.gov (United States)

    Mullins, C Daniel; Wingate, La'Marcus T; Edwards, Hillary A; Tofade, Toyin; Wutoh, Anthony

    2018-02-26

    The learning healthcare system (LHS) model framework has three core, foundational components. These include an infrastructure for health-related data capture, care improvement targets and a supportive policy environment. Despite progress in advancing and implementing LHS approaches, low levels of participation from patients and the public have hampered the transformational potential of the LHS model. An enhanced vision of a community-engaged LHS redesign would focus on the provision of health care from the patient and community perspective to complement the healthcare system as the entity that provides the environment for care. Addressing the LHS framework implementation challenges and utilizing community levers are requisite components of a learning health care community model, version two of the LHS archetype.

  15. A Fuzzy Control System for Inductive Video Games

    OpenAIRE

    Lara-Alvarez, Carlos; Mitre-Hernandez, Hugo; Flores, Juan; Fuentes, Maria

    2017-01-01

    It has been shown that the emotional state of students has an important relationship with learning; for instance, engaged concentration is positively correlated with learning. This paper proposes the Inductive Control (IC) for educational games. Unlike conventional approaches that only modify the game level, the proposed technique also induces emotions in the player for supporting the learning process. This paper explores a fuzzy system that analyzes the players' performance and their emotion...

  16. The APS control system network

    International Nuclear Information System (INIS)

    Sidorowicz, K.V.; McDowell, W.P.

    1995-01-01

    The APS accelerator control system is a distributed system consisting of operator interfaces, a network, and computer-controlled interfaces to hardware. This implementation of a control system has come to be called the open-quotes Standard Model.close quotes The operator interface is a UNDC-based workstation with an X-windows graphical user interface. The workstation may be located at any point on the facility network and maintain full functionality. The function of the network is to provide a generalized communication path between the host computers, operator workstations, input/output crates, and other hardware that comprise the control system. The crate or input/output controller (IOC) provides direct control and input/output interfaces for each accelerator subsystem. The network is an integral part of all modem control systems and network performance will determine many characteristics of a control system. This paper will describe the overall APS network and examine the APS control system network in detail. Metrics are provided on the performance of the system under various conditions

  17. Off-policy reinforcement learning for H∞ control design.

    Science.gov (United States)

    Luo, Biao; Wu, Huai-Ning; Huang, Tingwen

    2015-01-01

    The H∞ control design problem is considered for nonlinear systems with unknown internal system model. It is known that the nonlinear H∞ control problem can be transformed into solving the so-called Hamilton-Jacobi-Isaacs (HJI) equation, which is a nonlinear partial differential equation that is generally impossible to be solved analytically. Even worse, model-based approaches cannot be used for approximately solving HJI equation, when the accurate system model is unavailable or costly to obtain in practice. To overcome these difficulties, an off-policy reinforcement leaning (RL) method is introduced to learn the solution of HJI equation from real system data instead of mathematical system model, and its convergence is proved. In the off-policy RL method, the system data can be generated with arbitrary policies rather than the evaluating policy, which is extremely important and promising for practical systems. For implementation purpose, a neural network (NN)-based actor-critic structure is employed and a least-square NN weight update algorithm is derived based on the method of weighted residuals. Finally, the developed NN-based off-policy RL method is tested on a linear F16 aircraft plant, and further applied to a rotational/translational actuator system.

  18. Computer simulation of nuclear reactor control by means of heuristic learning controller

    International Nuclear Information System (INIS)

    Bubak, M.; Moscinski, J.

    1976-01-01

    A trial of application of two techniques of Artificial Intelligence: heuristic Programming and Learning Machines Theory for nuclear reactor control is presented. Considering complexity of the mathematical models describing satisfactorily the nuclear reactors, value changes of these models parameters in course of operation, knowledge of some parameters value with too small exactness, there appear diffucluties in the classical approach application for these objects control systems design. The classical approach consists in definition of the permissible control actions set on the base of the set performance index and the object mathematical model. The Artificial Intelligence methods enable construction of the control system, which gets during work an information being a priori inaccessible and uses it for its action change for the control to be the optimum one. Applying these methods we have elaborated the reactor power control system. As the performance index there has been taken the integral of the error square. For the control system there are only accessible: the set power trajectory, the reactor power and the control rod position. The set power trajectory has been divided into time intervals called heuristic intervals. At the beginning of every heuristic interval, on the base of the obtained experience, the control system chooses from the control (heuristic) set the optimum control. The heuristic set it is the set of relations between the control rod rate and the state variables, the set and the obtained power, similar to simplifications applied by nuclear reactors operators. The results obtained for the different control rod rates and different reactor (simulated on the digital computer) show the proper work of the system. (author)

  19. Learning feedback and feedforward control in a mirror-reversed visual environment.

    Science.gov (United States)

    Kasuga, Shoko; Telgen, Sebastian; Ushiba, Junichi; Nozaki, Daichi; Diedrichsen, Jörn

    2015-10-01

    When we learn a novel task, the motor system needs to acquire both feedforward and feedback control. Currently, little is known about how the learning of these two mechanisms relate to each other. In the present study, we tested whether feedforward and feedback control need to be learned separately, or whether they are learned as common mechanism when a new control policy is acquired. Participants were trained to reach to two lateral and one central target in an environment with mirror (left-right)-reversed visual feedback. One group was allowed to make online movement corrections, whereas the other group only received visual information after the end of the movement. Learning of feedforward control was assessed by measuring the accuracy of the initial movement direction to lateral targets. Feedback control was measured in the responses to sudden visual perturbations of the cursor when reaching to the central target. Although feedforward control improved in both groups, it was significantly better when online corrections were not allowed. In contrast, feedback control only adaptively changed in participants who received online feedback and remained unchanged in the group without online corrections. Our findings suggest that when a new control policy is acquired, feedforward and feedback control are learned separately, and that there may be a trade-off in learning between feedback and feedforward controllers. Copyright © 2015 the American Physiological Society.

  20. Evaluating Usability of E-Learning Systems in Universities

    OpenAIRE

    Nicholas Kipkurui Kiget; Professor G. Wanyembi; Anselemo Ikoha Peters

    2014-01-01

    The use of e-learning systems has increased significantly in the recent times. E-learning systems are supplementing teaching and learning in universities globally. Kenyan universities have adopted e-learning technologies as means for delivering course content. However despite adoption of these systems, there are considerable challenges facing the usability of the systems. Lecturers and students have different perceptions in regard to the usability of e-learning systems. The aim of this study ...

  1. Controlling changes - lessons learned from waste management facilities

    International Nuclear Information System (INIS)

    Johnson, B.M.; Koplow, A.S.; Stoll, F.E.; Waetje, W.D.

    1995-01-01

    This paper discusses lessons learned about change control at the Waste Reduction Operations Complex (WROC) and Waste Experimental Reduction Facility (WERF) of the Idaho National Engineering Laboratory (INEL). WROC and WERF have developed and implemented change control and an as-built drawing process and have identified structures, systems, and components (SSCS) for configuration management. The operations have also formed an Independent Review Committee to minimize costs and resources associated with changing documents. WROC and WERF perform waste management activities at the INEL. WROC activities include storage, treatment, and disposal of hazardous and mixed waste. WERF provides volume reduction of solid low-level waste through compaction, incineration, and sizing operations. WROC and WERF's efforts aim to improve change control processes that have worked inefficiently in the past

  2. Learning feedforward controller for a mobile robot vehicle

    NARCIS (Netherlands)

    Starrenburg, J.G.; Starrenburg, J.G.; van Luenen, W.T.C.; van Luenen, W.T.C.; Oelen, W.; Oelen, W.; van Amerongen, J.

    1996-01-01

    This paper describes the design and realisation of an on-line learning posetracking controller for a three-wheeled mobile robot vehicle. The controller consists of two components. The first is a constant-gain feedback component, designed on the basis of a second-order model. The second is a learning

  3. Continuous residual reinforcement learning for traffic signal control optimization

    NARCIS (Netherlands)

    Aslani, Mohammad; Seipel, Stefan; Wiering, Marco

    2018-01-01

    Traffic signal control can be naturally regarded as a reinforcement learning problem. Unfortunately, it is one of the most difficult classes of reinforcement learning problems owing to its large state space. A straightforward approach to address this challenge is to control traffic signals based on

  4. Digital control systems. Verteilte Prozessleitsysteme

    Energy Technology Data Exchange (ETDEWEB)

    1984-01-01

    With a distinct description of the systems properties thin regulation shall provide a latter transparency for the use of digital control systems. The application of the new technique shall be facilitated, incitations for the further development shall be given and the compatibility of the systems shall be advanced. Moreover, the regulation can be used as criteria catalogue for the evaluation of digital systems.

  5. Assisted Learning Systems in e-Education

    Directory of Open Access Journals (Sweden)

    Gabriel ZAMFIR

    2014-01-01

    Full Text Available Human society, analyzed as a learning environment, presumes different languages in order to know, to understand or to develop it. This statement results as a default application of the cog-nitive domain in the educational scientific research, and it highlights a key feature: each essen-tial discovery was available for the entire language compatible society. E-Society is constructed as an application of E-Science in social services, and it is going to reveal a learning system for each application of the information technology developed for a compatible society. This article is proposed as a conceptual one focused on scientific research and the interrelationship be-tween the building blocks of research, defined as an engine for any designed learning system applied in the cognitive domain. In this approach, educational research become a learning sys-tem in e-Education. The purpose of this analysis is to configure the teacher assisted learning system and to expose its main principles which could be integrated in standard assisted instruc-tion applications, available in e-Classroom, supporting the design of specific didactic activities.

  6. Self-Learning Power Control in Wireless Sensor Networks.

    Science.gov (United States)

    Chincoli, Michele; Liotta, Antonio

    2018-01-27

    Current trends in interconnecting myriad smart objects to monetize on Internet of Things applications have led to high-density communications in wireless sensor networks. This aggravates the already over-congested unlicensed radio bands, calling for new mechanisms to improve spectrum management and energy efficiency, such as transmission power control. Existing protocols are based on simplistic heuristics that often approach interference problems (i.e., packet loss, delay and energy waste) by increasing power, leading to detrimental results. The scope of this work is to investigate how machine learning may be used to bring wireless nodes to the lowest possible transmission power level and, in turn, to respect the quality requirements of the overall network. Lowering transmission power has benefits in terms of both energy consumption and interference. We propose a protocol of transmission power control through a reinforcement learning process that we have set in a multi-agent system. The agents are independent learners using the same exploration strategy and reward structure, leading to an overall cooperative network. The simulation results show that the system converges to an equilibrium where each node transmits at the minimum power while respecting high packet reception ratio constraints. Consequently, the system benefits from low energy consumption and packet delay.

  7. Machine learning paradigms applications in recommender systems

    CERN Document Server

    Lampropoulos, Aristomenis S

    2015-01-01

    This timely book presents Applications in Recommender Systems which are making recommendations using machine learning algorithms trained via examples of content the user likes or dislikes. Recommender systems built on the assumption of availability of both positive and negative examples do not perform well when negative examples are rare. It is exactly this problem that the authors address in the monograph at hand. Specifically, the books approach is based on one-class classification methodologies that have been appearing in recent machine learning research. The blending of recommender systems and one-class classification provides a new very fertile field for research, innovation and development with potential applications in “big data” as well as “sparse data” problems. The book will be useful to researchers, practitioners and graduate students dealing with problems of extensive and complex data. It is intended for both the expert/researcher in the fields of Pattern Recognition, Machine Learning and ...

  8. Adaptive learning fuzzy control of a mobile robot

    International Nuclear Information System (INIS)

    Tsukada, Akira; Suzuki, Katsuo; Fujii, Yoshio; Shinohara, Yoshikuni

    1989-11-01

    In this report a problem is studied to construct a fuzzy controller for a mobile robot to move autonomously along a given reference direction curve, for which control rules are generated and acquired through an adaptive learning process. An adaptive learning fuzzy controller has been developed for a mobile robot. Good properties of the controller are shown through the travelling experiments of the mobile robot. (author)

  9. Multidimensional Learner Model In Intelligent Learning System

    Science.gov (United States)

    Deliyska, B.; Rozeva, A.

    2009-11-01

    The learner model in an intelligent learning system (ILS) has to ensure the personalization (individualization) and the adaptability of e-learning in an online learner-centered environment. ILS is a distributed e-learning system whose modules can be independent and located in different nodes (servers) on the Web. This kind of e-learning is achieved through the resources of the Semantic Web and is designed and developed around a course, group of courses or specialty. An essential part of ILS is learner model database which contains structured data about learner profile and temporal status in the learning process of one or more courses. In the paper a learner model position in ILS is considered and a relational database is designed from learner's domain ontology. Multidimensional modeling agent for the source database is designed and resultant learner data cube is presented. Agent's modules are proposed with corresponding algorithms and procedures. Multidimensional (OLAP) analysis guidelines on the resultant learner module for designing dynamic learning strategy have been highlighted.

  10. Construction of multi-agent mobile robots control system in the problem of persecution with using a modified reinforcement learning method based on neural networks

    Science.gov (United States)

    Patkin, M. L.; Rogachev, G. N.

    2018-02-01

    A method for constructing a multi-agent control system for mobile robots based on training with reinforcement using deep neural networks is considered. Synthesis of the management system is proposed to be carried out with reinforcement training and the modified Actor-Critic method, in which the Actor module is divided into Action Actor and Communication Actor in order to simultaneously manage mobile robots and communicate with partners. Communication is carried out by sending partners at each step a vector of real numbers that are added to the observation vector and affect the behaviour. Functions of Actors and Critic are approximated by deep neural networks. The Critics value function is trained by using the TD-error method and the Actor’s function by using DDPG. The Communication Actor’s neural network is trained through gradients received from partner agents. An environment in which a cooperative multi-agent interaction is present was developed, computer simulation of the application of this method in the control problem of two robots pursuing two goals was carried out.

  11. Controlling systems of cogeneration blocks

    International Nuclear Information System (INIS)

    Suriansky, J.; Suriansky, J. Ml.; Puskajler, J.

    2007-01-01

    In this article the main parts of cogeneration unit control system are described. Article is aimed on electric power measurement with electricity protection as with temperature system regulation. In conclusion of the article, the control algorithm with perspective of cogeneration solve is indicated. (authors)

  12. A Control Systems Concept Inventory Test Design and Assessment

    Science.gov (United States)

    Bristow, M.; Erkorkmaz, K.; Huissoon, J. P.; Jeon, Soo; Owen, W. S.; Waslander, S. L.; Stubley, G. D.

    2012-01-01

    Any meaningful initiative to improve the teaching and learning in introductory control systems courses needs a clear test of student conceptual understanding to determine the effectiveness of proposed methods and activities. The authors propose a control systems concept inventory. Development of the inventory was collaborative and iterative. The…

  13. Automatic Bridge Control System

    OpenAIRE

    M. Niraimathi; S.Sivakumar; R.Vigneshwaran; R.Vinothkumar; P.Babu

    2012-01-01

    Bridge vibration control is an important issue whose purpose is to extend the structural service life of bridges. Normally, the bridge is modeled as an elastic beam or plate subject to a moving vehicle. However, the moving truck on a bridge is a complicated problem that must still be researched. In this paper, wepropose a new method, to overcome the huge load in the bridge a load cell is used at the entry which will monitor the load continuously at both ends. To escape from the heavy water fl...

  14. Virtualization in control system environment

    International Nuclear Information System (INIS)

    Shen, L.R.; Liu, D.K.; Wan, T.M.

    2012-01-01

    In large scale distributed control system, there are lots of common service composed an environment for the entire control system, such as the server system for the common software base library, application server, archive server and so on. This paper gives a description of a virtualization realization for control system environment including the virtualization for server, storage, network system and application for the control system. With a virtualization instance of the EPICS based control system environment that was built by the VMware vSphere v4, we tested the whole functionality of this virtualization environment in the SSRF control system, including the common server of the NFS, NIS, NTP, Boot and EPICS base and extension library tools, we also have applied virtualization to application servers such as the Archive, Alarm, EPICS gateway and all of the network based IOC. Specially, we test the high availability and VMotion for EPICS asynchronous IOC successful under the different VLAN configuration of the current SSRF control system network. (authors)

  15. Optimal Control of Mechanical Systems

    Directory of Open Access Journals (Sweden)

    Vadim Azhmyakov

    2007-01-01

    Full Text Available In the present work, we consider a class of nonlinear optimal control problems, which can be called “optimal control problems in mechanics.” We deal with control systems whose dynamics can be described by a system of Euler-Lagrange or Hamilton equations. Using the variational structure of the solution of the corresponding boundary-value problems, we reduce the initial optimal control problem to an auxiliary problem of multiobjective programming. This technique makes it possible to apply some consistent numerical approximations of a multiobjective optimization problem to the initial optimal control problem. For solving the auxiliary problem, we propose an implementable numerical algorithm.

  16. Decentralized control of complex systems

    CERN Document Server

    Siljak, Dragoslav D

    2011-01-01

    Complex systems require fast control action in response to local input, and perturbations dictate the use of decentralized information and control structures. This much-cited reference book explores the approaches to synthesizing control laws under decentralized information structure constraints.Starting with a graph-theoretic framework for structural modeling of complex systems, the text presents results related to robust stabilization via decentralized state feedback. Subsequent chapters explore optimization, output feedback, the manipulative power of graphs, overlapping decompositions and t

  17. Argonne's atlas control system upgrade

    International Nuclear Information System (INIS)

    Munson, F.; Quock, D.; Chapin, B.; Figueroa, J.

    1999-01-01

    The ATLAS facility (Argonne Tandem-Linac Accelerator System) is located at the Argonne National Laboratory. The facility is a tool used in nuclear and atomic physics research, which focuses primarily on heavy-ion physics. The accelerator as well as its control system are evolutionary in nature, and consequently, continue to advance. In 1998 the most recent project to upgrade the ATLAS control system was completed. This paper briefly reviews the upgrade, and summarizes the configuration and features of the resulting control system

  18. PLC VVVF Elevator Control System

    OpenAIRE

    Tang, Yujian; Gui, Tianyu

    2016-01-01

    The aim of the thesis is to introduce the PLC VVVF elevator and its control system. The thesis can be divided into three parts. The first part is about the overview of the lift: the kinds of the lift and the structure of the lift, it shows the knowledge about the components and the operating systems of the lift. The second part is about the PLC control system, it’s about the operations of the lift from the introduction about the hardware and software of the PLC control system. And the thi...

  19. Research on Open-Closed-Loop Iterative Learning Control with Variable Forgetting Factor of Mobile Robots

    Directory of Open Access Journals (Sweden)

    Hongbin Wang

    2016-01-01

    Full Text Available We propose an iterative learning control algorithm (ILC that is developed using a variable forgetting factor to control a mobile robot. The proposed algorithm can be categorized as an open-closed-loop iterative learning control, which produces control instructions by using both previous and current data. However, introducing a variable forgetting factor can weaken the former control output and its variance in the control law while strengthening the robustness of the iterative learning control. If it is applied to the mobile robot, this will reduce position errors in robot trajectory tracking control effectively. In this work, we show that the proposed algorithm guarantees tracking error bound convergence to a small neighborhood of the origin under the condition of state disturbances, output measurement noises, and fluctuation of system dynamics. By using simulation, we demonstrate that the controller is effective in realizing the prefect tracking.

  20. Multiple systems for motor skill learning.

    Science.gov (United States)

    Clark, Dav; Ivry, Richard B

    2010-07-01

    Motor learning is a ubiquitous feature of human competence. This review focuses on two particular classes of model tasks for studying skill acquisition. The serial reaction time (SRT) task is used to probe how people learn sequences of actions, while adaptation in the context of visuomotor or force field perturbations serves to illustrate how preexisting movements are recalibrated in novel environments. These tasks highlight important issues regarding the representational changes that occur during the course of motor learning. One important theme is that distinct mechanisms vary in their information processing costs during learning and performance. Fast learning processes may require few trials to produce large changes in performance but impose demands on cognitive resources. Slower processes are limited in their ability to integrate complex information but minimally demanding in terms of attention or processing resources. The representations derived from fast systems may be accessible to conscious processing and provide a relatively greater measure of flexibility, while the representations derived from slower systems are more inflexible and automatic in their behavior. In exploring these issues, we focus on how multiple neural systems may interact and compete during the acquisition and consolidation of new behaviors. Copyright © 2010 John Wiley & Sons, Ltd. This article is categorized under: Psychology > Motor Skill and Performance. Copyright © 2010 John Wiley & Sons, Ltd.

  1. LANSCE personnel access control system (PACS)

    International Nuclear Information System (INIS)

    Sturrock, J.C.; Gallegos, F.R.; Hall, M.J.

    1997-01-01

    The Radiation Security System (RSS) at the Los Alamos Neutron Science Center (LANSCE) provides personnel protection from prompt radiation due to accelerated beam. The Personnel Access Control System (PACS) is a component of the RSS that is designed to prevent personnel access to areas where prompt radiation is a hazard. PACS was designed to replace several older personnel safety systems (PSS) with a single modem unified design. Lessons learned from the operation over the last 20 years were incorporated into a redundant sensor, single-point failure safe, fault tolerant, and tamper-resistant system that prevents access to the beam areas by controlling the access keys and beam stoppers. PACS uses a layered philosophy to the physical and electronic design. The most critical assemblies are battery backed up, relay logic circuits; less critical devices use Programmable Logic Controllers (PLCs) for timing functions and communications. Outside reviewers have reviewed the operational safety of the design. The design philosophy, lessons learned, hardware design, software design, operation, and limitations of the device are described

  2. Research on cultivating medical students' self-learning ability using teaching system integrated with learning analysis technology.

    Science.gov (United States)

    Luo, Hong; Wu, Cheng; He, Qian; Wang, Shi-Yong; Ma, Xiu-Qiang; Wang, Ri; Li, Bing; He, Jia

    2015-01-01

    Along with the advancement of information technology and the era of big data education, using learning process data to provide strategic decision-making in cultivating and improving medical students' self-learning ability has become a trend in educational research. Educator Abuwen Toffler said once, the illiterates in the future may not be the people not able to read and write, but not capable to know how to learn. Serving as educational institutions cultivating medical students' learning ability, colleges and universities should not only instruct specific professional knowledge and skills, but also develop medical students' self-learning ability. In this research, we built a teaching system which can help to restore medical students' self-learning processes and analyze their learning outcomes and behaviors. To evaluate the effectiveness of the system in supporting medical students' self-learning, an experiment was conducted in 116 medical students from two grades. The results indicated that problems in self-learning process through this system was consistent with problems raised from traditional classroom teaching. Moreover, the experimental group (using this system) acted better than control group (using traditional classroom teaching) to some extent. Thus, this system can not only help medical students to develop their self-learning ability, but also enhances the ability of teachers to target medical students' questions quickly, improving the efficiency of answering questions in class.

  3. Vacuum control system of VEC

    International Nuclear Information System (INIS)

    Roy, Anindya; Bhole, R.B.; Bandopadhyay, D.L.; Mukhopadhyay, B.; Pal, Sarbajit; Sarkar, D.

    2009-01-01

    As a part of modernization of VEC (Variable Energy Cyclotron), the Vacuum Control System is being upgraded to PLC based automated system from initial Relay based Manual system. EPICS (Experimental Physics and Industrial Control System), a standard open source software tool for designing distributed control system, is chosen for developing the supervisory control software layer, leading towards a unified distributed control architecture of VEC Control System. A Modbus - TCP based IOC (I/O Controller) has been developed to communicate control data to PLC using Ethernet-TCP LAN. Keeping in mind, the operators' familiarity with MS-Windows, a MS-Windows based operator interface is developed using VB6. It is also used to test and evaluate EPICS compatibility to MS Windows. Several MS Windows ActiveX components e.g. text display, image display, alarm window, set-point input etc. have been developed incorporating Channel Access library of EPICS. Use of such components ease the programming complexity and reduce developmental time of the operator interface. The system is in the final phase of commissioning. (author)

  4. Episodic reinforcement learning control approach for biped walking

    Directory of Open Access Journals (Sweden)

    Katić Duško

    2012-01-01

    Full Text Available This paper presents a hybrid dynamic control approach to the realization of humanoid biped robotic walk, focusing on the policy gradient episodic reinforcement learning with fuzzy evaluative feedback. The proposed structure of controller involves two feedback loops: a conventional computed torque controller and an episodic reinforcement learning controller. The reinforcement learning part includes fuzzy information about Zero-Moment- Point errors. Simulation tests using a medium-size 36-DOF humanoid robot MEXONE were performed to demonstrate the effectiveness of our method.

  5. The effects of sleep deprivation on dissociable prototype learning systems.

    Science.gov (United States)

    Maddox, W Todd; Glass, Brian D; Zeithamova, Dagmar; Savarie, Zachary R; Bowen, Christopher; Matthews, Michael D; Schnyer, David M

    2011-03-01

    The cognitive neural underpinnings of prototype learning are becoming clear. Evidence points to 2 different neural systems, depending on the learning parameters. A/not-A (AN) prototype learning is mediated by posterior brain regions that are involved in early perceptual learning, whereas A/B (AB) is mediated by frontal and medial temporal lobe regions. To investigate the effects of sleep deprivation on AN and AB prototype learning and to use established prototype models to provide insights into the cognitive-processing locus of sleep-deprivation deficits. Participants performed an AN and an AB prototype learning task twice, separated by a 24-hour period, with or without sleep between testing sessions. Eighteen West Point cadets participated in the sleep-deprivation group, and 17 West Point cadets participated in a control group. Sleep deprivation led to an AN, but not an AB, performance deficit. Prototype model analyses indicated that the AN deficit was due to changes in attentional focus and a decrease in confidence that is reflected in an increased bias to respond non-A. The findings suggest that AN, but not AB, prototype learning is affected by sleep deprivation. Prototype model analyses support the notion that the effect of sleep deprivation on AN is consistent with lapses in attentional focus that are more detrimental to AN than to AB. This finding adds to a growing body of work that suggests that different performance changes associated with sleep deprivation can be attributed to a common mechanism of changes in simple attention and vigilance.

  6. 3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

    Science.gov (United States)

    Su,Chung-Ho; Cheng, Ching-Hsue

    2013-01-01

    The advancement of game-based learning has encouraged many related studies, such that students could better learn curriculum by 3-dimension virtual reality. To enhance software engineering learning, this paper develops a 3D game-based learning system to assist teaching and assess the students' motivation, satisfaction and learning achievement. A…

  7. Towards synergy between learning management systems and educational server applications

    OpenAIRE

    Hartog, R.J.M.; Schaaf, van der, H.; Kassahun, A.

    2008-01-01

    Most well-known Learning Management Systems (LMS) are based on a paradigm of learning objects to be uploaded into the system. Most formulations of this paradigm implicitly assume that the learning objects are self contained learning objects such as FLASH objects or JAVA applets or presentational learning objects such as slide presentations. These are typically client side objects. However, a demand for learning support that activates the student can often be satisfied better with a server app...

  8. An Instructional and Collaborative Learning System with Content Recommendation

    Science.gov (United States)

    Zheng, Xiang-wei; Ma, Hong-wei; Li, Yan

    2013-01-01

    With the rapid development of Internet, e-learning has become a new teaching and learning mode. However, lots of e-learning systems deployed on Internet are just electronic learning materials with very limited interactivity and diagnostic capability. This paper presents an integrated e-learning environment named iCLSR. Firstly, iCLSR provides an…

  9. Investigation of Drive-Reinforcement Learning and Application of Learning to Flight Control

    Science.gov (United States)

    1993-08-01

    WL-TR-93-1153 INVESTIGATION OF DRIVE-REINFORCEMEN% LEARNING AND APPLICATION OF LEARNING TO FLIGHT CONTROL AD-A277 442 WALTER L. BAKER (ED), STEPHEN ...OF LEARNING TO FUIGHT CONTROL PE 62204 ___ ___ ___ ___ __ ___ ___ ___ ___ ___ ___ __ PR 2003 6. AUTHOR(S) TA 05 WALTER L. BAKER (ED), STEPHEN C. ATKINS...34 Computers and Thought, E. A. Freigenbaum and J. Feldman (eds.), Mc- Graw Hill, New York, (1959). [19] Holland, J. H., "Escaping Brittleness: The Possibility

  10. JT-60 plasma control system

    International Nuclear Information System (INIS)

    Kurihara, K.

    1988-01-01

    JT-60 plasma control can be performed by the supervisory controller, the measurement system and actuators such as the poloidal field coil power supplies, gas injectors, neutral beam injection (NBI) heating system and radio frequency (RF) heating system. One of the most important characteristics of this system is a perfect digital control one composed of mini-computers, fast array processors and CAMAC modules, and it has large flexibility and few troubles to adjust the system. This system started to be operated in April 1985, after the six-year-long design, construction and testing, and have been operated and improved many times for two years. In this paper, the final system specification and its performance are presented aiming at the technological aspect of hardware and software. In addition, and experienced troubles are also presented. (author)

  11. Learning through the taste system

    Directory of Open Access Journals (Sweden)

    Thomas R. Scott

    2011-11-01

    Full Text Available Taste is the final arbiter of which chemicals from the environment will be admitted to the body. The action of swallowing a substance leads to a physiological consequence of which the taste system should be informed. Accordingly, taste neurons in the central nervous system are closely allied with those that receive input from the viscera so as to monitor the impact of a recently ingested substance. There is behavioral, anatomical, electrophysiological, gene expression, and neurochemical evidence that the consequences of ingestion influence subsequent food selection through development of either a conditioned taste aversion (if illness ensues or a conditioned taste preference (if satiety. This ongoing communication between taste and the viscera permits the animal to tailor its taste system to its individual needs over a lifetime.

  12. Information Systems in University Learning

    Directory of Open Access Journals (Sweden)

    Gheorghe SABAU

    2010-01-01

    Full Text Available The authors of this article are going to bring into light the significance, the place and the role of information systems in the university education process. At the same time they define the objectives and the target group of the subject named Economic Information Systems and state the competence gained by students by studying this subject. Special attention is given to the curriculum to be taught to students and to a suggestive enumeration of a series of economic applications that can be themes for laboratory practice and for students’ dissertation (graduation thesis.

  13. Computer control system of TRISTAN

    International Nuclear Information System (INIS)

    Kurokawa, Shin-ichi; Shinomoto, Manabu; Kurihara, Michio; Sakai, Hiroshi.

    1984-01-01

    For the operation of a large accelerator, it is necessary to connect an enormous quantity of electro-magnets, power sources, vacuum equipment, high frequency accelerator and so on and to control them harmoniously. For the purpose, a number of computers are adopted, and connected with a network, in this way, a large computer system for laboratory automation which integrates and controls the whole system is constructed. As a distributed system of large scale, the functions such as electro-magnet control, file processing and operation control are assigned to respective computers, and the total control is made feasible by network connection, at the same time, as the interface with controlled equipment, the CAMAC (computer-aided measurement and control) is adopted to ensure the flexibility and the possibility of expansion of the system. Moreover, the language ''NODAL'' having network support function was developed so as to easily make software without considering the composition of more complex distributed system. The accelerator in the TRISTAN project is composed of an electron linear accelerator, an accumulation ring of 6 GeV and a main ring of 30 GeV. Two ring type accelerators must be synchronously operated as one body, and are controlled with one computer system. The hardware and software are outlined. (Kako, I.)

  14. Control of Solar Energy Systems

    CERN Document Server

    Camacho, Eduardo F; Rubio, Francisco R; Martínez, Diego

    2012-01-01

    Control of Solar Energy Systems details the main solar energy systems, problems involved with their control, and how control systems can help in increasing their efficiency.  After a brief introduction to the fundamental concepts associated with the use of solar energy in both photovoltaic and thermal plants, specific issues related to control of solar systems are embarked upon. Thermal energy systems are then explored in depth, as well as  other solar energy applications such as solar furnaces and solar refrigeration systems. Problems of variable generation profile and of the contribution of many solar plants to the same grid system are considered with the necessary integrated and supervisory control solutions being discussed. The text includes material on: ·         A comparison of basic and advanced control methods for parabolic troughs from PID to nonlinear model-based control; ·         solar towers and solar tracking; ·         heliostat calibration, characterization and off...

  15. Learning Control of Fixed-Wing Unmanned Aerial Vehicles Using Fuzzy Neural Networks

    Directory of Open Access Journals (Sweden)

    Erdal Kayacan

    2017-01-01

    Full Text Available A learning control strategy is preferred for the control and guidance of a fixed-wing unmanned aerial vehicle to deal with lack of modeling and flight uncertainties. For learning the plant model as well as changing working conditions online, a fuzzy neural network (FNN is used in parallel with a conventional P (proportional controller. Among the learning algorithms in the literature, a derivative-free one, sliding mode control (SMC theory-based learning algorithm, is preferred as it has been proved to be computationally efficient in real-time applications. Its proven robustness and finite time converging nature make the learning algorithm appropriate for controlling an unmanned aerial vehicle as the computational power is always limited in unmanned aerial vehicles (UAVs. The parameter update rules and stability conditions of the learning are derived, and the proof of the stability of the learning algorithm is shown by using a candidate Lyapunov function. Intensive simulations are performed to illustrate the applicability of the proposed controller which includes the tracking of a three-dimensional trajectory by the UAV subject to time-varying wind conditions. The simulation results show the efficiency of the proposed control algorithm, especially in real-time control systems because of its computational efficiency.

  16. Upgrading the ATLAS control system

    International Nuclear Information System (INIS)

    Munson, F.H.; Ferraretto, M.

    1993-01-01

    Heavy-ion accelerators are tools used in the research of nuclear and atomic physics. The ATLAS facility at the Argonne National Laboratory is one such tool. The ATLAS control system serves as the primary operator interface to the accelerator. A project to upgrade the control system is presently in progress. Since this is an upgrade project and not a new installation, it was imperative that the development work proceed without interference to normal operations. An additional criteria for the development work was that the writing of additional ''in-house'' software should be kept to a minimum. This paper briefly describes the control system being upgraded, and explains some of the reasons for the decision to upgrade the control system. Design considerations and goals for the new system are described, and the present status of the upgrade is discussed

  17. Control Evaluation Information System Savings

    Directory of Open Access Journals (Sweden)

    Eddy Sutedjo

    2011-05-01

    Full Text Available The purpose of this research is to evaluate the control of information system savings in the banking and to identify the weaknesses and problem happened in those saving systems. Research method used are book studies by collecting data and information needed and field studies by interview, observation, questioner, and checklist using COBIT method as a standard to assess the information system control of the company. The expected result about the evaluation result that show in the problem happened and recommendation given as the evaluation report and to give a view about the control done by the company. Conclusion took from this research that this banking company has met standards although some weaknesses still exists in the system.Index Terms - Control Information System, Savings

  18. Implementing the learning health care system.

    NARCIS (Netherlands)

    Verheij, R.; Barten, D.J.; Hek, K.; Nielen, M.; Prins, M.; Zwaanswijk, M.; Bakker, D. de

    2014-01-01

    Background: As computerisation of primary care facilities is rapidly increasing, a wealth of data is created in routinely recorded electronic health records (EHRs). This data can be used to create a true learning health care system, in which routinely available data are processed and analysed in

  19. Distance Learning Delivery Systems: Instructional Options.

    Science.gov (United States)

    Steele, Ray L.

    1993-01-01

    Discusses the availability of satellite and cable programing to provide distance education opportunities in school districts. Various delivery systems are described, including telephones with speakers, personal computers, and satellite dishes; and a sidebar provides a directory of distance learning opportunities, including telecommunications…

  20. Manual control of unstable systems

    Science.gov (United States)

    Allen, R. W.; Hogue, J. R.; Parseghian, Z.

    1986-01-01

    Under certain operational regimes and failure modes, air and ground vehicles can present the human operator with a dynamically unstable or divergent control task. Research conducted over the last two decades has explored the ability of the human operator to control unstable systems under a variety of circumstances. Past research is reviewed and human operator control capabilities are summarized. A current example of automobile directional control under rear brake lockup conditions is also reviewed. A control system model analysis of the driver's steering control task is summarized, based on a generic driver/vehicle model presented at last year's Annual Manual. Results from closed course braking tests are presented that confirm the difficulty the average driver has in controlling the unstable directional dynamics arising from rear wheel lockup.

  1. Cigarette weight control systems

    International Nuclear Information System (INIS)

    Powell, G.F.W.; Bolt, R.C.; Simmons, A.

    1980-01-01

    A system is described for monitoring the weight of a continuous wrapped rod of tobacco formed by a cigarette-making machine. A scanner unit can be used which passes beta-rays from a primary radiation source through the rod. The absorption is measured by comparison of the intensity at a detector on the opposite side of the rod with that at a detector facing another smaller source, the balance unit. This is pre-set so that when the rod weight is correct the detected intensities from the two sources will be equal. It is essential that the scanning station is kept clean otherwise the dust is included in the weight reading and the cigarettes manufactured would be underweight. This can be checked using an artificial cigarette of known weight as a calibration check. In this device a test circuit can be connected to the scanner head and this opens the shutter over the radioactive source when the test is initiated. A warning device is initiated if the reading is beyond predetermined limits and can be made to prevent operation of the cigarette machine if a satisfactory test is not obtained. (U.K.)

  2. Vehicle electrical system state controller

    Science.gov (United States)

    Bissontz, Jay E.

    2017-10-17

    A motor vehicle electrical power distribution system includes a plurality of distribution sub-systems, an electrical power storage sub-system and a plurality of switching devices for selective connection of elements of and loads on the power distribution system to the electrical power storage sub-system. A state transition initiator provides inputs to control system operation of switching devices to change the states of the power distribution system. The state transition initiator has a plurality of positions selection of which can initiate a state transition. The state transition initiator can emulate a four position rotary ignition switch. Fail safe power cutoff switches provide high voltage switching device protection.

  3. ISABELLE control system: design concepts

    International Nuclear Information System (INIS)

    Humphrey, J.W.

    1979-01-01

    ISABELLE is a Department of Energy funded proton accelerator/storage ring being built at Brookhaven National Laboratory (Upton, Long Island, New York). It is large (3.8 km circumference) and complicated (approx. 30,000 monitor and control variables). It is based on superconducting technology. Following the example of previous accelerators, ISABELLE will be operated from a single control center. The control system will be distributed and will incorporate a local computer network. An overview of the conceptual design of the ISABELLE control system will be presented

  4. Traction Control System for Motorcycles

    Directory of Open Access Journals (Sweden)

    Cardinale Pascal

    2009-01-01

    Full Text Available Traction control is a widely used control system to increase stability and safety of four wheel vehicles. Automatic stability control is used in the BMW K1200R motorcycle and in motoGP competition, but not in other motorcycles. This paper presents an algorithm and a low-cost real-time hardware implementation for motorcycles. A prototype has been developed, applied on a commercial motorcycle, and tested in a real track. The control system that can be tuned by the driver during the race has been appreciated by the test driver.

  5. Controllability of a multichannel system

    Science.gov (United States)

    Ivanov, Sergei A.; Wang, Jun Min

    2018-02-01

    We consider the system consisting of K coupled acoustic channels with the different sound velocities cj. Channels are interacting at any point via the pressure and its time derivatives. Using the moment approach and the theory of exponential families with vector coefficients we establish two controllability results: the system is exactly controllable if (i) the control uj in the jth channel acts longer than the double travel time of a wave from the start to the end of the j-th channel; (ii) all controls uj act more than or equal to the maximal double travel time.

  6. Test results of HTTR control system

    International Nuclear Information System (INIS)

    Motegi, Toshihiro; Iigaki, Kazuhiko; Saito, Kenji; Sawahata, Hiroaki; Hirato, Yoji; Kondo, Makoto; Shibutani, Hideki; Ogawa, Satoru; Shinozaki, Masayuki; Mizushima, Toshihiko; Kawasaki, Kozo

    2006-06-01

    The plant control performance of the IHX helium flow rate control system, the PPWC helium flow rate control system, the secondary helium flow rate control system, the inlet temperature control system, the reactor power control system and the outlet temperature control system of the HTTR are obtained through function tests and power-up tests. As the test results, the control systems show stable control response under transient condition. Both of inlet temperature control system and reactor power control system shows stable operation from 30% to 100%, respectively. This report describes the outline of control systems and test results. (author)

  7. Formation Learning Control of Multiple Autonomous Underwater Vehicles With Heterogeneous Nonlinear Uncertain Dynamics.

    Science.gov (United States)

    Yuan, Chengzhi; Licht, Stephen; He, Haibo

    2017-09-26

    In this paper, a new concept of formation learning control is introduced to the field of formation control of multiple autonomous underwater vehicles (AUVs), which specifies a joint objective of distributed formation tracking control and learning/identification of nonlinear uncertain AUV dynamics. A novel two-layer distributed formation learning control scheme is proposed, which consists of an upper-layer distributed adaptive observer and a lower-layer decentralized deterministic learning controller. This new formation learning control scheme advances existing techniques in three important ways: 1) the multi-AUV system under consideration has heterogeneous nonlinear uncertain dynamics; 2) the formation learning control protocol can be designed and implemented by each local AUV agent in a fully distributed fashion without using any global information; and 3) in addition to the formation control performance, the distributed control protocol is also capable of accurately identifying the AUVs' heterogeneous nonlinear uncertain dynamics and utilizing experiences to improve formation control performance. Extensive simulations have been conducted to demonstrate the effectiveness of the proposed results.

  8. Efficient model learning methods for actor-critic control.

    Science.gov (United States)

    Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik

    2012-06-01

    We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.

  9. MULTIPLE ECH LAUNCHER CONTROL SYSTEM

    International Nuclear Information System (INIS)

    GREEN, M.T.; PONCE, D.; GRUNLOH, H.J.; ELLIS, R.A.; GROSNICKLE, W.H.; HUMPHREY, R.L.

    2004-03-01

    OAK-B135 The addition of new, high power gyrotrons to the heating and current drive arsenal at DIII-D, required a system upgrade for control of fully steerable ECH Launchers. Each launcher contains two pointing mirrors with two degrees of mechanical freedom. The two flavors of motion are called facet and tilt. Therefore up to four channels of motion per launcher need to be controlled. The system utilizes absolute encoders to indicate mirror position and therefore direction of the microwave beam. The launcher movement is primarily controlled by PLC, but future iterations of design, may require this control to be accomplished by a CPU on fast bus such as Compact PCI. This will be necessary to accomplish real time position control. Safety of equipment and personnel is of primary importance when controlling a system of moving parts. Therefore multiple interlocks and fault status enunciators have been implemented. This paper addresses the design of a Multiple ECH Launcher Control System, and characterizes the flexibility needed to upgrade to a real time position control system in the future

  10. Learning to teach secondary mathematics using an online learning system

    Science.gov (United States)

    Cavanagh, Michael; Mitchelmore, Michael

    2011-12-01

    We report the results of a classroom study of three secondary mathematics teachers who had no prior experience teaching with technology as they began to use an online mathematics learning system in their lessons. We gave the teachers only basic instruction on how to operate the system and then observed them intensively over four school terms as they taught using it. We documented changes in the teachers' Pedagogical Technology Knowledge and subsequently classified their various roles as technology bystanders, adopters, adaptors and innovators. Results show that all teachers made some progress toward using the system in more sophisticated ways, but the improvements were not uniform across the teachers. We suggest possible reasons to explain the variation and discuss some implications for teacher professional development.

  11. Weld analysis and control system

    Science.gov (United States)

    Kennedy, Larry Z. (Inventor); Rodgers, Michael H. (Inventor); Powell, Bradley W. (Inventor); Burroughs, Ivan A. (Inventor); Goode, K. Wayne (Inventor)

    1994-01-01

    The invention is a Weld Analysis and Control System developed for active weld system control through real time weld data acquisition. Closed-loop control is based on analysis of weld system parameters and weld geometry. The system is adapted for use with automated welding apparatus having a weld controller which is capable of active electronic control of all aspects of a welding operation. Enhanced graphics and data displays are provided for post-weld analysis. The system provides parameter acquisition, including seam location which is acquired for active torch cross-seam positioning. Torch stand-off is also monitored for control. Weld bead and parent surface geometrical parameters are acquired as an indication of weld quality. These parameters include mismatch, peaking, undercut, underfill, crown height, weld width, puddle diameter, and other measurable information about the weld puddle regions, such as puddle symmetry, etc. These parameters provide a basis for active control as well as post-weld quality analysis and verification. Weld system parameters, such as voltage, current and wire feed rate, are also monitored and archived for correlation with quality parameters.

  12. Learning, Leading, and Letting Go of Control

    DEFF Research Database (Denmark)

    Iversen, Ann-Merete; Pedersen, Anni Stavnskær; Kjær-Rasmussen, Lone Krogh

    2015-01-01

    The article introduces a new term in higher education: learner-led approaches in education (LED). This does not represent a single approach or dogma to replace existing dogmas, but a way of approaching learning and education that mirrors the complexity of society as it develops. LED is based...... on the assumption that all students have their own unique approach to learning and therefore have the potential to design learning processes that are meaningful for them. This removes focus from the teacher and the teaching to the learner and the learning. It builds on the student’s motivation and experienced...... meaningfulness as a driving force, and hence the term learner led. The methods applied in LED change over time, as different learners and teachers together co-create and design methods and approaches appropriate at that particular time, in that particular context and for that particular student or group...

  13. The BATES linac control system

    International Nuclear Information System (INIS)

    Russ, T.; Radouch, Z.

    1989-01-01

    The Bates linac control system (LCS), a distributed processing architecture, is described. Due to the historic evolution of the system, a mix of different hardware, operating systems and programming languages are used throughout. However, a standardized interface at the network level enables a smooth system integration. In particular, a multicasting scheme for data transmission over the network permits simultaneous database updates on more than one workstation. This allows for true distribution of data processing power. 3 figs

  14. Measuring strategic control in implicit learning: how and why?

    OpenAIRE

    Norman, Elisabeth

    2015-01-01

    Several methods have been developed for measuring the extent to which implicitly learned knowledge can be applied in a strategic, flexible manner. Examples include generation exclusion tasks in Serial Reaction Time (SRT) learning (Goschke, 1998; Destrebecqz and Cleeremans, 2001) and 2-grammar classification tasks in Artificial Grammar Learning (AGL; Dienes et al., 1995; Norman et al., 2011). Strategic control has traditionally been used as a criterion for determining whether acquired knowledg...

  15. Discrete Learning Control with Application to Hydraulic Actuators

    DEFF Research Database (Denmark)

    Andersen, Torben Ole; Pedersen, Henrik Clemmensen; Hansen, Michael R.

    2015-01-01

    In this paper the robustness of a class of learning control algorithms to state disturbances, output noise, and errors in initial conditions is studied. We present a simple learning algorithm and exhibit, via a concise proof, bounds on the asymptotic trajectory errors for the learned input...... and the corresponding state and output trajectories. Furthermore, these bounds are continuous functions of the bounds on the initial condition errors, state disturbance, and output noise, and the bounds are zero in the absence of these disturbances....

  16. Principles of e-learning systems engineering

    CERN Document Server

    Gilbert, Lester

    2008-01-01

    The book integrates the principles of software engineering with the principles of educational theory, and applies them to the problems of e-learning development, thus establishing the discipline of E-learning systems engineering. For the first time, these principles are collected and organised into the coherent framework that this book provides. Both newcomers to and established practitioners in the field are provided with integrated and grounded advice on theory and practice. The book presents strong practical and theoretical frameworks for the design and development of technology-based mater

  17. Component-Based Approach in Learning Management System Development

    Science.gov (United States)

    Zaitseva, Larisa; Bule, Jekaterina; Makarov, Sergey

    2013-01-01

    The paper describes component-based approach (CBA) for learning management system development. Learning object as components of e-learning courses and their metadata is considered. The architecture of learning management system based on CBA being developed in Riga Technical University, namely its architecture, elements and possibilities are…

  18. A Situated Cultural Festival Learning System Based on Motion Sensing

    Science.gov (United States)

    Chang, Yi-Hsing; Lin, Yu-Kai; Fang, Rong-Jyue; Lu, You-Te

    2017-01-01

    A situated Chinese cultural festival learning system based on motion sensing is developed in this study. The primary design principle is to create a highly interactive learning environment, allowing learners to interact with Kinect through natural gestures in the designed learning situation to achieve efficient learning. The system has the…

  19. Packaging of control system software

    International Nuclear Information System (INIS)

    Zagar, K.; Kobal, M.; Saje, N.; Zagar, A.; Sabjan, R.; Di Maio, F.; Stepanov, D.

    2012-01-01

    Control system software consists of several parts - the core of the control system, drivers for integration of devices, configuration for user interfaces, alarm system, etc. Once the software is developed and configured, it must be installed to computers where it runs. Usually, it is installed on an operating system whose services it needs, and also in some cases dynamically links with the libraries it provides. Operating system can be quite complex itself - for example, a typical Linux distribution consists of several thousand packages. To manage this complexity, we have decided to rely on Red Hat Package Management system (RPM) to package control system software, and also ensure it is properly installed (i.e., that dependencies are also installed, and that scripts are run after installation if any additional actions need to be performed). As dozens of RPM packages need to be prepared, we are reducing the amount of effort and improving consistency between packages through a Maven-based infrastructure that assists in packaging (e.g., automated generation of RPM SPEC files, including automated identification of dependencies). So far, we have used it to package EPICS, Control System Studio (CSS) and several device drivers. We perform extensive testing on Red Hat Enterprise Linux 5.5, but we have also verified that packaging works on CentOS and Scientific Linux. In this article, we describe in greater detail the systematic system of packaging we are using, and its particular application for the ITER CODAC Core System. (authors)

  20. Display systems for NPP control

    International Nuclear Information System (INIS)

    Rozov, S.S.

    1988-01-01

    Main trends in development of display systems used as the means for image displaying in NPP control systems are considered. It is shown that colour display devices appear to be the most universal means for concentrated data presentation. Along with digital means the display systems provide for high-speed response, sufficient for operative control of executive mechanisms. A conclusion is drawn that further development of display systems will move towards creation of large colour fields (on reflection base or with multicolour gas-discharge elements)

  1. The AGS Booster control system

    International Nuclear Information System (INIS)

    Frankel, R.; Auerbach, E.; Culwick, B.; Clifford, T.; Mandell, S.; Mariotti, R.; Salwen, C.; Schumburg, N.

    1988-01-01

    Although moderate in size, the Booster construction project requires a comprehensive control system. There are three operational modes: as a high intensity proton injector for the AGS, as a heavy ion accelerator and injector supporting a wide range of ions and as a polarized proton storage injector. These requirements are met using a workstation based extension of the existing AGS control system. Since the Booster is joining a complex of existing accelerators, the new system will be capable of supporting multiuser operational scenarios. A short discussion of this system is discussed in this paper

  2. VA National Bed Control System

    Data.gov (United States)

    Department of Veterans Affairs — The VA National Bed Control System records the levels of operating, unavailable and authorized beds at each VAMC, and it tracks requests for changes in these levels....

  3. DESIGNING MOTIVATIONAL LEARNING SYSTEMS IN DISTANCE EDUCATION

    Directory of Open Access Journals (Sweden)

    Jale BALABAN-SALI

    2008-07-01

    Full Text Available ABSTRACT The designing of instruction, when considered as a process, is the determination of instructional requirements of the learner and development of functional learning systems in order to meet these requirements. In fact, as a consequence of studies on the development of effective learning systems some instructional design theories have emerged. Among these theories the motivational design theory points out that instructional processes are required to be configured with the strategies which increases the attention, relevance, confidence and satisfaction of the students for an instructional design which ensures the continuity of learning motivation. The studies indicate that the systems which are developed on the basis of mentioned strategies raise the attention of the student during instruction, develop a relevance to the students’ requirements, create a positive expectation for success and help having a satisfaction by reinforcing success. In this article, the empirical studies related with this subject and the suggestions for presenting more effective motivational instructional designs in distance learning are summarized.

  4. Automated Subsystem Control for Life Support System (ASCLSS)

    Science.gov (United States)

    Block, Roger F.

    1987-01-01

    The Automated Subsystem Control for Life Support Systems (ASCLSS) program has successfully developed and demonstrated a generic approach to the automation and control of space station subsystems. The automation system features a hierarchical and distributed real-time control architecture which places maximum controls authority at the lowest or process control level which enhances system autonomy. The ASCLSS demonstration system pioneered many automation and control concepts currently being considered in the space station data management system (DMS). Heavy emphasis is placed on controls hardware and software commonality implemented in accepted standards. The approach demonstrates successfully the application of real-time process and accountability with the subsystem or process developer. The ASCLSS system completely automates a space station subsystem (air revitalization group of the ASCLSS) which moves the crew/operator into a role of supervisory control authority. The ASCLSS program developed over 50 lessons learned which will aide future space station developers in the area of automation and controls..

  5. What Learning Systems do Intelligent Agents Need? Complementary Learning Systems Theory Updated.

    Science.gov (United States)

    Kumaran, Dharshan; Hassabis, Demis; McClelland, James L

    2016-07-01

    We update complementary learning systems (CLS) theory, which holds that intelligent agents must possess two learning systems, instantiated in mammalians in neocortex and hippocampus. The first gradually acquires structured knowledge representations while the second quickly learns the specifics of individual experiences. We broaden the role of replay of hippocampal memories in the theory, noting that replay allows goal-dependent weighting of experience statistics. We also address recent challenges to the theory and extend it by showing that recurrent activation of hippocampal traces can support some forms of generalization and that neocortical learning can be rapid for information that is consistent with known structure. Finally, we note the relevance of the theory to the design of artificial intelligent agents, highlighting connections between neuroscience and machine learning. Copyright © 2016 Elsevier Ltd. All rights reserved.

  6. Control mechanisms in franchise systems

    OpenAIRE

    Hass, Jörg

    2012-01-01

    This dissertation answers the question which different control mechanisms exist in a franchise system. It is the first two-sided franchise empirical analysis, regarding all outlets of the franchise system (franchisees and company-owned) as well as the franchisor. On the theoretical side, this dissertation integrates the two main management theories: principal-agent-theory and transaction cost analysis. The results show that there are used different control mechanisms in a franchise sys...

  7. A cleanroom contamination control system

    OpenAIRE

    Whyte, W.; Eaton, T.

    2002-01-01

    Analytical methods for hazard and risk analysis are being considered for controlling contamination\\ud in pharmaceutical cleanrooms. The most suitable method appears to be the HACCP system that has\\ud been developed for the food industry, but this requires some reinterpretation for use in\\ud pharmaceutical manufacturing. This paper suggests a possible system.\\ud To control contamination effectively, it is necessary to have a good appreciation of the routes and\\ud sources of contamination, and ...

  8. Nova target diagnostics control system

    International Nuclear Information System (INIS)

    Severyn, J.R.

    1985-01-01

    During the past year the Nova target diagnostics control system was finished and put in service. The diagnostics loft constructed to the north of the target room provides the environmental conditions required to collect reliable target diagnostic data. These improvements include equipment cooling and isolation of the power source with strict control of instrumentation grounds to eliminate data corruption due to electromagnetic pulses from the laser power-conditioning system or from target implosion effects

  9. The ILC global control system

    International Nuclear Information System (INIS)

    Carwardine, J.; Arnold, N.; Lenkszus, F.; Saunders, C.; Rehlich, K.; Simrock, S.; Banerjee, B.; Chase, B.; Gottschalk, E.; Joireman, P.; Kasley, P.; Lackey, S.; McBride, P.; Pavlicek, V.; Patrick, J.; Votava, M.; Wolbers, S.; Furukawa, K.; Michizono, S.; Larsen, R.S.; Downing, R.

    2008-01-01

    The scale and performance parameters of the ILC require new thinking in regards to control system design. This design work has begun quite early in comparison to most accelerator projects, with the goal of uniquely high overall accelerator availability. Among the design challenges are high control system availability, precision timing and rf phase reference distribution, standardizing of interfaces, operability, and maintainability. We present the current state of the design and take a prospective look at ongoing research and development projects.

  10. Synthesis of pneumatic controll systems

    Directory of Open Access Journals (Sweden)

    D. Nowak

    2011-04-01

    Full Text Available Currently, the basic tool for automating the production processes are the PLCs. However, in many areas application of the pneumaticcontrol systems may be more reasonable. The main factor determining choice of the control technology are costs. In the case of pneumaticsystems, the costs shall be determined by the number of elements used. Therefore, during the design works it is important to choose anappropriate method for the pneumatic control systems synthesis. The article presents the MTS method, which may be used for a discretetechnological processes modeling and PLC programming, as well as for a pneumatic control systems designing. An important element ofthe MTS method is the network of actions, which graphically presents an algorithm of the implemented process. Based on the actionnetwork and operating machine’s functional diagram, the diagram of different states is determinated, which graphically shows changes ofthe control system’s input and output signals. Analysis of the diagram of different states, makes it easy to determine a schematic equation, which shall be the basis for the control system implementation. Advantage of the MTS method is the lack of restrictions on the number of the control system’s input and output signals. The resulting solution is characterized by a minimum number of elements needed to implement the control system.

  11. NPL superconducting Linac control system

    International Nuclear Information System (INIS)

    Swanson, H.E.; Howe, M.A.; Jackson, L.W.; LaCroix, J.M.; Readdy, H.P.; Storm, D.W.; Van Houten, L.P.

    1985-01-01

    The control system for the NPL Linac is based on a Microvax II host computer connected in a star network with 9 satellite computers. These satellites use single board varsions of DEC's PDP 11 processor. The operator's console uses high performance graphics and touch screen technology to display the current linac status and as the means for interactively controlling the operation of the accelerator

  12. Contamination Control: a systems approach

    NARCIS (Netherlands)

    Donck, J.C.J. van der

    2010-01-01

    Contamination influences a wide variety of industrial processes. For complex systems, contamination control, the collective effort to control contamination to such a level that it guarantees or even improves process or product functionality, offers a way for finding workable solutions. Central in

  13. INFORMATION SYSTEM QUALITY CONTROL KNOWLEDGE

    Directory of Open Access Journals (Sweden)

    Vladimir Nikolaevich Babeshko

    2017-02-01

    Full Text Available The development of the educational system is associated with the need to control the quality of educational services. Quality control knowledge is an important part of the scientific process. The penetration of computers into all areas of activities changing approaches and technologies that previously they were used.

  14. Control system oriented human interface

    International Nuclear Information System (INIS)

    Barale, P.; Jacobson, V.; Kilgore, R.; Rondeau, D.

    1976-11-01

    The on-line control system interface for magnet beam steering and focusing in the Bevalac is described. An Aydin model 5205B display generator was chosen. This display generator will allow the computer to completely rewrite a monitor screen in less than 50 ms and is also capable of controlling a color monitor

  15. Robust power system frequency control

    CERN Document Server

    Bevrani, Hassan

    2014-01-01

    This updated edition of the industry standard reference on power system frequency control provides practical, systematic and flexible algorithms for regulating load frequency, offering new solutions to the technical challenges introduced by the escalating role of distributed generation and renewable energy sources in smart electric grids. The author emphasizes the physical constraints and practical engineering issues related to frequency in a deregulated environment, while fostering a conceptual understanding of frequency regulation and robust control techniques. The resulting control strategi

  16. The ATLAS Detector Control System

    CERN Document Server

    Schlenker, S; Kersten, S; Hirschbuehl, D; Braun, H; Poblaguev, A; Oliveira Damazio, D; Talyshev, A; Zimmermann, S; Franz, S; Gutzwiller, O; Hartert, J; Mindur, B; Tsarouchas, CA; Caforio, D; Sbarra, C; Olszowska, J; Hajduk, Z; Banas, E; Wynne, B; Robichaud-Veronneau, A; Nemecek, S; Thompson, PD; Mandic, I; Deliyergiyev, M; Polini, A; Kovalenko, S; Khomutnikov, V; Filimonov, V; Bindi, M; Stanecka, E; Martin, T; Lantzsch, K; Hoffmann, D; Huber, J; Mountricha, E; Santos, HF; Ribeiro, G; Barillari, T; Habring, J; Arabidze, G; Boterenbrood, H; Hart, R; Marques Vinagre, F; Lafarguette, P; Tartarelli, GF; Nagai, K; D'Auria, S; Chekulaev, S; Phillips, P; Ertel, E; Brenner, R; Leontsinis, S; Mitrevski, J; Grassi, V; Karakostas, K; Iakovidis, G.; Marchese, F; Aielli, G

    2011-01-01

    The ATLAS experiment is one of the multi-purpose experiments at the Large Hadron Collider (LHC), constructed to study elementary particle interactions in collisions of high-energy proton beams. Twelve different sub-detectors as well as the common experimental infrastructure are supervised by the Detector Control System (DCS). The DCS enables equipment supervision of all ATLAS sub-detectors by using a system of >130 server machines running the industrial SCADA product PVSS. This highly distributed system reads, processes and archives of the order of 106 operational parameters. Higher level control system layers allow for automatic control procedures, efficient error recognition and handling, and manage the communication with external systems such as the LHC. This contribution firstly describes the status of the ATLAS DCS and the experience gained during the LHC commissioning and the first physics data taking operation period. Secondly, the future evolution and maintenance constraints for the coming years an...

  17. Locus of control and learning strategies as predictors of academic ...

    African Journals Online (AJOL)

    The aim of the research was to determine the relationships which exist between academic success, learning strategies and locus of control. In order to achieve this aim a small-scale quantitative study, utilising two inventories, was done. The first measuring instrument is the Learning and Study Strategies Inventory, which is ...

  18. Short-Term Memory, Executive Control, and Children's Route Learning

    Science.gov (United States)

    Purser, Harry R. M.; Farran, Emily K.; Courbois, Yannick; Lemahieu, Axelle; Mellier, Daniel; Sockeel, Pascal; Blades, Mark

    2012-01-01

    The aim of this study was to investigate route-learning ability in 67 children aged 5 to 11 years and to relate route-learning performance to the components of Baddeley's model of working memory. Children carried out tasks that included measures of verbal and visuospatial short-term memory and executive control and also measures of verbal and…

  19. Learned Helplessness: A Theory for the Age of Personal Control.

    Science.gov (United States)

    Peterson, Christopher; And Others

    Experiences with uncontrollable events may lead to the expectation that future events will elude control, resulting in disruptions in motivation, emotion, and learning. This text explores this phenomenon, termed learned helplessness, tracking it from its discovery to its entrenchment in the psychological canon. The volume summarizes and integrates…

  20. Indicators for successful learning in air traffic control training

    NARCIS (Netherlands)

    Van Meeuwen, Ludo; Brand-Gruwel, Saskia; Van Merriënboer, Jeroen; De Bock, Jeano; Kirschner, Paul A.

    2011-01-01

    Van Meeuwen, L. W., Brand-Gruwel, S., Van Merriënboer, J. J. G., De Bock, J. J. P. R., & Kirschner, P. A. (2010, August). Indicators for successful learning in air traffic control training. Paper presented at the 5th EARLI SIG 14 Learning and Professional Development Conference. Munich, Germany.