Relevant bibliographies by topics / Control and diagnostic algorithm

Academic literature on the topic 'Control and diagnostic algorithm'

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Published: 30 May 2022
Last updated: 31 May 2022

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Journal articles on the topic "Control and diagnostic algorithm"

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Bien, Z., M. J. Youn, M. J. Chung, J. H. Kim, B. C. Moon, and B. K. Kim. "A Fault Diagnostic Algorithm for Fault Tolerant Control Systems." IFAC Proceedings Volumes 19, no. 13 (November 1986): 119–22. http://dx.doi.org/10.1016/s1474-6670(17)59526-9.

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Park, Seong Ho. "Diagnostic Case-Control versus Diagnostic Cohort Studies for Clinical Validation of Artificial Intelligence Algorithm Performance." Radiology 290, no. 1 (January 2019): 272–73. http://dx.doi.org/10.1148/radiol.2018182294.

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Zheng, Chanjin, and Chun Wang. "Application of Binary Searching for Item Exposure Control in Cognitive Diagnostic Computerized Adaptive Testing." Applied Psychological Measurement 41, no. 7 (May 11, 2017): 561–76. http://dx.doi.org/10.1177/0146621617707509.

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Cognitive diagnosis has emerged as a new generation of testing theory for educational assessment after the item response theory (IRT). One distinct feature of cognitive diagnostic models (CDMs) is that they assume the latent trait to be discrete instead of continuous as in IRT. From this perspective, cognitive diagnosis bears a close resemblance to searching problems in computer science and, similarly, item selection problem in cognitive diagnostic computerized adaptive testing (CD-CAT) can be considered as a dynamic searching problem. Previously, item selection algorithms in CD-CAT were developed from information indices in information science and attempted to achieve a balance among several objectives by assigning different weights. As a result, they suffered from low efficiency from a tug-of-war competition among multiple goals in item selection and, at the same time, put an undue responsibility of assigning the weights for these goals by trial and error on users. Based on the searching problem perspective on CD-CAT, this article adapts the binary searching algorithm, one of the most well-known searching algorithms in searching problems, to item selection in CD-CAT. The two new methods, the stratified dynamic binary searching (SDBS) algorithm for fixed-length CD-CAT and the dynamic binary searching (DBS) algorithm for variable-length CD-CAT, can achieve multiple goals without any of the aforementioned issues. The simulation studies indicate their performances are comparable or superior to the previous methods.
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Fang, Yujie, Ting Kang, Yang Yang, Yonghong Zi, and Xiong Lu. "Dark-Lumen Magnetic Resonance Image Based on Artificial Intelligence Algorithm in Differential Diagnosis of Colon Cancer." Computational Intelligence and Neuroscience 2022 (March 27, 2022): 1–8. http://dx.doi.org/10.1155/2022/4217573.

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This research was aimed o investigate the application value and diagnostic effect of dark-lumen magnetic resonance imaging (dark-lumen MRI) based on artificial intelligence algorithm on colon cancer. A total of 98 patients with ulcerated colon cancer were selected as the study subjects. All patients underwent colonic endoscopy. The patients were divided into algorithm group (artificial intelligence algorithm processing image group) and control group (conventional method processing image group) according to different dark-lumen MRI processing methods. The detection efficiency of colon cancer was compared between the two groups. It showed that the diagnostic effect of dark-lumen MRI based on artificial intelligence algorithm was significant. The apparent diffusion coefficient (ADC) in the control group was 0.92 ± 0.14 mm2/s (minimum: 0.74, maximum: 1.30), ADC in the algorithm group was 1.55 ± 0.31 mm2/s (minimum: 1.22, maximum: 2.42). The ADC of patients in algorithm group was significantly higher than that of patients in control group, with statistical difference (t = 7.827, P < 0.001). The correct number of cases was 46 and the diagnostic error number was 3 in algorithm group, with accuracy of 93%. The correct number of cases was 41 and the diagnostic error number was 8 in control group, with accuracy of 83%. In comparison, the correct rate was 10% higher in algorithm group, indicating that the diagnostic effect was better in algorithm group. The mean value of invasion depth was 10.42 in the algorithm group and 5.27 in the control group, indicating that the algorithm group was more accurate in the judgment of invasion depth, had a good prospect of clinical application, and had guiding significance for the diagnosis of colon cancer.
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Sasayama, Takashi, Kazuhiro Tanaka, Masahiro Maeyama, Satoshi Nakamizo, Hirotomo Tanaka, Masamitsu Nishihara, Takanori Hirose, Yuichi Fujita, and Eiji Kohmura. "PATH-44. MULTIPLE BIOMARKER ALGORITHM BASED ON CXCL13, IL-10, IL-2 RECEPTOR, AND β2-MICROGLOBULIN IN CEREBROSPINAL FLUID TO DIAGNOSE CENTRAL NERVOUS SYSTEM LYMPHOMA." Neuro-Oncology 21, Supplement_6 (November 2019): vi153. http://dx.doi.org/10.1093/neuonc/noz175.640.

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Abstract BACKGROUND Brain biopsy is the gold standard for the diagnosis of primary central nervous system lymphoma (PCNSL). However, the biopsy procedure has a risk of complications, such as hemorrhage and seizure. We have reported that cerebrospinal fluid (CSF) interleukin-10 (IL-10), soluble IL-2 receptor (sIL-2R), and β2-microglobulin (β2-MG) are the useful diagnostic biomarkers for PCNSL. Recently, the C-X-C motif chemokine ligand 13 (CXCL13) has been reported to be another useful biomarker for the PCNSL. The aim of this study was to validate the diagnostic performance of the CSF CXCL13 and diagnostic algorithm based on the combination of these biomarkers. METHODS We retrospectively examined the CSF CXCL13 concentration, as well as IL-10, sIL-2R, and β2-MG, in a case-control study (n=230). We used logistic regression analyses to create diagnostic algorithms based on these CSF biomarkers. To examine the utility of the multivariate diagnostic algorithm, we conducted the prospective study and evaluated the accuracy of this algorithm. RESULTS In case-control study, we have demonstrated that CSF CXCL13 levels were significantly higher in the patients with PCNSL (area under the curve (AUC)=0.981). A total of 84 patients were enrolled in the prospective study. The multivariate diagnostic algorithm using CSF levels of CXCL13, IL-10, sIL-2R, and β2-MG demonstrated excellent diagnostic performance: positive predictive value was 89% and negative predictive value was 100%. Four markers’ combination (CXCL13 + IL-10 + β2-MG + sIL-2R) had the highest AUC (AUC=0.998). The misdiagnosis cases of the algorithm were only 3 cases; CNS Sjögren’s syndrome, histiocytic sarcoma, and glioblastoma. In addition, CSF CXCL13 levels were prognostic biomarkers in PCNSL patients. CONCLUSIONS Our study suggests that the algorithm based on 4 CSF biomarkers had excellent diagnostic performance in CNS lymphoma. However, this algorithm should be further validated in prospective cohort studies with larger numbers of patients.
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Matveev, Stanislav A., Evgeny B. Korotkov, Yuri A. Zhukov, Nikita S. Slobodzian, Mikhail I. Nadezhin, Andrei V. Gorbunov, and Leonid T. Tanklevskiy. "Diagnostic and Monitoring System for Technical Condition of Electromechanical Section of Thermal Control Systems in Spacecraft." International Journal of Mathematical, Engineering and Management Sciences 5, no. 1 (November 1, 2019): 181–92. http://dx.doi.org/10.33889/ijmems.2020.5.1.015.

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Modern diagnostics methods ensuring the safety of production and operation, as well as the improvement of functional characteristics of electromechanical systems’ are discussed, method of diagnostics according to the spectrum and hodograph of the engine’s equivalent current is presented. Functional concept is presented for the system of control, diagnostic and monitoring of technical condition of thermal control systems’ electromechanical part in the spacecraft. The decision-making and forecasting algorithm for the operational resource is based on ground-based studies and diagnostic results. This approach to device diagnostics and monitoring is also used in other servo drives, mechatronic and robotic systems of space vehicles and other objects that are inaccessible and left unattended. Hardware-algorithmic implementation of the system is described, recommendations on the components base selection are given.
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Li, Yi-Guang. "Diagnostics of power setting sensor fault of gas turbine engines using genetic algorithm." Aeronautical Journal 121, no. 1242 (July 3, 2017): 1109–30. http://dx.doi.org/10.1017/aer.2017.49.

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ABSTRACTGas path diagnostics is one of the most effective condition monitoring techniques in supporting condition-based maintenance of gas turbines and improving availability and reducing maintenance costs of the engines. The techniques can be applied to the health monitoring of different gas path components and also gas path measurement sensors. One of the most important measurement sensors is that for the engine control, also called the power setting sensor, which is used by the engine control system to control the operation of gas turbine engines. In most of the published research so far, it is rarely mentioned that faults in such sensors have been tackled in either engine control or condition monitoring. The reality is that if such a sensor degrades and has a noticeable bias, it will result in a shift in engine operating condition and misleading diagnostic results.In this paper, the phenomenon of a power-setting sensor fault has been discussed and a gas path diagnostic method based on a Genetic Algorithm (GA) has been proposed for the detection of power-setting sensor fault with and without the existence of engine component degradation and other gas path sensor faults. The developed method has been applied to the diagnostic analysis of a model aero turbofan engine in several case studies. The results show that the GA-based diagnostic method is able to detect and quantify the power-setting sensor fault effectively with the existence of single engine component degradation and single gas path sensor fault. An exceptional situation is that the power-setting sensor fault may not be distinguished from a component fault if both faults have the same fault signature. In addition, the measurement noise has small impact on prediction accuracy. As the GA-based method is computationally slow, it is only recommended for off-line applications. The introduced GA-based diagnostic method is generic so it can be applied to different gas turbine engines.
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Zinko, Roman, Oleh Polishchuk, and Ewa Kuliś. "Vehicle diagnostic system of the car engine." MATEC Web of Conferences 351 (2021): 01014. http://dx.doi.org/10.1051/matecconf/202135101014.

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Support of the established technical characteristics of engines is reached by its regular service and diagnostics in particular - existence of the diagnostic programs built in the onboard computer of the car which carry out constant control of the main parameters of the engine.Based on the algorithm of vibroacoustic diagnostics, a system of vibration and vibroacoustic diagnostics of the internal combustion engine (ICE) is proposed, which can be integrated into the intelligent environment of self - diagnostics of the car (Check - Engine). The algorithm takes into account the normalized parameters and criteria for assessing the vibration state: the absolute values of displacements, velocities and accelerations and their changes.For the self-diagnostic system, it is important to develop a classifier of engine states also to determine and / or predict the failure of its parts or units. Engine vibrations can be attributed to the following types: imbalance of the 1st and 2nd order of the engine; vibration associated with combustion in the engine; auxiliary units.The analysis of a vibroacoustic signal at work of the serviceable and faulty engine is carried out, influence of various elements of a design, placement of the gauge in horizontal and vertical directions is shown on it.
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Jankowska, Kamila, and Mateusz Dybkowski. "A Current Sensor Fault Tolerant Control Strategy for PMSM Drive Systems Based on Cri Markers." Energies 14, no. 12 (June 10, 2021): 3443. http://dx.doi.org/10.3390/en14123443.

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The paper describes a vector-controlled fault tolerant control (FTC) structure for permanent magnet synchronous motor (PMSM) drives. As a control algorithm, the classical field oriented control was applied. For the proper operation of this drive, minimum two current sensors are necessary, however, in the FTC drives additional redundant transducers are applied. Each measuring sensor, including current sensors, are susceptible to damage and can lead to unstable operation of the drive. The presented control structure, with a diagnostic and compensation system, is robust to the typical current sensor faults—lack of signal, intermittent signal, variable gain, signal noise and signal saturation. The fault detection algorithm is based on the signal method. The fault diagnostic system is tested in two control algorithms—the scalar control and vector control ones—to demonstrate the transient of the faulted signals, detection signals and detection time. After current sensor fault appearance, its influence on the control structure, especially speed transient, is compensated using non-sensitive components. The analysis is presented for all the abovementioned faults for different speed conditions.
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Budanova, M. A., M. P. Chmelevsky, T. V. Treshkur, A. V. Aseev, and V. M. Tikhonenko. "Automatic detection of ventricular and supraventricular wide QRS arrhythmias using complex of morphological criteria and algorithms." Kardiologiia 59, no. 3S (April 13, 2019): 36–42. http://dx.doi.org/10.18087/cardio.2659.

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Aim. The aim of study is a detection of ventricular and supraventricular wide QRS arrhythmias using complex of morphological criteria and algorithms by method of automatic analysis. Materials and methods. For 100 patients (m/f – 61/39, Me (min; max) – 44.5 (10; 85) years) of researched group the analysis of 14306 single wide ectopic complexes (QRS 120–230 ms) has been done. Wide complexes include 11028 (77%) ventricular complexes and 3278 (23%) supraventricular complexes represented by 145 different forms of QRS. For verification of arrhythmias origin transesophageal ECG recording and endocardial electrophysiological study were done. The control group included 59 patients (m/f – 25/34, Me (min; max) – 49.5 (14,85) years) with 720 wide QRS, including 467 (65%) ventricular and 253 (35%) supraventricular complexes represented by 86 forms of QRS. The criteria Drew B.J., Scheinman M.M. (1995); Wellens H.J. (1978), RWPT II (Pava LF, 2010) and the algorithms of Brugada P. (1991); Bayesian (2000); Vereckei A. (2008) were used to evaluate sensitivity, specificity and diagnostic accuracy of wide QRS complexes recognition one by one and together, using the method of Wald sequential automatic analysis (KT Result3, CJSC INCART, Russia) and method of artificial neural networks. Results. The best results for the detection of ventricular arrhythmias algorithms were demonstrated by the Brugada P., Drew B.J., Scheinman M.M. algorithm (sensitivity 86.43%, specificity 66.73%, diagnostic accuracy 82.14% in the study group, sensitivity 81.80%, specificity 73.12%, diagnostic accuracy 78.75% in the control group), and the Bayesian algorithm (sensitivity 87.81%, specificity 73.62%, diagnostic accuracy 84.72% in the study group, sensitivity 83.30%, specificity 77.08%, diagnostic accuracy 81.11% in the control group). A complex analysis of the Wald method recognized ventricular arrhythmias in the research group with sensitivity 83.11%, specificity 83.65%, diagnostic accuracy 83.23% and in the control group with a sensitivity 83.51%, specificity of 84.58% and diagnostic accuracy 83.89%. Artificial neural networks recognized ventricular arrhythmias with sensitivity 91.43%, specificity 91.30% and diagnostic accuracy 91.39% in the control group and with sensitivity 97.06%, specificity 99.39% and diagnostic accuracy 97.6% in the research group. Conclusion. Automatic analysis allows obtaining simultaneously the results of each algorithms/criteria and in combination. It significantly reduces the doctor’s work in assessing of amplitude-time characteristics of the complexes. Using artificial neural networks increases the accuracy of of ventricular and supraventricular arrhythmias recognition.
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Dissertations / Theses on the topic "Control and diagnostic algorithm"

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Merheb, Abdel-Razzak. "Diagnostic and fault-tolerant control applied to an unmanned aerial vehicle." Thesis, Aix-Marseille, 2016. http://www.theses.fr/2016AIXM4367/document.

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Les travaux de recherches sur la commande, le diagnostic et la tolérance aux défauts appliqués aux drones deviennent de plus en plus populaires. Il est judicieux de concevoir des lois de commande qui garantissent la stabilité et les performances du drone, non seulement dans le cas nominal, mais également en présence de fortes perturbations et de défauts.Dans cette thèse, un nouvel algorithme bio-inspiré adapté pour la recherche de solutions dans des problèmes d’optimisation est développé. Cet algorithme est utilisé pour trouver les gains des différents contrôleurs conçus pour les drones. La commande par mode glissant est utilisée pour développer deux contrôleurs passifs tolérants aux défauts pour les quadrirotors: un contrôleur par mode glissant augmentée avec un intégrateur, et un contrôleur par mode glissant implémenté en cascade. Parce que les commandes passives ont une robustesse réduite, une commande active par mode glissant est développée. Pour traiter les défauts extrêmes, un contrôleur d’urgence basé sur la conversion du quadrirotor en trirotor est développé. Les commandes actives, passives, et le contrôleur d’urgences sont ensuite intégrés pour former un contrôleur tolérant aux défauts capable de gérer un grand nombre de défaillances tout en garantissant les ressources actionneur et en limitant la charge de calcul du processeur. Finalement, des contrôleurs tolérants aux défauts, actifs et passifs, basés sur des méthodes par mode glissant du premier et deuxième ordre sont développées pour les octorotors. La commande active utilise des méthodes d’allocation de contrôles pour redistribuer les efforts sur les actionneurs sains, réduisant ainsi l’effet du défaut
Unmanned Aerial Vehicles (UAV) are more and more popular for their civil and military applications. Classical control laws usually show weaknesses in the presence of parameter uncertainties, environmental disturbances, and actuator and sensor faults. Therefore, it is judicious to design a control law capable of stabilizing the UAV not only in the fault-free nominal cases, but also in the presence of disturbances and faults. In this thesis, a new bio-inspired search algorithm called Ecological Systems Algorithm (ESA) suitable for engineering optimization problems is developed. The algorithm is used over the thesis to find optimal gains for the fault tolerant controllers. Sliding Mode Control theory is used to develop two Passive Fault Tolerant Controllers for quadrotor UAVs: Regular and Cascaded SMC. Because Passive Controllers handle a few numbers of faults, an Active Sliding Mode Fault Tolerant Controller using Kalman Filter is developed. To overcome severe faults and failures, an emergency controller based on the Quadrotor-to-Trirotor conversion maneuver is developed. The Controllers developed so far (Passive, Active, and emergency controllers) are then integrated to form the Integrated Fault Tolerant Controller (IFTC). The IFTC is a powerful controller that is able to handle a wide number of faults, and save actuator resources as well as processor computational effort. Finally, Passive and Active Fault Tolerant Controllers are designed for octorotor UAVs based on First Order and Second Order Sliding Mode Control. The AFTC uses Dynamic and Pseudo-Inverse Control Allocation methods to redistribute the control effort among healthy actuators reducing the effect of fault
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Kadir, Abdul. "Embedded control and diagnostics algorithm with fault prediction and analysis of AC induction machines." Thesis, University of Hertfordshire, 2006. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.427545.

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Soman, Ruturaj. "Research and development of diagnostic algorithms to support fault accommodating control for emerging shipboard power system architectures." Thesis, University of Strathclyde, 2013. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=24389.

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The U.S. Navy has proposed development of next generation warships utilising an increased amount of power electronics devices to improve flexibility and controllability. The high power density finite inertia network is envisioned to employ automated fault detection and diagnosis to aid timely remedial action. Integration of condition monitoring and fault diagnosis to form an intelligent power distribution system is anticipated to assist decision support for crew while enhancing security and mission availability. This broad research being in the conceptual stage has lack of benchmark systems to learn from. Thorough studies are required to successfully enable realising benefits offered by using increased power electronics and automation. Application of fundamental analysis techniques is necessary to meticulously understand dynamics of a novel system and familiarisation with associated risks and their effects. Additionally, it is vital to find ways of mitigating effects of identified risks. This thesis details the developing of a generalised methodology to help focus research into artificial intelligence (AI) based diagnostic techniques. Failure Mode and Effects Analysis (FMEA) is used in identifying critical parts of the architecture. Sneak Circuit Analysis (SCA) is modified to provide signals that differentiate faults at a component level of a dc-dc step down converter. These reliability analysis techniques combined with an appropriate AI-algorithm offer a potentially robust approach that can potentially be utilised for diagnosing faults within power electronic equipment anticipated to be used onboard the novel SPS. The proposed systematic methodology could be extended to other types of power electronic converters, as well as distinguishing subsystem level faults. The combination of FMEA, SCA with AI could also be used for providing enhanced decision support. This forms part of future research in this specific arena demonstrating the positives brought about by combining reliability analyses techniques with AI for next generation naval SPS.
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Maamouri, Rebah. "Diagnostic et commande tolérante aux défauts appliqués à un système de conversion électromécanique à base d’une machine asynchrone triphasée." Thesis, Ecole centrale de Marseille, 2017. http://www.theses.fr/2017ECDM0009/document.

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L’objectif de cette thèse est de proposer des stratégies de diagnostic dans le cas d'une commande en vitesse sans capteur mécanique (vitesse/position) d’une machine asynchrone triphasée en présence de défaut d'ouverture des transistors IGBT (Insulated Gate Bipolar Transistor) de l’onduleur. Une étude de l’impact de ces défauts sur les performances de ces structures sans capteur mécanique en termes de stabilité et de robustesse des observateurs en mode dégradé est présentée. Un observateur par mode glissant (Sliding Mode Observer) à base de modèle est développé et validé expérimentalement en vue de la commande sans capteur mécanique de la machine asynchrone triphasée. Les signaux issus de l’observateur (approche modèle) sont utilisés conjointement avec ceux mesurés (approche signale) pour former une approche hybride de diagnostic de défauts des transistors IGBT de l’onduleur. Un observateur par mode glissant d’ordre 2 à base d’un algorithme Super-Twisting est ensuite développé en vue d’améliorer la stabilité et d’assurer la continuité de fonctionnement du système en présence d'un défaut afin de pouvoir appliquer une stratégie de commande tolérante aux défauts dans les meilleures délais et conditions de fonctionnement
The main goal of this thesis is to propose diagnostic strategies in the case of a sensorless speed control of a three-phase induction motor under an opened-switch or opened-phase fault. A qualitative analysis of the performances, in terms of stability and robustness, of sensorless control applied to the electrical drive in pre-fault and post-fault operation modes is presented. A model-based sliding mode observer is developed and experimentally validated for sensorless speed control of three-phase induction motor. The signals issued from the observer (model approach) as well as the measured ones (signal approach) are simultaneously used to form a hybrid approach for inverter open-switch fault detection and identification. A second-order sliding mode observer based on Super-Twisting algorithm (STA) is also developed to improve the stability and to ensure the continuity of operation of the electrical drive especially during transient states induced by the fault, permitting thus to apply the reconfiguration step without losing the control
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Maquin, Didier. "Observabilité, diagnostic et validation de données des procédés industriels." Nancy 1, 1987. http://www.theses.fr/1987NAN10347.

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Présentation d'un logiciel de validation de données des systèmes décrits par des modèles structurellement exacts et représentés par des équations linéaires ou bilinéaires, grâce à l'équilibrage de bilan de ces systèmes dans le cas où ceux-ci sont complètement mesurés, un algorithme d'estimation permet de les résoudre
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Saied, Majd. "Fault-tolerant control of an octorotor unmanned aerial vehicle under actuators failures." Thesis, Compiègne, 2016. http://www.theses.fr/2016COMP2287.

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La sûreté de fonctionnement est devenue indispensable pour tous les systèmes critiques où des vies humaines sont en jeu (comme l’aéronautique, le ferroviaire, etc.). Ceci a conduit à la conception et au développement des architectures tolérantes aux fautes, l’objectif de ces architectures étant de maintenir un service correct délivré par le système malgré la présence de fautes, et en particulier de garantir la sécurité-innocuité et la fiabilité du système. La tolérance aux fautes sur les drones aériens multirotors a récemment reçu une attention importante de la part de la communauté scientifique. En particulier, plusieurs travaux ont été développés sur la tolérance aux fautes des quadrirotors suite à des fautes partielles sur les actionneurs, et récemment des recherches ont abordé le problème de panne totale de l’un des actionneurs. D’après ces études, il a été montré qu’une défaillance totale d’un actionneur dans un quadrirotor rend le système non complètement contrôlable. Une solution proposée est de considérer des multirotors avec des actionneurs redondants (hexarotors ou octorotors). La redondance inhérente disponible dans ces véhicules est exploitée, en cas de défaillance sur les actionneurs, pour redistribuer les efforts de commande sur les moteurs sains de façon à garantir la stabilité et la contrôlabilité complète du système. Dans ce travail de thèse, des approches pour la conception de systèmes de commande tolérants aux fautes des drones multirotors sont étudiées et appliquées au contrôle des octorotors. Toutefois, les algorithmes sont conçus de manière à être applicables sur les autres types de multirotors avec des modifications mineures. D’abord, une analyse de contrôlabilité de l’octorotor après l’occurrence de défaillances sur les actionneurs est présentée. Ensuite, un module de détection et d’isolation de pannes moteurs basé sur un observateur non-linéaire et les mesures de la centrale inertielle est proposé. Les mesures des vitesses et des courants de moteurs fournis par les contrôleurs de vitesse sont également utilisées dans un autre algorithme de détection pour détecter les défaillances des actionneurs et distinguer les pannes moteurs des pertes des hélices. Un module de rétablissement basé sur la reconfiguration du multiplexage est proposé pour redistribuer les efforts de commande d’une manière optimale sur les actionneurs sains après l’occurrence de défaillances dans le système. Une architecture complète, comprenant la détection et l’isolation des défauts suivie par le rétablissement du système est validée expérimentalement sur un octorotor coaxial puis elle est comparée à d’autres architectures basées sur l’allocation de commande et la tolérance aux fautes passive par mode glissant
With growing demands for safety and reliability, and an increasing awareness about the risks associated with system malfunction, dependability has become an essential concern in modern technological systems, particularly safety-critical systems such as aircrafts or railway systems. This has led to the design and development of fault tolerant control systems (FTC). The main objective of a FTC architecture is to maintain the desirable performance of the system in the event of faults and to prevent local faults from causing failures. The last years witnessed many developments in the area of fault detection and diagnosis and fault tolerant control for Unmanned Aerial rotary-wing Vehicles. In particular, there has been extensive work on stability improvements for quadrotors in case of partial failures, and recently, some works addressed the problem of a quadrotor complete propeller failure. However, these studies demonstrated that a complete loss of a quadrotor motor results in a vehicle that is not fully controllable. An alternative is then to consider multirotors with redundant actuators (octorotors or hexarotors). Inherent redundancy available in these vehicles can be exploited, in the event of an actuator failure, to redistribute the control effort among the remaining working actuators such that stability and complete controllability are retained. In this thesis, fault-tolerant control approaches for rotary-wing UAVs are investigated. The work focuses on developing algorithms for a coaxial octorotor UAV. However, these algorithms are designed to be applicable to any redundant multirotor under minor modifications. A nonlinear model-based fault detection and isolation system for motors failures is constructed based on a nonlinear observer and on the outputs of the inertial measurement unit. Motors speeds and currents given by the electronic speed controllers are also used in another fault detection and isolation module to detect actuators failures and distinguish between motors failures and propellers damage. An offline rule-based reconfigurable control mixing is designed in order to redistribute the control effort on the healthy actuators in case of one or more motors failures. A complete architecture including fault detection and isolation followed by system recovery is tested experimentally on a coaxial octorotor and compared to other architectures based on pseudo-inverse control allocation and a robust controller using second order sliding mode
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McGraw, Philip E. "The oscillogenic control algorithm." Thesis, Virginia Tech, 1987. http://hdl.handle.net/10919/45770.

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An electronic-hardware-based oscillogenic controller previously developed by P. K. Mercure was used as a model for translation into a software-based control algoritnm. The oscillogenic instrument, invented by P. R. Rony and P. K. Mercure, uses a feedback element (the oscillogenic controller) and a sensor component to produces a periodic signal yielding information about the instrument's sensor component. A control program that utilized the oscillogenic control algorithm was written in the Turbo Pascal programming language. An IBM PC with 640 kilobytes of read/write memory and with analog-to-digital and digital-to-analog converter boards running the control program performed as the controller component of an oscillogenic instrument. A sample time of 0.5 seconds was used for this study. The instrument's sensor component consisted of a forced air thermal system with air flow rates ranging from 8.4 to 3l kg/hr. The oscillogenic instrument's frequency was, over the limited range tested (0.032 to 0.062 hz), a linear indication of the thermal system's convective heat transfer coefficient, which varied from 230 to 400 W/m2-°C.
Master of Science

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Millar, Alexander Paul. "Plasma diagnostic signal analysis : a Bayesian based genetic algorithm approach." Thesis, University of Glasgow, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326472.

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Kassapakis, E. G. "Studies on a predictive control algorithm." Thesis, University of Reading, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360726.

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Otava, Lukáš. "Algoritmy monitorování a diagnostiky pohonů se synchronními motory." Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-447552.

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Permanent magnet synchronous machine drives are used more often. Although, synchronous machines drive also suffer from possible faults. This thesis is focused on the detection of the three-phase synchronous motor winding faults and the detection of the drive control loop sensors' faults. Firstly, a model of the faulty winding of the motor is presented. Effects of the inter-turn short fault were analyzed. The model was experimentally verified by fault emulation on the test bench with an industrial synchronous motor. Inter-turn short fault detection algorithms are summarized. Three existing conventional winding fault methods based on signal processing of the stator voltage and stator current residuals were verified. Three new winding fault detection methods were developed by the author. These methods use a modified motor model and the extended Kalman filter state estimator. Practical implementation of the algorithms on a microcontroller is described and experimental results show the performance of the presented algorithms in different scenarios on test bench measurements. Highly related motor control loop sensors fault detection algorithms are also described. These algorithms are complementary to winding fault algorithms. The decision mechanism integrates outputs of sensor and winding fault detection algorithms and provides an overall drive fault diagnosis concept.
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Books on the topic "Control and diagnostic algorithm"

1

Soufian, M. Advanced control algorithm for process control unit. Manchester: UMIST, 1994.

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Ding, Steven X. Model-based fault diagnosis techniques: Design schemes, algorithms, and tools. Berlin: Springer, 2008.

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Chun, Thomas Yong Lee. Diagnostic supervisory control a DES approach. Ottawa: National Library of Canada, 1996.

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Soufian, Mustapha. A multivariable model predictive control algorithm with constraints. Manchester: University of Manchester, 1995.

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Ding, Steven X. Model-Based Fault Diagnosis Techniques: Design Schemes, Algorithms and Tools. 2nd ed. London: Springer London, 2013.

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Zhang, Zhonghua. Smart TCT: An efficient algorithm for supervisory control design. Ottawa: National Library of Canada, 2001.

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Stanton, Michael B. An algorithm for control volume analysis of cryogenic systems. Springfield, Va: Available from the National Technical Information Service, 1989.

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Edwards, Eric Charles. An algorithm for autonomous flight control of unmanned stationkeeping aircraft. [Downsview, Ont.]: Department of Aerospace Science and Engineering, University of Toronto, 1990.

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Palm, William J. A control-configured end effector for a visual servoing algorithm. Kingston, R.I: Dept. of Mechanical Engineering, the University of Rhode Island, 1985.

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Edwards, Eric Charles. An algorithm for autonomous flight control of unmanned stationkeeping aircraft. Ottawa: National Library of Canada = Bibliothèque nationale du Canada, 1992.

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Book chapters on the topic "Control and diagnostic algorithm"

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Ziarko, Wojciech, and Jack David Katzberg. "Control Algorithm Acquisition, Analysis and Reduction: A Machine Learning Approach." In Knowledge-Based System Diagnosis, Supervision, and Control, 167–80. Boston, MA: Springer US, 1989. http://dx.doi.org/10.1007/978-1-4899-2471-1_10.

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Ortega, F., J. B. Ordieres, C. Menéndez, and C. González Nicieza. "Development of a Neural-based Diagnostic System to Control the Ropes of Mining Shifts." In Artificial Neural Nets and Genetic Algorithms, 108–11. Vienna: Springer Vienna, 1995. http://dx.doi.org/10.1007/978-3-7091-7535-4_30.

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Favre, Cédric, Hagen Völzer, and Peter Müller. "Diagnostic Information for Control-Flow Analysis of Workflow Graphs (a.k.a. Free-Choice Workflow Nets)." In Tools and Algorithms for the Construction and Analysis of Systems, 463–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2016. http://dx.doi.org/10.1007/978-3-662-49674-9_27.

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Pustokhin, Denis A., Irina V. Pustokhina, M. Ilayaraja, and K. Shankar. "Fuzzy with Gravitational Search Algorithm Tuned Radial Basis Function Network for Medical Disease Diagnosis and Classification Model." In Soft Computing for Data Analytics, Classification Model, and Control, 41–55. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-030-92026-5_3.

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Diedrich, Alexander, Kaja Balzereit, and Oliver Niggemann. "First Approaches to Automatically Diagnose and Reconfigure Hybrid Cyber-Physical Systems." In Machine Learning for Cyber Physical Systems, 113–22. Berlin, Heidelberg: Springer Berlin Heidelberg, 2020. http://dx.doi.org/10.1007/978-3-662-62746-4_12.

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AbstractMaintaining modern production machinery requires a significant amount of time and money. Still, plants suffer from expensive production stops and downtime due to faults within individual components. Often, plants are too complex and generate too much data to make manual analysis and diagnosis feasible. Instead, faults often occur unnoticed, resulting in a production stop. It is then the task of highly-skilled engineers to recognise and analyse symptoms and devise a diagnosis. Modern algorithms are more effective and help to detect and isolate faults faster and more precise, thus leading to increased plant availability and lower operating costs.In this paper we attempt to solve some of the described challenges. We describe a concept for an automated framework for hybrid cyberphysical production systems performing two distinct tasks: 1) fault diagnosis and 2) reconfiguration. For diagnosis, the inputs are connection and behaviour models of the components contained within the system and a model describing their causal dependencies. From this information the framework is able to automatically derive a diagnosis provided a set of known symptoms. Taking the output of the diagnosis as a foundation, the reconfiguration part generates a new configuration, which, if applicable, automatically recovers the plant from its faulty state and resumes production. The described concept is based on predicate logic, specifically Satisfiability-Modulo-Theory. The input models are transformed into logical predicates. These predicates are the input to an implementation of Reiter’s diagnosis algorithm, which identifies the minimum-cardinality diagnosis. Taking this diagnosis, a reconfiguration algorithm determines a possible, alternative control, if existing. Therefore the current system structure described by the connection and component models is analysed and alternative production plans are searched. If such an alternative plan exists, it is transmitted to the control of the system. Otherwise, an error that the system is not reconfigurable is returned.
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Postacchini, F., and G. Trasimeni. "Diagnostic Algorithm." In Lumbar Disc Herniation, 333–40. Vienna: Springer Vienna, 1999. http://dx.doi.org/10.1007/978-3-7091-6430-3_13.

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Noebauer-Huhmann, Iris M., Joannis Panotopoulos, and Rainer I. Kotz. "Imaging Algorithm in the Diagnosis, Therapy Control and Follow-up of Musculo-Skeletal Tumours and Metastases." In European Surgical Orthopaedics and Traumatology, 3977–94. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-34746-7_188.

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Wang, Jing, Jinglin Zhou, and Xiaolu Chen. "Simulation Platform for Fault Diagnosis." In Intelligent Control and Learning Systems, 45–58. Singapore: Springer Singapore, 2022. http://dx.doi.org/10.1007/978-981-16-8044-1_4.

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AbstractThe previous chapters have described the mathematical principles and algorithms of multivariate statistical methods, as well as the monitoring processes when used for fault diagnosis. In order to validate the effectiveness of data-driven multivariate statistical analysis methods in the field of fault diagnosis, it is necessary to conduct the corresponding fault monitoring experiments. Therefore this chapter introduces two kinds of simulation platform, Tennessee Eastman (TE) process simulation system and fed-batch Penicillin Fermentation Process simulation system. They are widely used as test platforms for the process monitoring, fault classification, and identification of industrial process. The related experiments based on PCA, CCA, PLS, and FDA are completed on the TE simulation platforms.
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Cholewa, Wojciech, Józef Korbicz, Jan Maciej Kościelny, Krzysztof Patan, Tomasz Rogala, Michał Syfert, and Marcin Witczak. "Diagnostic Methods." In Modeling, Diagnostics and Process Control, 153–231. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16653-2_5.

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Frühwirth, Thom, and Slim Abdennadher. "Algorithm = Logic + Control." In Cognitive Technologies, 7–8. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-662-05138-2_2.

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Conference papers on the topic "Control and diagnostic algorithm"

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Xiong, Lu, Yingze Yang, Zhiwu Huang, and Liran Li. "A power bond graph based diagnostic algorithm for CCBII brake." In 2016 Chinese Control and Decision Conference (CCDC). IEEE, 2016. http://dx.doi.org/10.1109/ccdc.2016.7531489.

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Ding, Junhua, and M. N. H. Tabrizi. "Modeling and Model Checking of a Clinical Diagnostic Algorithm." In 2008 IEEE International Conference on Networking, Sensing and Control (ICNSC). IEEE, 2008. http://dx.doi.org/10.1109/icnsc.2008.4525187.

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Yuan, Zhenbing, Shuli Guo, and Lina Han. "Disease diagnostic prediction model based on improved hybrid CAPSO-BP algorithm." In 2017 36th Chinese Control Conference (CCC). IEEE, 2017. http://dx.doi.org/10.23919/chicc.2017.8027977.

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Wang, Jishuai, Qing Qian, Qiang Zhang, Lei Wang, Wenbo Cheng, and Xiaotian Ma. "Optimal Scheduling Algorithm based on Emergency Priority for In Vitro Diagnostic Devices." In 2020 IEEE 9th Data Driven Control and Learning Systems Conference (DDCLS). IEEE, 2020. http://dx.doi.org/10.1109/ddcls49620.2020.9275277.

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Sheard, J., J. Heberlein, K. Stelson, and E. Pfender. "Diagnostic Development for Control of Wire-Arc Spraying." In ITSC 1997, edited by C. C. Berndt. ASM International, 1997. http://dx.doi.org/10.31399/asm.cp.itsc1997p0613.

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Abstract This research has focused on characterization of the wire arc spray process with the goal of achieving improved process controls. Arc voltage and current traces have been analyzed on-line using an oscilloscope and a personal computer with LabView software. The characteristic features of the arc voltage fluctuations are correlated with the molten metal droplet formation process using a high speed Laser Strobe video system operating in synchronization with the oscilloscope trigger. Voltage minima occur when larger globules of molten metal leave the wire tip. Analysis of the voltage fluctuations indicate that they are neither random nor periodic, and that they can be described based on chaos theory. This approach may be used for achieving a further understanding of the dynamic nature of the process, and for the development of control algorithms.
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Xiao Li, Pu Yang, Jiangfan Ni, and Jing Zhao. "Fault diagnostic method for PV array based on improved wavelet neural network algorithm." In 2014 11th World Congress on Intelligent Control and Automation (WCICA). IEEE, 2014. http://dx.doi.org/10.1109/wcica.2014.7052884.

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Chao Wu, Eyad Abed, Gang Bai, Brian Beaudoin, Santiago Bernal, Irving Haber, Rami Kishek, et al. "A robust orbit-steering and control algorithm using quadrupole-scans as a diagnostic." In 2007 IEEE Particle Accelerator Conference (PAC). IEEE, 2007. http://dx.doi.org/10.1109/pac.2007.4440261.

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Noursadeghi, Elaheh, and Ioannis Raptis. "A Particle Filtering-Based Approach for Distributed Fault Diagnosis and Estimation of Multi-Robot Systems." In ASME 2016 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/dscc2016-9789.

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This paper deals with the problem of designing a distributed fault diagnosis and estimation algorithm for multi-robot systems that are subject to faults in the form of abrupt velocity biases. To solve this problem, the multi-robot collective is converted to a network of interconnected diagnostic nodes (DNs) that is deployed to monitor the health of the system. Each node consists of a reduced-order estimator with relative state measurements and an online parameter learning filter. The local estimator executes a distributed variation of the particle filtering algorithm using the local sensor measurements and the fault progression model of the robots. The parameter learning filter is used to obtain an approximation of the severity of faults. Numerical simulations demonstrate the efficiency of the proposed approach.
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Yu, Hongtao, and Reza Langari. "A Detection and Warning System for Unintended Acceleration." In ASME 2015 Dynamic Systems and Control Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/dscc2015-9715.

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This paper presents a data-driven method to detect vehicle problems related to unintended acceleration (UA). A diagnostic system is formulated by analyzing several specific vehicle events such as acceleration peaks and generating corresponding mathematical models. The diagnostic algorithm was implemented in the Simulink/dSpace environment for validation. Major factors that affect vehicles’ acceleration (e.g., changes of road grades and gear shifting) were included in the simulation. UA errors were added randomly when human drivers drove virtual cars. The simulation results show that the algorithm succeeds in detecting abnormal acceleration.
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"A Concept of the Real-time Diagnostic System for Prototype Engines - Architecture and Algorithm." In 10th International Conference on Informatics in Control, Automation and Robotics. SciTePress - Science and and Technology Publications, 2013. http://dx.doi.org/10.5220/0004426703600365.

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Reports on the topic "Control and diagnostic algorithm"

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Teytelman, Dmitry. Architectures and Algorithms for Control and Diagnostics of Coupled-Bunch Instabilities in Circular Accelerators. Office of Scientific and Technical Information (OSTI), July 2003. http://dx.doi.org/10.2172/815292.

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Shepherd, S. Jeff, Pei-Jan Paul Lin, John M. Boone, Dianna D. Cody, Jane R. Fisher, G. Donald Frey, Hy Glasser, et al. Quality Control in Diagnostic Radiology. AAPM, 2002. http://dx.doi.org/10.37206/73.

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Allen, Donald S., Yang-Woo Kim, and Meenakshi Pasupathy. Forecasting with an Adaptive Control Algorithm. Federal Reserve Bank of St. Louis, 1996. http://dx.doi.org/10.20955/wp.1996.009.

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Sadek, Fahim, and Bijan Mohraz. A modified optimal algorithm for active structural control. Gaithersburg, MD: National Institute of Standards and Technology, 1996. http://dx.doi.org/10.6028/nist.ir.5782.

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Seginer, Ido, Louis D. Albright, and Robert W. Langhans. On-line Fault Detection and Diagnosis for Greenhouse Environmental Control. United States Department of Agriculture, February 2001. http://dx.doi.org/10.32747/2001.7575271.bard.

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Background Early detection and identification of faulty greenhouse operation is essential, if losses are to be minimized by taking immediate corrective actions. Automatic detection and identification would also free the greenhouse manager to tend to his other business. Original objectives The general objective was to develop a method, or methods, for the detection, identification and accommodation of faults in the greenhouse. More specific objectives were as follows: 1. Develop accurate systems models, which will enable the detection of small deviations from normal behavior (of sensors, control, structure and crop). 2. Using these models, develop algorithms for an early detection of deviations from the normal. 3. Develop identifying procedures for the most important faults. 4. Develop accommodation procedures while awaiting a repair. The Technion team focused on the shoot environment and the Cornell University team focused on the root environment. Achievements Models: Accurate models were developed for both shoot and root environment in the greenhouse, utilizing neural networks, sometimes combined with robust physical models (hybrid models). Suitable adaptation methods were also successfully developed. The accuracy was sufficient to allow detection of frequently occurring sensor and equipment faults from common measurements. A large data base, covering a wide range of weather conditions, is required for best results. This data base can be created from in-situ routine measurements. Detection and isolation: A robust detection and isolation (formerly referred to as 'identification') method has been developed, which is capable of separating the effect of faults from model inaccuracies and disturbance effects. Sensor and equipment faults: Good detection capabilities have been demonstrated for sensor and equipment failures in both the shoot and root environment. Water stress detection: An excitation method of the shoot environment has been developed, which successfully detected water stress, as soon as the transpiration rate dropped from its normal level. Due to unavailability of suitable monitoring equipment for the root environment, crop faults could not be detected from measurements in the root zone. Dust: The effect of screen clogging by dust has been quantified. Implications Sensor and equipment fault detection and isolation is at a stage where it could be introduced into well equipped and maintained commercial greenhouses on a trial basis. Detection of crop problems requires further work. Dr. Peleg was primarily responsible for developing and implementing the innovative data analysis tools. The cooperation was particularly enhanced by Dr. Peleg's three summer sabbaticals at the ARS, Northem Plains Agricultural Research Laboratory, in Sidney, Montana. Switching from multi-band to hyperspectral remote sensing technology during the last 2 years of the project was advantageous by expanding the scope of detected plant growth attributes e.g. Yield, Leaf Nitrate, Biomass and Sugar Content of sugar beets. However, it disrupted the continuity of the project which was originally planned on a 2 year crop rotation cycle of sugar beets and multiple crops (com and wheat), as commonly planted in eastern Montana. Consequently, at the end of the second year we submitted a continuation BARD proposal which was turned down for funding. This severely hampered our ability to validate our findings as originally planned in a 4-year crop rotation cycle. Thankfully, BARD consented to our request for a one year extension of the project without additional funding. This enabled us to develop most of the methodology for implementing and running the hyperspectral remote sensing system and develop the new analytical tools for solving the non-repeatability problem and analyzing the huge hyperspectral image cube datasets. However, without validation of these tools over a ful14-year crop rotation cycle this project shall remain essentially unfinished. Should the findings of this report prompt the BARD management to encourage us to resubmit our continuation research proposal, we shall be happy to do so.
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Less, Brennan, Iain Walker, and Yihuan Tang. Development of an Outdoor Temperature Based Control Algorithm for Residential Mechanical Ventilation Control. Office of Scientific and Technical Information (OSTI), August 2014. http://dx.doi.org/10.2172/1220536.

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Less, Brennan, Iain Walker, and Yihuan Tang. Development of an Outdoor Temperature-Based Control Algorithm for Residential Mechanical Ventilation Control. Office of Scientific and Technical Information (OSTI), June 2014. http://dx.doi.org/10.2172/1171351.

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Theodosopoulos, T. V., M. S. Branicky, and M. M. Livstone. A Hierarchical Algorithm for Neural Training and Control. Revision. Fort Belvoir, VA: Defense Technical Information Center, October 1992. http://dx.doi.org/10.21236/ada459605.

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Wang, Yun, and Ben G. Fitzpatrick. Novel Algorithm/Hardware Partnerships for Real-Time Nonlinear Control. Fort Belvoir, VA: Defense Technical Information Center, February 2014. http://dx.doi.org/10.21236/ada598335.

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Young, Joseph G. A cooperative control algorithm for camera based observational systems. Office of Scientific and Technical Information (OSTI), January 2012. http://dx.doi.org/10.2172/1034889.

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