Journal articles: 'Data controllers'

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Burnett, Rachel. "Data controllers and data processors." ITNOW 47, no. 5 (September 1, 2005): 34. http://dx.doi.org/10.1093/itnow/bwi108.

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Jianwang, Hong, Ricardo A. Ramirez-Mendoza, and Ruben Morales-Menendez. "Iterative Data-Driven Control for Closed Loop with Two Unknown Controllers." Mathematical Problems in Engineering 2021 (August 3, 2021): 1–11. http://dx.doi.org/10.1155/2021/4827900.

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Iterative idea is combined with data-driven control and is used to design the feedforward controller and feedback controller simultaneously. Consider one closed loop system with two controllers, the classical model-based control holds on the condition of known plant. To alleviate the modeling process for plant, data-driven control is applied to design the two controllers. After these two controllers are parametrized by two unknown parameter vectors, the iterative idea is introduced to identify these two parameter vectors. Furthermore, for more general case of controllers, the closed relations between controllers and expected transfer functions are derived. Then, the iterative idea is also introduced to achieve the controller design. To be of benefit for latter stability analysis, some equities are derived for output-input sensitivity functions with three kinds of disturbances. Generally, after formulating the problem of the controller design as one model-matching problem, the purpose of this paper is threefold. First, we derive that, in case of two parametrized controllers, the iterative idea is performed to identify these two unknown parameter vectors, even when parameters converge to their true values. Second, we show how to design the two controllers iteratively for more general forms and find the closed relations between these controllers and expected closed loop transfer functions. Third, we provide some heuristic considerations on output-input sensitivity functions, which are of benefit for our stability analysis on data-driven control. Finally, one example is given to show the feasibility of our proposed theories.

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Safonov, Michael G., and Fabricio B. Cabral. "Fitting controllers to data." Systems & Control Letters 43, no. 4 (July 2001): 299–308. http://dx.doi.org/10.1016/s0167-6911(01)00112-8.

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Quadros, Mariella M., Ignacio Rubio Scola, and Valter J. S. Leite. "Compensated hybrid PI controllers for sampled-data controlled systems." IFAC-PapersOnLine 51, no. 25 (2018): 240–45. http://dx.doi.org/10.1016/j.ifacol.2018.11.112.

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JUDD, R. P., R. P. VAN TIL, and P. L. STUCKMAN. "Discrete time quantized data controllers." International Journal of Control 46, no. 4 (October 1987): 1225–33. http://dx.doi.org/10.1080/00207178708933964.

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Zhang, Bowei, and Pengcheng Liu. "Control and benchmarking of a 7-DOF robotic arm using Gazebo and ROS." PeerJ Computer Science 7 (March 23, 2021): e383. http://dx.doi.org/10.7717/peerj-cs.383.

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The robot controller plays an important role in controlling the robot. The controller mainly aims to eliminate or suppress the influence of uncertain factors on the control robot. Furthermore, there are many types of controllers, and different types of controllers have different features. To explore the differences between controllers of the same category, this article studies some controllers from basic controllers and advanced controllers. This article conducts the benchmarking of the selected controller through pre-set tests. The test task is the most commonly used pick and place. Furthermore, to complete the robustness test, a task of external force interference is also set to observe whether the controller can control the robot arm to return to a normal state. Subsequently, the accuracy, control efficiency, jitter and robustness of the robot arm controlled by the controller are analyzed by comparing the Position and Effort data. Finally, some future works of the benchmarking and reasonable improvement methods are discussed.

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Bainbridge, David, and Graham Pearce. "Data controllers and the new data protection law." Computer Law & Security Review 14, no. 4 (July 1998): 259–64. http://dx.doi.org/10.1016/s0267-3649(98)80044-7.

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John, Nicolas, and Maximilian Wellmann. "Data security management and data protection for video conferencing software." International Cybersecurity Law Review 1, no. 1-2 (October 2020): 39–50. http://dx.doi.org/10.1365/s43439-020-00013-4.

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Abstract Corona crisis and video conferencing software – two terms that now belong together. However, the demands controllers have on video conferencing software can quickly reach the limits of data protection regulations. In recent years, the progressive development of video conferencing software has already excited many users and led to significant growth. In ad hoc situations, like the Corona pandemic, issues regarding data protection are all too often neglected. This is fatal considering the fact that the implementation of video conferencing software is accompanied by a large number of data protection and security issues that must be addressed and weighed up by the controller. At first glance, technically feasible solutions can quickly turn out to be “Trojan horses” and pose a serious threat to personal data. Therefore, the selection, set-up and use of data protection-compliant video conferencing software is of great importance for controllers. This article aims to examine relevant questions regarding data protection and security management from a European legal perspective. In particular, the detailed analysis of the requirements of the General Data Protection Regulation (GDPR) as well as the practical consequences for the controller should provide practicians an overview of the legal problems associated with the implementation and use of video conferencing software.

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Jianwang, Hong, Ricardo A. Ramirez-Mendoza, and Tang Xiaojun. "Direct Data-Driven Control for Cascade Control System." Mathematical Problems in Engineering 2021 (August 28, 2021): 1–11. http://dx.doi.org/10.1155/2021/1465493.

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This paper combines system identification, direct data-driven control, and optimization algorithm to design two controllers for one cascade control system, that is, the inner controller and the outer controller. More specifically, when these two controllers in the cascade control system are parameterized by two unknown parameter vectors, respectively, the problem of controller design is changed to parameter identification. To avoid the modeling process for the unknown plants in the cascade control system, a direct data-driven control scheme is proposed to identify those two parameter vectors through minimizing two optimization problems, which do not need any knowledge of the unknown plants. Furthermore, the detailed first-order gradient algorithm is applied to solve our constructed optimization problems, and its convergence property is also analyzed. To extend the above idea to design a nonlinear controller in the cascade control system, a direct data-driven scheme is proposed to get one optimal nonlinear controller, by using some spectral knowledge. Finally, one simulation example of flight simulation is used to prove the efficiency of our proposed direct data-driven control for the cascade control system.

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Bai, Liang, Yun-Wen Feng, Ning Li, Xiao-Feng Xue, and Yong Cao. "Data-Driven Adaptive Iterative Learning Method for Active Vibration Control Based on Imprecise Probability." Symmetry 11, no. 6 (June 2, 2019): 746. http://dx.doi.org/10.3390/sym11060746.

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A data-driven adaptive iterative learning (IL) method is proposed for the active control of structural vibration. Considering the repeatability of structural dynamic responses in the vibration process, the time-varying proportional-type iterative learning (P-type IL) method was applied for the design of feedback controllers. The model-free adaptive (MFA) control, a data-driven method, was used to self-tune the time-varying learning gains of the P-type IL method for improving the control precision of the system and the learning speed of the controllers. By using multi-source information, the state of the controlled system was detected and identified. The square root values of feedback gains can be considered as characteristic parameters and the theory of imprecise probability was investigated as a tool for designing the stopping criteria. The motion equation was driven from dynamic finite element (FE) formulation of piezoelectric material, and then was linearized and transformed properly to design the MFA controller. The proposed method was numerically and experimentally tested for a piezoelectric cantilever plate. The results demonstrate that the proposed method performs excellent in vibration suppression and the controllers had fast learning speeds.

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Milašinović, Miloš, Dušan Prodanović, Budo Zindović, Boban Stojanović, and Nikola Milivojević. "Control theory-based data assimilation for hydraulic models as a decision support tool for hydropower systems: sequential, multi-metric tuning of the controllers." Journal of Hydroinformatics 23, no. 3 (February 22, 2021): 500–516. http://dx.doi.org/10.2166/hydro.2021.078.

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Abstract Increasing renewable energy usage puts extra pressure on decision-making in river hydropower systems. Decision support tools are used for near-future forecasting of the water available. Model-driven forecasting used for river state estimation often provides bad results due to numerous uncertainties. False inflows and poor initialization are some of the uncertainty sources. To overcome this, standard data assimilation (DA) techniques (e.g., ensemble Kalman filter) are used, which are not always applicable in real systems. This paper presents further insight into the novel, tailor-made model update algorithm based on control theory. According to water-level measurements over the system, the model is controlled and continuously updated using proportional–integrative–derivative (PID) controller(s). Implementation of the PID controllers requires the controllers’ parameters estimation (tuning). This research deals with this task by presenting sequential, multi-metric procedure, applicable for controllers’ initial tuning. The proposed tuning method is tested on the Iron Gate hydropower system in Serbia, showing satisfying results.

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Szabó, László, Klára Kubovicsné Stocz, Laura Szabó, Sándor Németh, and Ferenc Szeifert. "Dynamic Simulator-Based APC Design for a Naphtha Redistillation Column." Hungarian Journal of Industry and Chemistry 45, no. 1 (October 1, 2017): 17–22. http://dx.doi.org/10.1515/hjic-2017-0004.

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Abstract In this simulation study the operation of a naphtha redistillation column (a column with two feeds and three products) was analyzed with the application of Aspen HYSYS® software. The simulator, structure of local controllers and the product-quality estimators were based on the data of an industrial column in the Danube Refinery. The aim of the analysis was to identify the dynamic and steady-state effects of heating and cooling as well as the sidestream of product qualities. The relationship between the tray temperatures and the quality of the products was also identified and inferential calculations were made. Based on the identified relationships, a twolevel hierarchical control structure was developed. On the lowest level of the hierarchy are the local controllers of flowrates, liquid levels, pressure and duty. The inferential calculations are important components of the controller which serve as the controlled variables at the coordination level. The inputs of the estimators are the process data of the column, e.g. temperature, pressure and flowrate. On the top level of the control hierarchical structure the quality of the products are controlled by manipulating the setpoint of the local controllers. Based on the analysis of the Controlled Variable – Manipulated Variable relationship, closed-loop quality control was achieved with PID controllers. The result of the analysis may form the basis of Advanced Process Controller implementation.

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Jabbar, Abdul, and Fahad Mumtaz Malik. "Sampled-Data Backstepping Control of a Quadrotor Unmanned Aerial Vehicle." IAES International Journal of Robotics and Automation (IJRA) 4, no. 2 (June 1, 2014): 124. http://dx.doi.org/10.11591/ijra.v4i2.pp124-134.

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Sampled-data backstepping control of a quadrotor UAV is presented in this paper. The discrete time controllers have been designed on the basis of a continuous time system model and an approximate discrete time equivalent system model (Euler Approximate model) obtained using the Euler method. The performance of the controllers obtained using the two sampled-data approaches has been compared in the presence of wing gusts and modeling uncertainties. Simulations have revealed that the backstepping controller designed on the basis of an approximate discrete time model has better performance in the presence of wind gusts and modeling uncertainties. In addition, the closed loop system has a larger region of attraction.

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Madievski, A. "Optimum FWL Design of Sampled Data Controllers." IFAC Proceedings Volumes 26, no. 2 (July 1993): 499–502. http://dx.doi.org/10.1016/s1474-6670(17)49174-9.

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Formentin, Simone, Dario Piga, Roland Tóth, and Sergio M. Savaresi. "Direct learning of LPV controllers from data." Automatica 65 (March 2016): 98–110. http://dx.doi.org/10.1016/j.automatica.2015.11.031.

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Breschi, Valentina, and Simone Formentin. "Direct data‐driven design of switching controllers." International Journal of Robust and Nonlinear Control 30, no. 15 (December 18, 2019): 6042–72. http://dx.doi.org/10.1002/rnc.4821.

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Ferrarotti, Laura, and Alberto Bemporad. "Learning optimal switching feedback controllers from data." IFAC-PapersOnLine 53, no. 2 (2020): 1602–7. http://dx.doi.org/10.1016/j.ifacol.2020.12.2205.

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Joshi, Girisha, and Pinto Pius A J. "ANFIS controller for vector control of three phase induction motor." Indonesian Journal of Electrical Engineering and Computer Science 19, no. 3 (September 1, 2020): 1177. http://dx.doi.org/10.11591/ijeecs.v19.i3.pp1177-1185.

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For variable speed drive applications such as electric vehicles, 3 phase induction motor is used and is controlled by fuzzy logic controllers. For the steady functioning of the vehicle drive, it is essential to generate required torque and speed during starting, coasting, free running, braking and reverse operating regions. The drive performance under these transient conditions are studied and presented. In the present paper, vector control technique is implemented using three fuzzy logic controllers. Separate Fuzzy logic controllers are used to control the direct axis current, quadrature axis current and speed of the motor. In this paper performance of the indirect vector controller containing artificial neural network based fuzzy logic (ANFIS) based control system is studied and compared with regular fuzzy logic system, which is developed without using artificial neural network. Data required to model the artificial neural network based fuzzy inference system is obtained from the PI controlled induction motor system. Results obtained in MATLAB-SIMULINK simulation shows that the ANFIS controller is superior compared to controller which is implemented only using fuzzy logic, under all dynamic conditions.

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Shieh, Leang-san, Wei-min Wang, and John W. Sunkel. "Design of PAM and PWM Controllers for Sampled-Data Interval Systems." Journal of Dynamic Systems, Measurement, and Control 118, no. 4 (December 1, 1996): 673–82. http://dx.doi.org/10.1115/1.2802342.

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In this paper, we address two issues: digital redesign of a continuous-time interval system using an interval chebyshev quadrature approximation method; and translation of the newly digitally redesigned pulse-amplitude modulated (PAM) controller into an equivalent pulse-width modulated (PWM) controller via a second-order Taylor-series approximation method. Using this new interval digital redesign technique, the dynamic states of the digitally controlled sampled-data interval system are able to closely match those of the original analogously controlled continuous-time uncertain system. Three illustrative examples are provided to demonstrate the effectiveness of the proposed methods.

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Mamat, Normaisharah, Fitri Yakub, and Sheikh Ahmad Zaki Sheikh Salim. "Analysis of controllers in suppressing the structural building vibration." Malaysian Journal of Fundamental and Applied Sciences 15, no. 1 (February 4, 2019): 112–16. http://dx.doi.org/10.11113/mjfas.v15n2019.1101.

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Two degree of freedom (2 DOF) mass spring damper system is used in representing as building structure that dealing with the earthquake vibration. The real analytical input is used to the system that taken at El Centro earthquake that occurred in May 1940 with magnitude of 7.1 Mw. Two types of controller are presented in controlling the vibration which are fuzzy logic (FL) and sliding mode controller (SMC). The paper was aimed to improve the performance of building structure towards vibration based on proposed controllers. Fuzzy logic and sliding mode controller are widely known with robustness character. The mathematical model of two degree of freedom mass spring damper wasis derived to obtain the relationship between mass, spring, damper, force and actuator. Fuzzy logic and sliding mode controllers were implemented to 2 DOF system to suppress the earthquake vibration of two storeys building. Matlab/Simulink was used in designing the system and controllers to present the result of two storeys displacement time response and input control voltage for uncontrolled and controlled system. Then the data of earthquake disturbance was taken based on real seismic occurred at El Centro to make it as the force disturbance input to the building structure system. The controllers proposed would minimize the vibration that used in sample earthquake disturbance data. The simulation result was carried out by using Matlab/Simulink. The simulation result showed sliding mode controller was better controller than fuzzy logic. In specific, by using the controller, earthquake vibration can be reduced.

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Matsumori, Hiroki, Shin Wakitani, and Mingcong Deng. "Design and Application of a Data-Driven Expert Controller Based on the Operating Data of a Skilled Worker." Journal of Robotics and Mechatronics 28, no. 5 (October 20, 2016): 730–38. http://dx.doi.org/10.20965/jrm.2016.p0730.

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[abstFig src='/00280005/16.jpg' width='300' text='Schematic of data-driven expert controller' ] In recent years, due to the mass retirement of skilled workers, loss of expertise has emerged as a problem in Japan. Meanwhile, the performance of computer hardware has been drastically improving. Skill-based PID controllers utilizing a database have been proposed as a potential solution to this problem. However, these controllers may not respond to multiple demands of control performance from users because the controller was not considered in the evaluation from the users. As a solution to this problem, an expert controller based on a skilled worker’s operating information with control performance assessments has been proposed. According to the method, I/O data, PID parameters that are estimated using the operating data and evaluation values of the skill of the skilled worker are stored in the database. From this, information vectors with high scores are selected, and a local PID controller is designed in response to the user’s requirements. In the conventional research, the least squares method is applied for estimating the PID parameters from the operating data of the skilled worker, and there are no restrictions on their values. This risks a loss of physical meanings of PID parameters in the case that they have negative values. In this research, an expert controller using particle swarm optimization (PSO) is proposed. In this method, data obtained by human control of a control simulator constructed on a computer is used to estimate human’s skill as PID parameters. Moreover, providing restrictions for the estimation of PID parameters enables them to preserve their physical meanings. In this research, the effectiveness of the proposed expert controller is verified using a control simulator.

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Muluye, Worku. "A Review on Software-Defined Networking Distributed Controllers." International Journal of Engineering and Computer Science 9, no. 2 (February 15, 2020): 24953–61. http://dx.doi.org/10.18535/ijecs/v9i2.4439.

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A computer network is a critical issue in our day to day activity; however, today it works under various problems. Since in the current network architecture the control plane and data plane are vertically bundled on the same device. To solve this problem programmable Software-Defined Network is released. OpenFlow is a protocol that vertically separates control plane and data plane of the network devices. In SDN the controllers are the brains of the network that controls the network devices. Today’s network required successful integration of distributed controllers to make the network more consistent. SDN distributed controller is a controller that we can add or remove the controllers according to the number of devices change. Distributed controller architecture has investigated and compared the 6 recent distributed controllers by using 26 criteria. Orion is the first best controller and ONOS is the second best controller.

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Chen, Lequn, Xiling Yao, Youxiang Chew, Fei Weng, Seung Ki Moon, and Guijun Bi. "Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning." Applied Sciences 10, no. 22 (November 10, 2020): 7967. http://dx.doi.org/10.3390/app10227967.

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Closed-loop control is desirable in direct energy deposition (DED) to stabilize the process and improve the fabrication quality. Most existing DED controllers require system identifications by experiments to obtain plant models or layer-dependent adaptive control rules, and such processes are cumbersome and time-consuming. This paper proposes a novel data-driven adaptive control strategy to adjust laser voltage with the melt pool size feedback. A multitasking controller architecture is developed to incorporate an autotuning unit that optimizes controller parameters based on the DED process data automatically. Experimental validations show improvements in the geometric accuracy and melt pool consistency of controlled samples. The main advantage of the proposed controller is that it can adapt to DED processes with different part shapes, materials, tool paths, and process parameters without tweaking. System identification is not required even when process conditions are changed, which reduces the controller implementation time and cost for end-users.

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Wong, Janis, and Tristan Henderson. "Co-Creating Autonomy: Group Data Protection and Individual Self-determination within a Data Commons." International Journal of Digital Curation 15, no. 1 (August 11, 2020): 16. http://dx.doi.org/10.2218/ijdc.v15i1.714.

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Recent privacy scandals such as Cambridge Analytica and the Nightingale Project show that data sharing must be carefully managed and regulated to prevent data misuse. Data protection law, legal frameworks, and technological solutions tend to focus on controller responsibilities as opposed to protecting data subjects from the beginning of the data collection process. Using a case study of how data subjects can be better protected during data curation, we propose that a co-created data commons can protect individual autonomy over personal data through collective curation and rebalance power between data subjects and controllers.

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Nowaková, Jana, and Miroslav Pokorný. "Intelligent Controller Design by the Artificial Intelligence Methods." Sensors 20, no. 16 (August 10, 2020): 4454. http://dx.doi.org/10.3390/s20164454.

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With the rapid growth of sensor networks and the enormous, fast-growing volumes of data collected from these sensors, there is a question relating to the way it will be used, and not only collected and analyzed. The data from these sensors are traditionally used for controlling and influencing the states and processes. Standard controllers are available and successfully implemented. However, with the data-driven era we are facing nowadays, there is an opportunity to use controllers, which can include much information, elusive for common controllers. Our goal is to propose a design of an intelligent controller–a conventional controller, but with a non-conventional method of designing its parameters using approaches of artificial intelligence combining fuzzy and genetics methods. Intelligent adaptation of parameters of the control system is performed using data from the sensors measured in the controlled process. All parts designed are based on non-conventional methods and are verified by simulations. The identification of the system’s parameters is based on parameter optimization by means of its difference equation using genetic algorithms. The continuous monitoring of the quality control process and the design of the controller parameters are conducted using a fuzzy expert system of the Mamdani type, or the Takagi–Sugeno type. The concept of the intelligent control system is open and easily expandable.

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Hu, Liang, Jiejun Hu, Tao Fu, Jiyang Bao, and Feng Wang. "Asymmetric network information cache based on mobile traffic in software-defined network." Advances in Mechanical Engineering 11, no. 1 (January 2019): 168781401881989. http://dx.doi.org/10.1177/1687814018819894.

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Software-defined network is an encouraging research area that realizes updates throughout an entire network, and a wireless network is ubiquitous in an up-to-date world. The combination of these techniques, which is referred to as a wireless software-defined network, has been a significant development in numerous testbeds. The extensive use of distributed controllers that achieved elastic extension and are fault tolerant in large-scale wireless networks is hopeful. Despite their profits, they generate significant overhead in synchronizing network information. Thus, power-hungry wireless software-defined network devices limit the usage of distributed controllers in wireless networks. The patterns of storing network information have a crucial effect on controller performances, as they determine the probability of processing requests based on local data. To address this problem, we identify a better pattern for controllers to retain proper network information to balance costs in terms of both synchronous traffic and response time. We analyze the characteristics of distributed controllers and propose an overhead model of a distributed controller in a wireless software-defined network. Based on this model, we design an asymmetric network information cache to make trade-offs among different controller architectures. The asymmetric network information cache measures real-time network traffic and computes the traffic among sub-networks controlled by controller nodes. Then, the controller asymmetrically caches suitable network data to substantially busier nodes. The experimental results indicate that the asymmetric network information cache achieves a trade-off between synchronous traffic and the average response time.

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KEEL, Lee H., Sandipan MITRA, and Shankar P. BHATTACHARYYA. "Data Driven Synthesis of Three Term Digital Controllers." SICE Journal of Control, Measurement, and System Integration 1, no. 2 (2008): 102–10. http://dx.doi.org/10.9746/jcmsi.1.102.

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Chen, Zhiyong, and Hisaya Fujioka. "Performance Analysis of Nonlinear Sampled-Data Emulated Controllers." IEEE Transactions on Automatic Control 59, no. 10 (October 2014): 2778–83. http://dx.doi.org/10.1109/tac.2014.2312854.

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Wong, W. S., and C. W. Sung. "Robust Convergence of Low-Data Rate-Distributed Controllers." IEEE Transactions on Automatic Control 49, no. 1 (January 2004): 82–87. http://dx.doi.org/10.1109/tac.2003.821418.

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Smith, Craig, Masayoshi Tumizuka, and Kenji Takeuchi. "Cost effective repetitive controllers for data storage devices." IFAC Proceedings Volumes 32, no. 2 (July 1999): 891–96. http://dx.doi.org/10.1016/s1474-6670(17)56150-9.

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Pena, Ricardo S. Sanchez. "Approximation of analog controllers for sampled-data systems." Journal of Guidance, Control, and Dynamics 13, no. 6 (November 1990): 1155–57. http://dx.doi.org/10.2514/3.20593.

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de Oliveira Pacheco, Nazareno. "Use neutral data interfaces for Numerical Controllers Computerized." IEEE Latin America Transactions 15, no. 6 (June 2017): 1212–18. http://dx.doi.org/10.1109/tla.2017.7932711.

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Schulte, Alexandra, and Oliver Bülchmann. "Wie Big Data die Rolle des Controllers verändert." Controlling & Management Review 60, S1 (March 2016): 54–61. http://dx.doi.org/10.1007/s12176-016-0004-0.

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Bisoffi, Andrea, Claudio De Persis, and Pietro Tesi. "Trade-offs in learning controllers from noisy data." Systems & Control Letters 154 (August 2021): 104985. http://dx.doi.org/10.1016/j.sysconle.2021.104985.

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Han, Shah, and Lee. "Holographic Mixed Reality System for Air Traffic Control and Management." Applied Sciences 9, no. 16 (August 15, 2019): 3370. http://dx.doi.org/10.3390/app9163370.

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Based on a long-term prediction by the International Civil Aviation Organization indicating steady increases in air traffic demand throughout the world, the workloads of air traffic controllers are expected to continuously increase. Air traffic control and management (ATC/M) includes the processing of various unstructured composite data along with the real-time visualization of aircraft data. To prepare for future air traffic, research and development intended to effectively present various complex navigation data to air traffic controllers is necessary. This paper presents a mixed reality-based air traffic control system for the improvement of and support for air traffic controllers’ workflow using mixed reality technology that is effective for the delivery of information such as complex navigation data. The existing control systems involve difficulties in information access and interpretation. Therefore, taking notice of the necessity for the integration of air traffic control systems, this study presents the mixed reality (MR) system, which is a new approach, that enables the control of air traffic in interactive environments. This system is provided in a form usable in actual operational environments with a head-mounted see-through display installed with a controller to enable more structured work support. In addition, since this system can be controlled first-hand by air traffic controllers, it provides a new experience through improved work efficiency and productivity.

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Li, Xian-Sheng, Yuan-Yuan Ren, and Xue-Lian Zheng. "Model-Free Adaptive Control for Tank Truck Rollover Stabilization." Mathematical Problems in Engineering 2021 (August 20, 2021): 1–16. http://dx.doi.org/10.1155/2021/8417071.

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Influenced by lateral liquid sloshing in partially filled tanks, tank vehicles are apt to encounter with rollover accidents. Due to its strong nonlinearity and loading state uncertainty, it has great challenges in tank vehicle active control. Based on the model-free adaptive control (MFAC) theory, the roll stability control problem of tank trucks with different tank shapes and liquid fill percentages is explored. First, tank trucks equipped with cylinder or elliptical cylinder tanks are modelled, and vehicle dynamics is analyzed. This dynamic model is used to provide I/O data in the controlled system. Next, the control objective of tank vehicle rollover stabilization is analyzed and the controlled variable is selected. Subsequently, differential braking and active front steering controller are designed by MFAC algorithm. Finally, the effectiveness of the designed controllers is verified by simulation, and difference between the controllers is analyzed. The controller designed by MFAC algorithm is proven to be adaptive to vehicle loading and driving states. The controlled system has great robustness.

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Guerlain, Stephanie, Greg Jamieson, and Peter Bullemer. "Visualizing Model-Based Predictive Controllers." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 22 (July 2000): 511–14. http://dx.doi.org/10.1177/154193120004402203.

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One common problem with information displays, particularly in process control, is that relevant data is often scattered across several, separate displays that obscure important relationships and fail to show event information. The current displays used for model-based predictive controllers demonstrate several of the problems that this kind of a design can incur. It is hard to get a good sense of the recent, current and near-future status of the controller (situation awareness), and it is difficult to make informed decision when making changes to the controller (putting data into context). This forces users to navigate around a virtual workspace and attempt to compile the data necessary to make an informed conclusion. We have applied several design principles to show how it is possible to re-represent data into hierarchical data layers that support the cognitive tasks of monitoring, diagnosis, and control. This design forms a coherent, coordinated workspace which helps orient users to problems in the controller, with direct navigation to supporting details.

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Silva, Bruno E., and Ramiro S. Barbosa. "Experiments with Neural Networks in the Identification and Control of a Magnetic Levitation System Using a Low-Cost Platform." Applied Sciences 11, no. 6 (March 12, 2021): 2535. http://dx.doi.org/10.3390/app11062535.

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In this article, we designed and implemented neural controllers to control a nonlinear and unstable magnetic levitation system composed of an electromagnet and a magnetic disk. The objective was to evaluate the implementation and performance of neural control algorithms in a low-cost hardware. In a first phase, we designed two classical controllers with the objective to provide the training data for the neural controllers. After, we identified several neural models of the levitation system using Nonlinear AutoRegressive eXogenous (NARX)-type neural networks that were used to emulate the forward dynamics of the system. Finally, we designed and implemented three neural control structures: the inverse controller, the internal model controller, and the model reference controller for the control of the levitation system. The neural controllers were tested on a low-cost Arduino control platform through MATLAB/Simulink. The experimental results proved the good performance of the neural controllers.

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Sands, Timothy. "Comparison and Interpretation Methods for Predictive Control of Mechanics." Algorithms 12, no. 11 (November 4, 2019): 232. http://dx.doi.org/10.3390/a12110232.

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Objects that possess mass (e.g., automobiles, manufactured items, etc.) translationally accelerate in direct proportion to the force applied scaled by the object’s mass in accordance with Newton’s Law, while the rotational companion is Euler’s moment equations relating angular acceleration of objects that possess mass moments of inertia. Michel Chasles’s theorem allows us to simply invoke Newton and Euler’s equations to fully describe the six degrees of freedom of mechanical motion. Many options are available to control the motion of objects by controlling the applied force and moment. A long, distinguished list of references has matured the field of controlling a mechanical motion, which culminates in the burgeoning field of deterministic artificial intelligence as a natural progression of the laudable goal of adaptive and/or model predictive controllers that can be proven to be optimal subsequent to their development. Deterministic A.I. uses Chasle’s claim to assert Newton’s and Euler’s relations as deterministic self-awareness statements that are optimal with respect to state errors. Predictive controllers (both continuous and sampled-data) derived from the outset to be optimal by first solving an optimization problem with the governing dynamic equations of motion lead to several controllers (including a controller that twice invokes optimization to formulate robust, predictive control). These controllers are compared to each other with noise and modeling errors, and the many figures of merit are used: tracking error and rate error deviations and means, in addition to total mean cost. Robustness is evaluated using Monte Carlo analysis where plant parameters are randomly assumed to be incorrectly modeled. Six instances of controllers are compared against these methods and interpretations, which allow engineers to select a tailored control for their given circumstances. Novel versions of the ubiquitous classical proportional-derivative, “PD” controller, is developed from the optimization statement at the outset by using a novel re-parameterization of the optimal results from time-to-state parameterization. Furthermore, time-optimal controllers, continuous predictive controllers, and sampled-data predictive controllers, as well as combined feedforward plus feedback controllers, and the two degree of freedom controllers (i.e., 2DOF). The context of the term “feedforward” used in this study is the context of deterministic artificial intelligence, where analytic self-awareness statements are strictly determined by the governing physics (of mechanics in this case, e.g., Chasle, Newton, and Euler). When feedforward is combined with feedback per the previously mentioned method (provenance foremost in optimization), the combination is referred to as “2DOF” or two degrees of freedom to indicate the twice invocation of optimization at the genesis of the feedforward and the feedback, respectively. The feedforward plus feedback case is augmented by an online (real time) comparison to the optimal case. This manuscript compares these many optional control strategies against each other. Nominal plants are used, but the addition of plant noise reveals the robustness of each controller, even without optimally rejecting assumed-Gaussian noise (e.g., via the Kalman filter). In other words, noise terms are intentionally left unaddressed in the problem formulation to evaluate the robustness of the proposed method when the real-world noise is added. Lastly, mismodeled plants controlled by each strategy reveal relative performance. Well-anticipated results include the lowest cost, which is achieved by the optimal controller (with very poor robustness), while low mean errors and deviations are achieved by the classical controllers (at the highest cost). Both continuous predictive control and sampled-data predictive control perform well at both cost as well as errors and deviations, while the 2DOF controller performance was the best overall.

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Majetta, Kristin, Christoph Clauß, and Christoph Nytsch-Geusen. "Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating." Electronics 10, no. 4 (February 23, 2021): 523. http://dx.doi.org/10.3390/electronics10040523.

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This paper describes a way to generate a great amount of data and to use it to find a relation between a room controller and a certain room. Therefore, simulation scenarios are defined and developed that contain different room, location, usage and controller models. With parameter variation and optimization of the corresponding controller parameters a data basis is created with about 5300 entries. On the basis of this data, machine learning algorithms like artificial neural networks can be used to investigate the relation between rooms and their best suited controllers.

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Plummer, A. R. "A comparison of linear discrete-time design methods for servosystem control." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 211, no. 4 (June 1, 1997): 281–300. http://dx.doi.org/10.1243/0959651971539812.

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Three linear discrete-time model-based controller design techniques are compared: pole placement, linear quadratic Gaussian (LQG) and H∞ control. It is shown that design choices can be made for all three controllers by considering the effect on the sensitivity functions of the closed-loop system. Also all three controllers can be implemented using an identical controller structure. A comparative study of the application of the techniques to an electromechanical servosystem is made. The controllers are designed from a discrete-time plant model estimated from experimental data, and a polynomial-based solution method is used in each case. It is concluded that acceptable performance can be achieved using any of the controllers if informed design choices are made.

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Al mahdawi, Raghda Salam, and Huda M. Salih. "Optimization of open flow controller placement in software defined networks." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 4 (August 1, 2021): 3145. http://dx.doi.org/10.11591/ijece.v11i4.pp3145-3153.

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The world is entering into the era of Big Data where computer networks are an essential part. However, the current network architecture is not very convenient to configure such leap. Software defined network (SDN) is a new network architecture which argues the separation of control and data planes of the network devices by centralizing the former in high level, centralised devices and efficient supervisors, called controllers. This paper proposes a mathematical model that helps optimizing the locations of the controllers within the network while minimizing the overall cost under realistic constrains. Our method includes finding the minimum cost of placing the controllers; these costs are the network latency, controller processing power and link bandwidth. Different types of network topologies have been adopted to consider the data profile of the controllers, links of controllers and locations of switches. The results showed that as the size of input data increased, the time to find the optimal solution also increased in a non-polynomial time. In addition, the cost of solution is increased linearly with the input size. Furthermore, when increasing allocating possible locations of the controllers, for the same number of switches, the cost was found to be less.

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Li Qin and Tongwen Chen. "Multirate sampled-data systems: all H/sub ∞/ suboptimal controllers and the minimum entropy controller." IEEE Transactions on Automatic Control 44, no. 3 (March 1999): 537–50. http://dx.doi.org/10.1109/9.751347.

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Duley, Jacqueline A., Scott M. Galster, and Raja Parasuraman. "Information Manager for Determining Data Presentation Preferences in Future Enroute Air Traffic Management." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 1 (October 1998): 47–51. http://dx.doi.org/10.1177/154193129804200112.

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One proposed vision of the future National Airspace System (NAS) involves a change in philosophy from that of air traffic control to one of air traffic management, i.e. Free Flight. In order to accommodate this philosophy change, new technologies will be implemented to assist the air traffic manager (today's air traffic controller) in decision making. When enhancing the system we must also consider the interface between the air traffic manager and this new system and its corresponding new philosophy. To better determine the design of such an interface we must first understand the information needs of the air traffic manager. The present study investigated the information requirements of 58 enroute air traffic controllers. The controllers provided their preferences in presentation frequency as well as the importance of the information to be displayed. The results reveal the potential for adaptive automation as a form of information management.

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Agarwala, Ranjeet, and Robert A. Chin. "Innovative Controller Design for a 5MW Wind Turbine Blade." Journal of Sustainable Development 11, no. 4 (July 29, 2018): 78. http://dx.doi.org/10.5539/jsd.v11n4p78.

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The development and evaluation of a nonlinear pitch controller for wind turbine blades and the design and modeling of an associated actuator and controller was examined. The pitch actuator and controller were modeled and analyzed using Pneumatically Actuated Muscles (PAMs) for actively pitching the wind turbine blade. PAMs are very light and have a high specific work and a good contraction ratio. Proportional Integral and Derivative (PID) controllers were envisaged for the wind turbine pitching system at the blade tip due to its routine usage in the wind turbine industry. Deployment of controllers enables effective pitch angle tracking for power abatement at various configurations. The controller was subjected to four pitch angle trajectory signals. PID controllers were tuned to achieve satisfactory performance when subjected to the test signal. Low pitch angle errors resulted in satisfactory blade pitch angle tracking. Deployment of these controllers enhances wind turbine performance and reliability. The data suggest that the pitch system and actuator that was modeled using PAMs and PID controllers is effective providing robust pitch angle trajectory tracking. The results suggest that the proposed design can be successfully integrated into the family of wind turbine blade pitch angle controller technologies.

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Fan, Li, Lei Wei, and Xin Jian Zhao. "A Hierarchical Control Strategy of Multi-Microgrids." Applied Mechanics and Materials 738-739 (March 2015): 955–61. http://dx.doi.org/10.4028/www.scientific.net/amm.738-739.955.

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This paper gives a hierarchical control strategy of multi-microgrids. The hierarchical control structure is made up with microgrid center controller (MGCC), microgrid controller (MC), generator controller (GC), load controller (LC). Controllers recognize the current operation mode of microgrids according to state trigger event and local operation state, realize transition of operation state. Controller is controlled by the upper controller, but once the communication among controllers is interrupted, MC can operate normally according to its local operation state. Thus, the MCs have a certain independence. The simulation platform is built-up by Netlogo for simulation of controller logic and communication coordination mechanism, OpenDSS for modeling distribution network and multi-microgrids, and matlab for data transmission and control optimization. With the simulation platform, this paper analyzed the characteristics of power regulation and different state transitions of multi-microgrids. Through verification, the strategy is available to realize operation state transition of multi-microgrids, guarantee stability of multi-microgrids under every operation state. Besides, compared with centralized control, it has better control effect and it has faster response.

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Kamal, Tariq, Murat Karabacak, Vedran S. Perić, Syed Zulqadar Hassan, and Luis M. Fernández-Ramírez. "Novel Improved Adaptive Neuro-Fuzzy Control of Inverter and Supervisory Energy Management System of a Microgrid." Energies 13, no. 18 (September 10, 2020): 4721. http://dx.doi.org/10.3390/en13184721.

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In this paper, energy management and control of a microgrid is developed through supervisor and adaptive neuro-fuzzy wavelet-based control controllers considering real weather patterns and load variations. The supervisory control is applied to the entire microgrid using lower–top level arrangements. The top-level generates the control signals considering the weather data patterns and load conditions, while the lower level controls the energy sources and power converters. The adaptive neuro-fuzzy wavelet-based controller is applied to the inverter. The new proposed wavelet-based controller improves the operation of the proposed microgrid as a result of the excellent localized characteristics of the wavelets. Simulations and comparison with other existing intelligent controllers, such as neuro-fuzzy controllers and fuzzy logic controllers, and classical PID controllers are used to present the improvements of the microgrid in terms of the power transfer, inverter output efficiency, load voltage frequency, and dynamic response.

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Tung, Shu Chu, Wu Jeng Li, Kuang Chyi Lee, and Jui Chang Lin. "Environment Supervisory Control of Computer Room Based on Android Device." Applied Mechanics and Materials 418 (September 2013): 124–27. http://dx.doi.org/10.4028/www.scientific.net/amm.418.124.

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This research designs environment supervisory control system of computer room which consists of multiple Android environment controllers and one supervisory control server. An Android environment controller is a controller based on Android device. The controller contains an Android device, a Wi-Fi wireless access point, a switch hut (or NAT) and three data acquisition modules. The Android device enters TCP/IP LAN through the Wi-Fi access point. The data acquisition modules with TCP/IP interface are plugged into the LAN, and read/written by the Android device with Modbus TCP/IP protocol. Control logics are designed for computer room environment control. The controller monitors air conditioning systems, room temperature and humidity, fire alarm systems, uninterruptible power supply (UPS) systems, electricity supply systems, leak detections, and door access control systems. If something happens, it can drive buzzer, alarm, voice dialing, or air conditioning, send SMS, voice mail, record audio, or video. A supervisory control server is used to help remote controls of all Android environment controllers. All Android controllers send their operation data to the server. Authorized user can login to the server to monitor and control certain Android controller with a browser or Android device.

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De Loo, I., and B. Verstegen. "Het onderscheiden van groepen controllers op basis van activiteiten." Maandblad Voor Accountancy en Bedrijfseconomie 82, no. 12 (December 1, 2008): 541–49. http://dx.doi.org/10.5117/mab.82.13867.

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Er bestaat veel onduidelijkheid over wat precies een ‘controllerrol’ is en welke rollen er zoal te onderscheiden zijn in de literatuur. In dit artikel wordt een empirisch geïnformeerd conceptueel raamwerk geïntroduceerd dat in volgende onderzoeken kan worden verfi jnd. Controllers worden ingedeeld in groepen op basis van de activiteiten die zij verrichten. Vervolgens worden variabelen onderscheiden die het groepslidmaatschap van een controller kunnen verklaren. Hierbij wordt gebruikgemaakt van Nederlandse data van controllers die zijn afgestudeerd aan vier opleidingen. Geconcludeerd wordt dat deze controllers ofwel als information adapters (controllers die de nadruk leggen op het verzamelen, analyseren en rapporteren van informatie, alsmede op het ondersteunen van veranderingsprocessen) ofwel als watchmen (controllers die scorekeepingactiviteiten en risicomonitoring benadrukken) kunnen worden geclassifi ceerd.

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Graves, Martin J., Richard T. Black, and David J. Lomas. "Constrained Surface Controllers for Three-dimensional Image Data Reformatting." Radiology 252, no. 1 (July 2009): 218–24. http://dx.doi.org/10.1148/radiol.2521081368.

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Journal articles on the topic 'Data controllers'

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