يعرض 1 - 20 نتائج من 92 نتيجة بحث عن '"Estimación de estados"', وقت الاستعلام: 0.85s تنقيح النتائج
  1. 1
    Dissertation/ Thesis
  2. 2
    Academic Journal
  3. 3
  4. 4
    Dissertation/ Thesis
  5. 5
    Dissertation/ Thesis
  6. 6
    Conference

    المساهمون: Universidad de Sevilla. Departamento de Lenguajes y Sistemas Informáticos

    Relation: Jornadas de Automática (2007).; DPI2006-15476-C02-01; DPI2007-66718-C04-01; http://intranet.ceautomatica.es/old/actividades/jornadasXXVIII.htm; https://idus.us.es/handle//11441/95932

  7. 7
    Academic Journal

    المساهمون: Rivadeneira Paz, Pablo Santiago, Gómez Pérez, Cesar Augusto

    وصف الملف: application/pdf

    Relation: Andersen, B. B., Nielsen, R. F., Udugama, I. A., Papadakis, E., Gernaey, K. V., Huusom, J. K., … Abildskov, J. (2018). Integrated Process Design and Control of Cyclic Distillation Columns. IFAC-PapersOnLine, 51(18), 542–547. https://doi.org/10.1016/J.IFACOL.2018.09.368; Aqar, D. Y., Rahmanian, N., & Mujtaba, I. M. (2017). Feasibility of integrated batch reactive distillation columns for the optimal synthesis of ethyl benzoate. Chemical Engineering and Processing: Process Intensification, 122, 10–20. https://doi.org/10.1016/J.CEP.2017.08.012; Birk, J., & Zeitz, M. (1988). Extended luenberger observer for non-linear rnultivariable systems. International Journal of Control, 47(6), 1823–1836. https://doi.org/10.1080/00207178808906138; Cameron, I., & Hangos, K. (2001). Process modelling and model analysis.; Diwekar, U. M., & Madhavan, K. P. (1991). Multicomponent batch distillation column design. Industrial & Engineering Chemistry Research, 30(4), 713–721. https://doi.org/10.1021/ie00052a014; Doran, P. (1995). Bioprocess engineering principles.; El-Maghlany, W. M., Hanafy, A. A., Hassan, A. A., & El-Magid, M. A. (2016). Experimental study of Cu–water nanofluid heat transfer and pressure drop in a horizontal double-tube heat exchanger. Experimental Thermal and Fluid Science, 78, 100–111. https://doi.org/https://doi.org/10.1016/j.expthermflusci.2016.05.015; Escobar, R. F., Juárez, D., Siqueiros, J., Irles, C., & Hernández, J. A. (2008). On-line COP estimation for waste energy recovery heat transformer by water purification process. Desalination, 222(1–3), 666–672. https://doi.org/10.1016/j.desal.2007.01.192; Felder, R. M., Rousseau, R. W., Bullard, L. G., & Eduardo Pizarro Borges, L. (2016). Princípios Elementares dos Processos Químicos 4 a edición.; Fernández Villaverde, A., & Rodríguez Banga, J. (n.d.). Análisis de observabilidad e identificabilidad estructural de modelos no lineales: aplicación a la vía de señalización JAK/STAT. Ruc.Udc.Es. https://doi.org/10.17979/spudc.9788497497169.631; Fully Integrated, Hall Effect-Based Linear Current Sensor with 2.1 kVRMS Voltage Isolation and a Low-Resistance Current Conductor ACS712. (n.d.). Retrieved from www.allegromicro.com; Green, D., & Perry, R. (1997). Perry’s Chemical Engineers’ Handbook/edición Don W. Green y Robert H. Perry. Retrieved from http://www.sidalc.net/cgi-bin/wxis.exe/?IsisScript=INDUSTRIAL.xis&method=post&formato=2&cantidad=1&expresion=mfn=002414; Güémez, J., Fiolhais, C., & Fiolhais, M. (2002). Revisiting Black’s experiments on the latent heats of water. The Physics Teacher, 40(1), 26–31. https://doi.org/10.1119/1.1457825; Hulhoven, X., Wouwer, A., Science, P. B.-C. engineering, & 2006, U. (n.d.). Hybrid extended Luenberger-asymptotic observer for bioprocess state estimation.; Kaewpradit, P., Kittisupakorn, P., Thitiyasook, P., & Mujtaba, I. M. (2008). Dynamic composition estimation for a ternary batch distillation. Chemical Engineering Science, 63, 3309–3318. https://doi.org/10.1016/j.ces.2008.03.033; Kamble, P., Khan, Z., Capper, S., Sharp, J., & Watson, I. (2017). Improving downdraft gasifier stability by robust instrumentation and control systems. In Energy Procedia (Vol. 142, pp. 2214–2217). Elsevier Ltd. https://doi.org/10.1016/j.egypro.2017.12.591; Kitil, A. O., & Kumar, M. (2018). An IoT-BasedRain Alerting and Flood Prediction using Sensors and Arduino for Smart Environment. International Journal of Pure and Applied Mathematics, 118(24).; Klingberg, A. (2000). Modelling and Opimisation of Batch Distillation.; Latha Chopparapu, S., George, V. I., Thirunavukkarasu, I., & Bhat, V. S. (2017). Design and Simulation of Kalman Filter for the Estimation of Tray Temperatures in a Binary Distillation Column. International Journal of Pure and Applied Mathematics, 114(9), 11–20. Retrieved from http://acadpubl.eu/jsi/2017-114-7-ICPCIT-2017/articles/9/2.pdf; Luenberger, D. G. (1964). Observing the state of a linear system. IEEE Transactions on Military Electronics, 8(2), 74–80.; Madabhushi, P. B., & Adams, T. A. (2018). Side stream control in semicontinuous distillation. Computers & Chemical Engineering, 119, 450–464. https://doi.org/10.1016/j.compchemeng.2018.09.002; Messaoudi, M., Sbita, L., & Abdelkrim, M. N. (2007). A robust nonlinear observer for states and parameters estimation and on-line adaptation of rotor time constant in sensorless induction motor drives. International Journal of Physical Sciences (Vol. 2).; Morales, R., Colombian, H. A.-2017 I. 3rd, & 2017, undefined. (n.d.). Operation feasible region for flash distillation control and design. Ieeexplore.Ieee.Org. Retrieved from https://ieeexplore.ieee.org/abstract/document/8276405/; Moran, M., Shapiro, H., Boettner, D., & Bailey, M. (2010). Fundamentals of engineering thermodynamics.; Ogata, K., & Yang, Y. (2010). Modern control engineering.; Perry, D., Porter, A., of, L. V.-P. of the conference on T. future, & 2000, undefined. (n.d.). Empirical studies of software engineering: a roadmap. Ufv.Br. Retrieved from ftp://ftp.ufv.br/dpi/mestrado/ExperimentalSWE/empiricalstudiesSWE-perry-ACMfutureofSWE-2000.pdf; Phimister, J. R., & Seider, W. D. (2000). Semicontinuous, middle-vessel distillation of ternary mixtures. AIChE Journal, 46(8), 1508–1520. https://doi.org/10.1002/aic.690460804; Quintero-Marmol, E., Luyben, W. L., & Georgakis, C. (1991). Application of an Extended Luenberger Observer to the Control of Multicomponent Batch Distillation. Industrial and Engineering Chemistry Research, 30(8), 1870–1880. https://doi.org/10.1021/ie00056a029; Rodriguez-Donis, I., Gerbaud, V., Lavoine, S., Meyer, M., Thiebaud-Roux, S., & Dupouyet, A. (2019). Modelling and experimental validation of dimethyl carbonate solvent recovery from an aroma mixture by batch distillation. Chemical Engineering Research and Design, 147, 1–17. https://doi.org/10.1016/j.cherd.2019.04.007; Safdarnejad, S. M., Gallacher, J. R., & Hedengren, J. D. (2016). Dynamic parameter estimation and optimization for batch distillation. Computers & Chemical Engineering, 86, 18–32. https://doi.org/10.1016/J.COMPCHEMENG.2015.12.001; Serway, R. (1992). Physics for Scientists and Engineers: With Modern Physics, Saunders Golden Sunburst Series.; Simon, D. (2006). Optimal state estimation: Kalman, H infinity, and nonlinear approaches.; Sukasem, N., Hareemao, T., & Sudawong, C. (2017). The mimic of fractional distillation technology for development of homegrown pot distillery for ethanol distillation. Energy Procedia, 138, 985–990. https://doi.org/10.1016/J.EGYPRO.2017.10.101; Tong, H., & Ng, M. (2018). Analysis of regularized least squares for functional linear regression model. Journal of Complexity, 49, 85–94. https://doi.org/10.1016/j.jco.2018.08.001; Tronci, S., Bezzo, F., Barolo, M., & Baratti, R. (2005). Geometric observer for a distillation column: Development and experimental testing. Industrial and Engineering Chemistry Research, 44(26), 9884–9893. https://doi.org/10.1021/ie048751n; Ulas, S., Diwekar, U. M., & Stadtherr, M. A. (2005). Uncertainties in parameter estimation and optimal control in batch distillation. Computers & Chemical Engineering, 29(8), 1805–1814. https://doi.org/10.1016/j.compchemeng.2005.03.002; Universidad Nacional de Colombia : Dirección de Laboratorios - DIRLAB - Laboratorio de Productos Naturales. (n.d.). Retrieved January 28, 2020, from http://direcciondelaboratorios.medellin.unal.edu.co/index.php/nuestros-laboratorios/facultad-de-ciencias/31; Welch, G., & Bishop, G. (1995). An Introduction to the Kalman Filter. Retrieved from http://www.cs.unc.edu/~gb; Zhao, X. F., Ba, Q., Li, L., Gong, P., & Ou, J. P. (2012). A three-index estimator based on active thermometry and a novel monitoring system of scour under submarine pipelines. Sensors and Actuators, A: Physical, 183, 115–122. https://doi.org/10.1016/j.sna.2012.05.039; https://repositorio.unal.edu.co/handle/unal/78521

  8. 8
    Academic Journal
  9. 9
    Dissertation/ Thesis

    المؤلفون: Garzón Hidalgo, Juan David

    المساهمون: Pérez González, Ernesto, Programa de Investigacion sobre Adquisicion y Analisis de Señales Paas-Un, orcid:0000-0003-1602-8780

    وصف الملف: 108 páginas; application/pdf

    Relation: LaReferencia; A. J. Wood, B. Wollenberg, and G. B. Sheblé, Power generation, operation, and control; A. Dubey, S. Chakrabarti, and V. Terzija, “SCADA and PMU Measurement Based Methods for Robust Hybrid State Estimation,” Electr. Power Components Syst., vol. 47, no. 9–10, pp. 849–860, 2019, doi:10.1080/15325008.2019.1627606; H. Wu and Giri, “PMU Impact on State Estimation Reliability for Improved Grid Security,” in 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition, 2006, pp. 1349–1351, doi:10.1109/TDC.2006.1668709; M. Rostami and S. Lotfifard, “Distributed dynamic state estimation of power systems,” IEEE Trans. Ind. Informatics, vol. 14, no. 8, pp. 3395–3404, 2018, doi:10.1109/TII.2017.2777495; Y. Sun, M. Fu, and H. Zhang, “Performance comparison of distributed state estimation algorithms for power systems,” J. Syst. Sci. Complex., vol. 30, no. 3, pp. 595–615, 2017, doi:10.1007/s11424-017-6062-3; J. Zhao et al., “Power System Dynamic State Estimation: Motivations, Definitions, Methodologies, and Future Work,” IEEE Trans. Power Syst., vol. 34, no. 4, pp. 3188–3198, 2019, doi:10.1109/TPWRS.2019.2894769; A. McMorran, “Common Information Model Primer, First Edition,” 2011.; K. Martin and C. Sun, “Synchro-Phasor Data Conditioning and Validation Project Phase 1 , Task 1 Report Review of existing infrastructure systems , administrative processes , and data validation schemes , methods and,” 2013; K. Martin and J. Mo, “Synchro-‐Phasor Data Conditioning and Validation Project Phase 1, Task 3 Report Algorithms and Methods for,” 2014.; K. Martin and C. Sun, “Synchro-Phasor Data Conditioning and Validation Project Phase 1 , Task 2 Report Best Practice Recommendations for Synchrophasor Systems : Administration , Planning and Implementation , and Operation and Maintenance,” 2013.; K. D. Jones, A. Pal, and J. S. Thorp, “Methodology for Performing Synchrophasor Data Conditioning and Validation,” IEEE Trans. Power Syst., vol. 30, no. 3, pp. 1121–1130, 2015, doi:10.1109/TPWRS.2014.2347047; M. Wu and L. Xie, “Online Detection of Low-Quality Synchrophasor Measurements: A Data-Driven Approach,” IEEE Trans. Power Syst., vol. 32, no. 4, pp. 2817–2827, 2017, doi:10.1109/TPWRS.2016.2633462; Y. Hao, M. Wang, J. H. Chow, E. Farantatos, and M. Patel, “Modelless data quality improvement of streaming synchrophasor measurements by exploiting the low-rank hankel structure,” IEEE Trans. Power Syst., vol. 33, no. 6, pp. 6966–6977, 2018, doi:10.1109/TPWRS.2018.2850708; Y. Wu, Y. Xiao, F. Hohn, L. Nordstrom, J. Wang, and W. Zhao, “Bad Data Detection Using Linear WLS and Sampled Values in Digital Substations,” IEEE Trans. Power Deliv., vol. 33, no. 1, pp. 150–157, 2018, doi:10.1109/TPWRD.2017.2669110; A. W. McMorran, “An Introduction to IEC 61970-301 & 61968-11 : The Common Information Model,” Power, vol. 1, no. January, pp. 1–42, 2007, [Online]. Available: http://scholar.google.com/scholar?hl=en&btnG=Search&q=intitle:An+Introduction+to+IEC+61970-301+&+61968-11+:+The+Common+Information+Model#0; A. W. McMorran, R. W. Lincoln, G. A. Taylor, and E. M. Stewart, “Addressing misconceptions about the Common Information Model (CIM),” IEEE Power Energy Soc. Gen. Meet., no. Cim, pp. 1–4, 2011, doi:10.1109/PES.2011.6039391; R. Khare, M. Khadem, S. Moorty, K. Methaprayoon, and J. Zhu, “Patterns and practices for CIM applications,” IEEE Power Energy Soc. Gen. Meet., pp. 1–8, 2011, doi:10.1109/PES.2011.6039268; K. D. Jones, V. A. Centeno, J. S. Thorp, and K. D. Jones, “Three-Phase Linear State Estimation with Phasor Measurements by,” 2011; R. Ebrahimian and R. Baldick, “State estimation distributed processing,” IEEE Trans. Power Syst., vol. 15, no. 4, pp. 1240–1246, 2000, doi:10.1109/59.898096; B. Ozsoy and M. Gol, “A Hybrid State Estimation Strategy with Optimal Use of Pseudo-Measurements,” Proc. - 2018 IEEE PES Innov. Smart Grid Technol. Conf. Eur. ISGT-Europe 2018, 2018, doi:10.1109/ISGTEurope.2018.8571513; B. Dönmez and A. Abur, “A Computationally Efficient Method to Place Critical Measurements,” Power, vol. 26, no. 2, pp. 924–931, 2011; https://repositorio.unal.edu.co/handle/unal/85433; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

  10. 10
    Academic Journal
  11. 11
    Academic Journal
  12. 12
  13. 13
    Academic Journal
  14. 14
  15. 15
    Dissertation/ Thesis

    المساهمون: Giraldo Trujillo, Luis Felipe, Zambrano Jacobo, Andrés Felipe, No aplica

    وصف الملف: 23 páginas; application/pdf

    Relation: Arturo S. Bretas, Newton G. Bretas, Joao B.A. London, Breno E.B. Carvalho, Cyber-Physical Power Systems State Estimation: Chapter 4 - Classical static state estimation in electric power systems, Elsevier, 2021.; A. Abur and A. G. Exposito, Power systems state estimation: theory and implementation, Marcel Dekker Publishers, Nova York, USA, 2004.; N. G. Bretas, S. A. Piereti, A. S. Bretas and A. C. P. Martins, A Geometrical View for Multiple Gross Errors Detection, Identification, and Correction in Power System State Estimation, in IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2128-2135, Aug. 2013.; F. C. Schweppe and E. J. Handschin, Static state estimation in electric power systems, in Proceedings of the IEEE, vol. 62, no. 7, pp. 972-982, July 1974.; Carvalho, Breno Bretas, Newton, Largest Normalized Residual Test Analysis for Measurements Gross Errors Processing in the WLS Estimator. Proceedings of the IASTED Asian Conference on Power and Energy Systems, AsiaPES 2012.; I. T. Jolliffe, Principal Component Analysis, Wiley Online Library, 2002.; Yao Liu, Peng Ning, and Michael K. Reiter. 2011. False data injection attacks against state estimation in electric power grids. ACM Trans. Inf. Syst. Secur. 14, 1, Article 13 (May 2011).; M. Esmalifalak, L. Liu, N. Nguyen, R. Zheng and Z. Han, "Detecting Stealthy False Data Injection Using Machine Learning in Smart Grid", in IEEE Systems Journal, vol. 11, no. 3, pp. 1644-1652, Sept. 2017.; P. Kundur, Power System Stability and control. McGraw Hill, 1994.; A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. JohnWiley and Sons, Inc., 2001; C. M. Bishop, Mixture Models and EM, in Patter Recognition and Machine Learning, Springer, 2006, pp. 423-439.; http://hdl.handle.net/1992/59283; instname:Universidad de los Andes; reponame:Repositorio Institucional Séneca; repourl:https://repositorio.uniandes.edu.co/

  16. 16
    Dissertation/ Thesis

    المساهمون: Giraldo Trujillo, Luis Felipe, Ramos López, Gustavo, Zambrano Jacobo, Andrés Felipe, No aplica

    وصف الملف: 27 páginas; application/pdf

    Relation: Arturo S. Bretas, Newton G. Bretas, Joao B.A. London, Breno E.B. Carvalho, Cyber- Physical Power Systems State Estimation: Chapter 4 - Classical static state estimation in electric power systems, Elsevier, 2021.; A. Abur and A. G. Exposito, Power systems state estimation: theory and implementation, Marcel Dekker Publishers, Nova York, USA, 2004.; N. G. Bretas, S. A. Piereti, A. S. Bretas and A. C. P. Martins, .A Geometrical View for Multiple Gross Errors Detection, Identification, and Correction in Power System State Estimation" ,in IEEE Transactions on Power Systems, vol. 28, no. 3, pp. 2128-2135, Aug. 2013.; F. C. Schweppe and E. J. Handschin, Static state estimation in electric power systems, in Proceedings of the IEEE, vol. 62, no. 7, pp. 972-982, July 1974.; Carvalho, Breno Bretas, Newton, Largest Normalized Residual Test Analysis for Measurements Gross Errors Processing in the WLS Estimator. Proceedings of the IASTED Asian Conference on Power and Energy Systems, AsiaPES 2012.; I. T. Jolliffe, Principal Component Analysis, Wiley Online Library, 2002.; Yao Liu, Peng Ning, and Michael K. Reiter. 2011. False data injection attacks against state estimation in electric power grids. ACM Trans. Inf. Syst. Secur. 14, 1, Article 13 (May 2011).; M. Esmalifalak, L. Liu, N. Nguyen, R. Zheng and Z. Han, "Detecting Stealthy False Data Injection Using Machine Learning in Smart Grid" ,in IEEE Systems Journal, vol. 11, no. 3, pp. 1644-1652, Sept. 2017.; P. Kundur, Power System Stability and control. McGraw Hill, 1994.; A. Hyvärinen, J. Karhunen, and E. Oja, Independent Component Analysis. JohnWiley and Sons, Inc., 2001; C. M. Bishop, Mixture Models and EM, in Patter Recognition and Machine Learning, Springer, 2006, pp. 423-439.; http://hdl.handle.net/1992/59275; instname:Universidad de los Andes; reponame:Repositorio Institucional Séneca; repourl:https://repositorio.uniandes.edu.co/

  17. 17
    Dissertation/ Thesis

    المؤلفون: Cortés Calle, Carlos César

    المساهمون: Botero Castro, Héctor Antonio

    وصف الملف: 98 páginas; application/pdf

    Relation: R. y. R. S. C. García Arbeláez, C.; Barrera, X.; Gómez, El ABC de los compromisos de Colombia para la COP21. 2015.; M. . L. . H. y. E. . M. . E. García Arbeláez, C ., G . Vallejo, El Acuerdo de París. Así actuará Colombia frente al cambio climático. 2016.; M. de minas y energía, Unidad de Planeación Minero Energética, and Universidad de Córdoba, “Incidencia real de la minería del carbón, del oro y del uso del mercurio en la calidad ambiental con énfasis especial en el recurso hídrico - diseño de herramientas para la planeación,” p. 663, 2015.; S. C. Chelgani, M. Parian, P. S. Parapari, Y. Ghorbani, and J. Rosenkranz, “A comparative study on the effects of dry and wetgrinding on mineral flotation separation-a review,” Journal of Materials Research and Technology, no. x x, pp. 1–8, 2019.; J. L. Salazar, H. Valdés-González, E. Vyhmesiter, and F. Cubillos, “Model predictive control of semiautogenous mills (sag),” Minerals Engineering, vol. 64, pp. 92–96, 2014.; A. Jankovic, S. Suthers, T. Wills, and W. Valery, “Evaluation of dry grinding using HPGR in closed circuit with an air classifier,” Minerals Engineering, vol. 71, pp. 133–138, 2015.; D. Sbarbaro, J. Barriga, H. Valenzuela, and G. Cortes, “A multi-input-single-output Smith predictor for feeders control in SAG grinding plants,” IEEE Transactions on Control Systems Technology, vol. 13, no. 6, pp. 1069–1075, 2005.; J. Yang, S. Li, X. Chen, and Q. Li, “Disturbance rejection of ball mill grinding circuits using DOB and MPC,” Powder Technology, vol. 198, no. 2, pp. 219–228, 2010.; L. C. Coetzee, I. K. Craig, and E. C. Kerrigan, “Robust nonlinear model predictive control of a run-of-mine ore milling circuit,” IEEE Transactions on Control Systems Technology, vol. 18, no. 1, pp. 222–229, 2010.; P. Karelovic, R. Razzetto, and A. Cipriano, Evaluation of MPC strategies for mineral grinding, vol. 15. IFAC, 2013.; J. D. le Roux, A. Steinboeck, A. Kugi, and I. K. Craig, “An EKF observer to estimate semi-autogenous grinding mill hold-ups,” Journal of Process Control, vol. 51, pp. 27–41, 2017.; F. Herrera, “Objetivos De Desarrollo Sostenible en Colombia: Los Retos para 2030,” Pnud, p. 74, 2018.; T. A. Apelt and N. F. Thornhill, “Inferential measurement of SAG mill parameters V: MPC simulation,” Minerals Engineering, vol. 22, no. 12, pp. 1045–1052, 2009.; G. Q. César and S. H. Daniel, Multivariable Model Predictive Control of a Simulated SAG plant, vol. 42. IFAC, 200; M. A. Naidoo, L. E. Olivier, and I. K. Craig, Combined neural network and particle filter state estimation with application to a run-of-mine ore mill, vol. 46. IFAC, 2013.; M. G. Maritz, J. D. Le Roux, and I. K. Craig, “Feed Size Distribution Feedforward Control for a Grinding Mill Circuit,” IFAC-PapersOnLine, vol. 52, no. 14, pp. 7–12, 2019.; P. Varas, R. Carvajal, and J. C. Aguero, “State Estimation for SAG Mills utilizing a simplified model with an alternative measurement,” IEEE CHILEAN Con ference on Electrical, Electronics Engineering, Information and Communication Technologies, CHILECON 2019, pp. 1–7, 2019.; J. D. Roux and I. K. Craig, “Requirements for estimating the volume of rocks and balls in a grinding mill,” IFAC-PapersOnLine, vol. 50, no. 1, pp. 1169–1174, 2017.; “14 - process modelling for control and diagnostic purposes,” in Process Modelling and Model Analysis (K. Hangos and I. Cameron, eds.), vol. 4 of Process Systems Engineering, pp. 363–386, Academic Press, 2001.; H. Alvarez, R. Lamanna, P. Vega, and S. Revollar, “Metodología para la obtención de modelos semifísicos de base fenomenológica aplicada a una sulfitadora de jugo de caña de azúcar,” RIAI - Revista Iberoamericana de Automatica e Informatica Industrial, vol. 6, no. 3, pp. 10–20, 2009.; E. A. Blanco, “Molienda Capítulo 8.,” Universidad De Cantabria, p. 55, 2019.; S. Morrell and I. Stephenson, “Slurry discharge capacity of autogenous and semiautogenous mills and the effect of grate design,” International Journal of Mineral Processing, vol. 46, no. 1-2, pp. 53–72, 1996.; D. Ramkrishna, Population balances: Theory and applications to particulate sys tems in engineering. Elsevier, 2000.; G. Besan¸con, “Nonlinear observers and applications,” Springer, 2007.; A. E. E. Inc., “Archweigh dual hp belt scale ®,” 2022.; S. AG, “Caudalímetros electromagnéticos Sitrans F M,” 2010.; W. S. Rice Lake, “Transmitter Weight SCT-2200 Advanced Series,” 2020.; HBM, “RTN Load Cell Special features,” 2021.; Rhosonics, “Serie sdm - medidor de densidad del lodo,” 2022.; S. C. Chapra and R. P. Canale, Métodos numéricos para ingenieros. McGraw-Hill Interamericana, 5 ed., 2007; D. Domíngues, Proyecto de automatización con PLC Siemens y Scada en Matlab mediante comunicación OPC para un sistema de mecanizado de piezas con control de velocidad de un motor de C.C. PhD thesis, Universidad Politécnica de Valencia, 2018.; Y. Triviño and D. Castelblanco, Desarrollo de una interfaz gráfica con LabView para la planta T5555. PhD thesis, Universidad Distrita Francisco José de Caldas, 2017.; G. Bastin and D. Dochain, “Chapter 4 - state and parameter estimation with unknown yield coefficients,” in On-line Estimation and Adaptive Control of Bioreactors (G. Bastin and D. Dochain, eds.), Process Measurement and Control, pp. 201–250, Amsterdam: Elsevier, 1990.; Siemens AG, “PCS 7 Unit Template ”Stirred tank reactor with Kalman filter ¨using the example of the Chemical Industry,” 2018.; https://repositorio.unal.edu.co/handle/unal/81481; Universidad Nacional de Colombia; Repositorio Institucional Universidad Nacional de Colombia; https://repositorio.unal.edu.co/

  18. 18
  19. 19
  20. 20

    المساهمون: Orozco Henao, César Augusto, Marín Quintero, Juan Guillermo

    المصدر: Repositorio Uninorte
    Universidad del Norte
    instacron:Universidad del Norte

    وصف الملف: application/pdf; image/png