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Journal articles on the topic 'Multivariable Control'

Author: Grafiati

Published: 4 June 2021

Last updated: 15 June 2025

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1

Zelinka, Peter. "Multivariable Predictive Control." IFAC Proceedings Volumes 30, no. 21 (1997): 175–81. http://dx.doi.org/10.1016/s1474-6670(17)41435-2.

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2

Mort, N. "Multivariable Process Control." IFAC Proceedings Volumes 27, no. 9 (1994): 161–64. http://dx.doi.org/10.1016/s1474-6670(17)45920-9.

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3

Tzouanas, V. K., C. Georgakis, W. L. Luyben, and L. H. Ungar. "Expert multivariable control." Computers & Chemical Engineering 12, no. 9-10 (1988): 1065–74. http://dx.doi.org/10.1016/0098-1354(88)87027-3.

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4

C., Aguodoh Patrick, and Chiagunye Tochukwu T. "Modeling a Multivariable Process Control System using PID Optimization." International Journal of Trend in Scientific Research and Development Volume-2, Issue-1 (2017): 433–39. http://dx.doi.org/10.31142/ijtsrd7016.

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5

SEN, M. DE LA, and M. B. PAZ. "Discrete multivariable adaptive control." International Journal of Control 42, no. 5 (1985): 1071–97. http://dx.doi.org/10.1080/00207178508933413.

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6

Morilla, Fernando, Juan Garrido, and Francisco Vázquez. "Control Multivariable por Desacoplo." Revista Iberoamericana de Automática e Informática Industrial RIAI 10, no. 1 (2013): 3–17. http://dx.doi.org/10.1016/j.riai.2012.11.001.

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7

Shen, Gwo Chyau, and Won Kyoo Lee. "Multivariable adaptive inferential control." Industrial & Engineering Chemistry Research 27, no. 10 (1988): 1863–72. http://dx.doi.org/10.1021/ie00082a019.

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8

Duan, Jiamin, Michael J. Grimble, and Michael A. Johnson. "Multivariable weighted predictive control." Journal of Process Control 7, no. 3 (1997): 219–35. http://dx.doi.org/10.1016/s0959-1524(97)00007-3.

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9

Engell, Sebastian. "Robust multivariable feedback control." Automatica 27, no. 4 (1991): 749–50. http://dx.doi.org/10.1016/0005-1098(91)90070-i.

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10

Ansari, R. M., and M. O. Tadé. "Constrained Nonlinear Multivariable Control." Chemical Engineering Research and Design 78, no. 4 (2000): 621–29. http://dx.doi.org/10.1205/026387600527563.

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11

Prime, H. A. "Multivariable Control for Industrial Applications." Electronics and Power 33, no. 11-12 (1987): 747. http://dx.doi.org/10.1049/ep.1987.0435.

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12

Shakouri, A. "Multivariable Control of Industrial Fractionators." IFAC Proceedings Volumes 19, no. 15 (1986): 49–54. http://dx.doi.org/10.1016/s1474-6670(17)59398-2.

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13

Dulău, Mircea, and Tudor-Mircea Dulău. "Multivariable System with Level Control." Procedia Technology 22 (2016): 614–22. http://dx.doi.org/10.1016/j.protcy.2016.01.128.

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14

Roberts, G. N., and D. R. Towill. "Multivariable Control of Warship Manoeuvring." IFAC Proceedings Volumes 20, no. 5 (1987): 227–32. http://dx.doi.org/10.1016/s1474-6670(17)55206-4.

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15

Ho, W. K., T. H. Lee, and E. B. Tay. "Knowledge-based multivariable PID control." Control Engineering Practice 6, no. 7 (1998): 855–64. http://dx.doi.org/10.1016/s0967-0661(98)00060-4.

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16

Tao, Gang. "Multivariable adaptive control: A survey." Automatica 50, no. 11 (2014): 2737–64. http://dx.doi.org/10.1016/j.automatica.2014.10.015.

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17

Thoma, M. "Multivariable control for industrial application." Automatica 25, no. 6 (1989): 956–57. http://dx.doi.org/10.1016/0005-1098(89)90065-4.

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18

Koung, Ching-Wei, and John F. Macgregor. "Identification for robust multivariable control." Automatica 30, no. 10 (1994): 1541–54. http://dx.doi.org/10.1016/0005-1098(94)90094-9.

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19

Brabrand, H., and S. Jorgenson. "Robust Multivariable Adaptive Process Control." IFAC Proceedings Volumes 21, no. 10 (1988): 195–200. http://dx.doi.org/10.1016/b978-0-08-036620-3.50038-7.

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20

Bahar, Mehrdad, and Jan Jantzen. "Digraph Programs for Multivariable Control." IFAC Proceedings Volumes 28, no. 10 (1995): 241–46. http://dx.doi.org/10.1016/s1474-6670(17)51524-4.

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21

Carr, S. "Multivariable Control for Industrial Applications." IEE Proceedings D Control Theory and Applications 135, no. 6 (1988): 500. http://dx.doi.org/10.1049/ip-d.1988.0077.

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22

Grimble, M. J. "H∞ multivariable-control-law synthesis." IEE Proceedings D Control Theory and Applications 140, no. 5 (1993): 353. http://dx.doi.org/10.1049/ip-d.1993.0047.

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23

Kouvaritakis, B., and J. A. Rossiter. "Multivariable stable generalised predictive control." IEE Proceedings D Control Theory and Applications 140, no. 5 (1993): 364. http://dx.doi.org/10.1049/ip-d.1993.0048.

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24

Larkin, Louis J., and James Philpott. "Implementation of a Multivariable Control." Journal of Engineering for Gas Turbines and Power 126, no. 3 (2004): 472–74. http://dx.doi.org/10.1115/1.1362668.

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A multivariable control (MVC) was designed and implemented for the Joint Technology Demonstrator Engine (JTDE) XTE65-2. The engine control system utilized an existing MC68000 processor that used fixed point ADA for its programming language and was limited in throughput and memory. A canonical formulation for the MVC compensator was used to minimize memory and calculation load on the processor. Use of this formulation resulted in a number of numerical difficulties. This paper relates the issues associated with the implementation of a MVC in this environment, and some approaches to solve these difficulties.

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25

Garrido, Juan, Francisco Vázquez, and Fernando Morilla. "Multivariable PID control by decoupling." International Journal of Systems Science 47, no. 5 (2014): 1054–72. http://dx.doi.org/10.1080/00207721.2014.911390.

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26

Huaguang, Zhang, and Lilong Cai. "MULTIVARIABLE FUZZY GENERALIZED PREDICTIVE CONTROL." Cybernetics and Systems 33, no. 1 (2002): 69–99. http://dx.doi.org/10.1080/019697202753306505.

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27

Zhang, Jie, and Rudy Agustriyanto. "Multivariable Inferential Feed-Forward Control." Industrial & Engineering Chemistry Research 42, no. 18 (2003): 4186–97. http://dx.doi.org/10.1021/ie020714d.

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28

Macháček, Jiří, and Josef Kotyk. "Multivariable Control of Distillation Column." IFAC Proceedings Volumes 28, no. 9 (1995): 185–90. http://dx.doi.org/10.1016/s1474-6670(17)47037-6.

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29

Ydstie, B. E., A. H. Kemna, and L. K. Liu. "Multivariable extended-horizon adaptive control." Computers & Chemical Engineering 12, no. 7 (1988): 733–43. http://dx.doi.org/10.1016/0098-1354(88)80011-5.

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30

Shen, Shih-Haur, and Cheng-Ching Yu. "Indirect feedforward control: multivariable systems." Chemical Engineering Science 47, no. 12 (1992): 3085–97. http://dx.doi.org/10.1016/0009-2509(92)87008-e.

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31

McDermott, Patrick E. "Adaptive multivariable optimal predictive control." International Journal of Adaptive Control and Signal Processing 1, no. 2 (1987): 111–28. http://dx.doi.org/10.1002/acs.4480010203.

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32

Seshagiri, Sridhar. "Robust Multivariable PI Control: Applications to Process Control." IFAC Proceedings Volumes 41, no. 2 (2008): 11937–42. http://dx.doi.org/10.3182/20080706-5-kr-1001.02020.

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33

Zhang, Wei, Yagang Wang, Yurong Liu, and Weidong Zhang. "Multivariable disturbance observer-based H2analytical decoupling control design for multivariable systems." International Journal of Systems Science 47, no. 1 (2015): 179–93. http://dx.doi.org/10.1080/00207721.2015.1036479.

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34

HARA, Shinji, and Yutaka YAMAMOTO. "Stability of Multivariable Repetitive Control Systems." Transactions of the Society of Instrument and Control Engineers 22, no. 12 (1986): 1256–61. http://dx.doi.org/10.9746/sicetr1965.22.1256.

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35

Ramírez-Mendoza, Mercedes, and Pedro Albertos. "MULTIVARIABLE CONTROL OF A REDUCTION FURNACE." IFAC Proceedings Volumes 40, no. 5 (2007): 231–36. http://dx.doi.org/10.3182/20070606-3-mx-2915.00037.

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36

Popescu, D., and C. Dimon. "MULTIVARIABLE CONTROL ON A COMPLEX PLATFORM." IFAC Proceedings Volumes 40, no. 18 (2007): 241–46. http://dx.doi.org/10.3182/20070927-4-ro-3905.00041.

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37

EL-SHAHAT, ISMAIL. "Suboptimal Decentralized Control of Multivariable Systems." Journal of King Abdulaziz University-Engineering Sciences 11, no. 2 (1999): 107–14. http://dx.doi.org/10.4197/eng.11-2.9.

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38

Yong, Y. K., I. A. Mahmood, B. Bhikkaji, and S. O. R. Moheimani. "Multivariable Control Designs for Piezoelectric tubes." IFAC Proceedings Volumes 44, no. 1 (2011): 2030–35. http://dx.doi.org/10.3182/20110828-6-it-1002.01745.

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39

ZHAO, YAO, and HIDENORI KIMURA. "Multivariable dead-beat control with robustness." International Journal of Control 47, no. 1 (1988): 229–55. http://dx.doi.org/10.1080/00207178808906009.

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40

Gupta, Madan, Jerzy Kiszka, and G. Trojan. "Multivariable Structure of Fuzzy Control Systems." IEEE Transactions on Systems, Man, and Cybernetics 16, no. 5 (1986): 638–56. http://dx.doi.org/10.1109/tsmc.1986.289309.

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41

Pratt, Roger, and Daniel J. Walker. "Book Review: Robust Multivariable Feedback Control." International Journal of Electrical Engineering & Education 29, no. 3 (1992): 275–76. http://dx.doi.org/10.1177/002072099202900313.

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42

Whalley, R., and M. Ebrahimi. "Optimum Multivariable Wind Tunnel System Control." Proceedings of the Institution of Mechanical Engineers, Part I: Journal of Systems and Control Engineering 219, no. 7 (2005): 519–31. http://dx.doi.org/10.1243/095965105x33590.

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The control of multivariable system models following input set point and load disturbance changes is considered. An inner and outer loop control strategy is proposed, for analysis purposes, enabling targeted recovery rates, off-set attenuation and constrained steady state interaction to be achieved. Proportional control and passive network compensation alone are employed. Gain ratio selection, ensuring energy efficient confinement of output perturbations, following low frequency load disturbances and reference input changes, is exercised. Disturbance suppression and transient recovery rate adjustment, via outer loop feedback advancement, is advocated. An application study is presented for purposes of illustration, confirming the theoretical predictions thereby.

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43

LIU, G. P., H. UNBEHAUEN, and R. J. PATTON. "Robust control of multivariable critical systems." International Journal of Systems Science 26, no. 10 (1995): 1907–18. http://dx.doi.org/10.1080/00207729508929144.

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44

Gossner, J. R., J. A. Rossiter, and B. Kouvaritakis. "Constrained multivariable cautious stable predictive control." IEE Proceedings - Control Theory and Applications 145, no. 5 (1998): 385–91. http://dx.doi.org/10.1049/ip-cta:19981835.

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45

Alexandrov, A. G., and Yu F. Orlov. "FREQUENCY ADAPTIVE CONTROL OF MULTIVARIABLE PLANTS." IFAC Proceedings Volumes 35, no. 1 (2002): 295–300. http://dx.doi.org/10.3182/20020721-6-es-1901.01035.

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46

Hsu, Liu, José Paulo Vilela Soares da Cunha, Ramon R. Costa, and Fernando Lizarralde. "UNIT VECTOR CONTROL OF MULTIVARIABLE SYSTEMS." IFAC Proceedings Volumes 35, no. 1 (2002): 331–36. http://dx.doi.org/10.3182/20020721-6-es-1901.01041.

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47

He, Xiang-Dong, Sheng Liu, Harry Asada, and Hiroyuki Itoh. "Multivariable Control of Vapor Compression Systems." HVAC&R Research 4, no. 3 (1998): 205–30. http://dx.doi.org/10.1080/10789669.1998.10391401.

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48

SONG, Q., M. R. KATEBI, and M. J. GRIMBLE. "Robust multivariable implicit self-tuning control." IMA Journal of Mathematical Control and Information 10, no. 1 (1993): 49–70. http://dx.doi.org/10.1093/imamci/10.1.49.

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49

Morales Villegas, Hernán Vinicio, Milton Ramiro Aimacaña Sanchez, Bryan Israel Chango Guanoluisa, Katerin Mishel Simba Palomo, and Emanuel Ricardo Sacta Paida. "Control Multivariable de un Robot Móvil." Ciencia Latina Revista Científica Multidisciplinar 8, no. 6 (2025): 6536–54. https://doi.org/10.37811/cl_rcm.v8i6.15342.

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En este trabajo se propone un algoritmo de control discreto basado en axiomas de algebra lineal de un robot uniciclo, a fin de analizar la evolución de los estados del sistema de control para diferentes periodos de muestreo y evaluar la estabilidad y robustez del control en tareas de regulación y seguimiento. Se modelaron la cinemática y las restricciones no holonómicas del robot, considerando parámetros como velocidad angular, velocidad lineal y características físicas del prototipo. Por tal motivo, se incluyó simulaciones y experimentos prácticos, implementando controladores multivariables MIMO y PID en motores DC. De esta manera, los resultados evidencian que el sistema es inestable con tiempos de muestreo superiores a 0.5 segundos. Sin embargo, para intervalos menores los controladores propuestos permiten un desempeño eficiente en seguimiento de trayectorias y regulación de posiciones. Además, el diseño basado en álgebra lineal demostró mayor robustez ante perturbaciones en comparación con el PID. Por lo que, se contribuye al desarrollo de estrategias avanzadas de control para robots móviles, destacando la importancia de la discretización y el manejo de restricciones cinemáticas en entornos dinámicos.

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50

WEN, GUILIN, QING-GUO WANG, CHONG LIN, GUANGYAO LI, and XU HAN. "CHAOS SYNCHRONIZATION VIA MULTIVARIABLE PID CONTROL." International Journal of Bifurcation and Chaos 17, no. 05 (2007): 1753–58. http://dx.doi.org/10.1142/s0218127407018051.

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Synchronization via multivariable PID control is studied. Based on the descriptor approach, the problem of PID controller design is transformed to that of static output feedback (SOF) controller design. The improvement of the solvability of the Linear Matrix Inequality (LMI) is achieved, in comparison with the existing literature on designing PID controller based on the LMI technique. With the aid of the free-weighting matrix approach and the S-procedure, the synchronization criterion for a general Lur'e system is established based on the LMI technique. The feasibility of the methodology is illustrated by the well-known Chua's circuit.

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