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Journal articles on the topic 'State feedback control'

Author: Grafiati

Published: 4 June 2021

Last updated: 8 June 2024

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1

Sguarezi Filho, Joãozinho, André Luiz de Lacerda Ferreira Murari, Carlos Eduardo Capovilla, José Alberto Torrico Altuna, and Rogério Vani Jacomini. "A State Feedback Dfig Power Control For Wind Generation." Eletrônica de Potência 20, no. 2 (May 1, 2015): 151–59. http://dx.doi.org/10.18618/rep.2015.2.151159.

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2

HIGUCHI, Takehiro, Seiya UENO, and Takuya OHMURA. "A3 Singularity Avoidance for Control Moment Gyro Systems Using State Feedback Control Law." Proceedings of the Space Engineering Conference 2009.18 (2010): 11–16. http://dx.doi.org/10.1299/jsmesec.2009.18.11.

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3

Yaesh, Isaac, Agnès Cohen, and Uri Shaked. "Delayed State-Feedback H ∞ Control." IFAC Proceedings Volumes 31, no. 19 (July 1998): 51–56. http://dx.doi.org/10.1016/s1474-6670(17)41127-x.

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4

Albertos, Pedro, and Antonio Sala. "State Feedback Control with Integrity." IFAC Proceedings Volumes 37, no. 21 (December 2004): 211–16. http://dx.doi.org/10.1016/s1474-6670(17)30470-6.

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5

Kaewpraek, Nikorn, and Wudhichai Assawinchaichote. "H∞Fuzzy State-Feedback Control Plus State-Derivative-Feedback Control Synthesis for Photovoltaic Systems." Asian Journal of Control 18, no. 4 (October 29, 2015): 1441–52. http://dx.doi.org/10.1002/asjc.1233.

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6

Cardim, Rodrigo, Marcelo C. M. Teixeira, Edvaldo AssunçÃo, and Márcio R. Covacic. "DESIGN OF STATE-DERIVATIVE FEEDBACK CONTROLLERS USING A STATE FEEDBACK CONTROL DESIGN." IFAC Proceedings Volumes 40, no. 20 (2007): 22–27. http://dx.doi.org/10.3182/20071017-3-br-2923.00004.

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7

KONO, Michio. "Decoupling Control by Incomplete State Feedback." Transactions of the Society of Instrument and Control Engineers 21, no. 6 (1985): 632–34. http://dx.doi.org/10.9746/sicetr1965.21.632.

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8

Bühler, H. "Kaskaden-Zustandsregelung / Cascaded state feedback control." auto 33, no. 1-12 (December 1985): 52–60. http://dx.doi.org/10.1524/auto.1985.33.112.52.

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9

Clarke, Francis H., Ludovic Rifford, and R. J. Stern. "Feedback in state constrained optimal control." ESAIM: Control, Optimisation and Calculus of Variations 7 (2002): 97–133. http://dx.doi.org/10.1051/cocv:2002005.

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10

Nishida, Takeshi. "State Feedback Control using Particle Filter." IEEJ Transactions on Electronics, Information and Systems 133, no. 7 (2013): 1376–83. http://dx.doi.org/10.1541/ieejeiss.133.1376.

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11

van Handel, R., J. K. Stockton, and H. Mabuchi. "Feedback control of quantum state reduction." IEEE Transactions on Automatic Control 50, no. 6 (June 2005): 768–80. http://dx.doi.org/10.1109/tac.2005.849193.

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12

Kase, Wataru, and Yuji Shigehiro. "Pseudo Innerizing Control by State Feedback." IEEJ Transactions on Electronics, Information and Systems 136, no. 12 (2016): 1827–33. http://dx.doi.org/10.1541/ieejeiss.136.1827.

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13

LI, YUXIA, WALLACE K. S. TANG, and GUANRONG CHEN. "GENERATING HYPERCHAOS VIA STATE FEEDBACK CONTROL." International Journal of Bifurcation and Chaos 15, no. 10 (October 2005): 3367–75. http://dx.doi.org/10.1142/s0218127405013988.

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In this letter, a simple nonlinear state feedback controller is designed for generating hyperchaos from a three-dimensional autonomous chaotic system. The hyperchaotic system is not only demonstrated by computer simulations but also verified with bifurcation analysis, and is implemented experimentally via an electronic circuit.

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14

Mondié, S., P. Zagalak, and V. Kučera. "State feedback in linear control theory." Linear Algebra and its Applications 317, no. 1-3 (September 2000): 177–92. http://dx.doi.org/10.1016/s0024-3795(00)00153-1.

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15

Ram, Y. M., Akshay Singh, and John E. Mottershead. "State feedback control with time delay." Mechanical Systems and Signal Processing 23, no. 6 (August 2009): 1940–45. http://dx.doi.org/10.1016/j.ymssp.2008.04.012.

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16

Veillette, Robert J. "Reliable linear-quadratic state-feedback control." Automatica 31, no. 1 (January 1995): 137–43. http://dx.doi.org/10.1016/0005-1098(94)e0045-j.

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17

Zhong, Wanxie, W. P. Howson, and F. W. Williams. "control state feedback and Rayleigh quotient." Computer Methods in Applied Mechanics and Engineering 191, no. 3-5 (November 2001): 489–501. http://dx.doi.org/10.1016/s0045-7825(01)00286-9.

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18

NISHIDA, TAKESHI. "State Feedback Control Using Particle Filter." Electronics and Communications in Japan 98, no. 6 (May 6, 2015): 16–25. http://dx.doi.org/10.1002/ecj.11658.

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19

Chen, Gang, Hong-qiu Zhu, Chun-hua Yang, and Chun-hua Hu. "State feedback control for Lurie networked control systems." Journal of Central South University 19, no. 12 (December 2012): 3510–15. http://dx.doi.org/10.1007/s11771-012-1436-0.

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20

Lee, Feng-Chi, Yuan-Wei Tseng, Rong-Ching Wu, Wen-Chuan Chen, and Chin-Sheng Chen. "Inverse Optimal Control in State Derivative Space System with Applications in Motor Control." Energies 14, no. 6 (March 23, 2021): 1775. http://dx.doi.org/10.3390/en14061775.

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This paper mathematically explains how state derivative space (SDS) system form with state derivative related feedback can supplement standard state space system with state related feedback in control designs. Practically, inverse optimal control is attractive because it can construct a stable closed-loop system while optimal control may not have exact solution. Unlike the previous algorithms which mainly applied state feedback, in this paper inverse optimal control are carried out utilizing state derivative alone in SDS system. The effectiveness of proposed algorithms are verified by design examples of DC motor tracking control without tachometer and very challenging control problem of singular system with impulse mode. Feedback of direct measurement of state derivatives without integrations can simplify implementation and reduce cost. In addition, the proposed design methods in SDS system with state derivative feedback are analogous to those in state space system with state feedback. Furthermore, with state derivative feedback control in SDS system, wider range of problems such as singular system control can be handled effectively. These are main advantages of carrying out control designs in SDS system.

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21

Clarke, F. H., and R. J. Stern. "State Constrained Feedback Stabilization." SIAM Journal on Control and Optimization 42, no. 2 (January 2003): 422–41. http://dx.doi.org/10.1137/s036301290240453x.

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22

Hong, Seongil, Chul H. Park, and Hyun C. Park. "Vibration control of beams using multiobjective state-feedback control." Smart Materials and Structures 15, no. 1 (January 9, 2006): 157–63. http://dx.doi.org/10.1088/0964-1726/15/1/044.

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23

Dabiri, Azita, Balazs Kulcsar, and Hakan Koroglu. "Distributed LPV State-Feedback Control Under Control Input Saturation." IEEE Transactions on Automatic Control 62, no. 5 (May 2017): 2450–56. http://dx.doi.org/10.1109/tac.2016.2598967.

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24

Nguyen, Le Hoa, and Keum-Shik Hong. "Hopf bifurcation control via a dynamic state-feedback control." Physics Letters A 376, no. 4 (January 2012): 442–46. http://dx.doi.org/10.1016/j.physleta.2011.11.057.

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25

Abbas, Hossam Seddik, Ahsan Ali, Seyed Mahdi Hashemi, and Herbert Werner. "LPV state-feedback control of a control moment gyroscope." Control Engineering Practice 24 (March 2014): 129–37. http://dx.doi.org/10.1016/j.conengprac.2013.05.008.

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26

Angélico, Bruno A., Fernando S. Barbosa, and Fabio Y. Toriumi. "State Feedback Decoupling Control of a Control Moment Gyroscope." Journal of Control, Automation and Electrical Systems 28, no. 1 (September 16, 2016): 26–35. http://dx.doi.org/10.1007/s40313-016-0277-8.

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27

XIAO, MIN, WEI XING ZHENG, and JINDE CAO. "BIFURCATION CONTROL OF A CONGESTION CONTROL MODEL VIA STATE FEEDBACK." International Journal of Bifurcation and Chaos 23, no. 06 (June 2013): 1330018. http://dx.doi.org/10.1142/s0218127413300188.

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This paper proposes to use a state feedback method to control the Hopf bifurcation for a novel congestion control model, i.e. the exponential random early detection (RED) algorithm with a single link and a single source. The gain parameter of the congestion control model is chosen as the bifurcation parameter. The analysis shows that in the absence of the state feedback controller, the model loses stability via the Hopf bifurcation early, and can maintain a stationary sending rate only in a certain domain of the gain parameter. When applying the state feedback controller to the model, the onset of the undesirable Hopf bifurcation is postponed. Thus, the stability domain is extended, and the model possesses a stable sending rate in a larger parameter range. Furthermore, explicit formulae to determine the properties of the Hopf bifurcation are obtained. Numerical simulations are given to justify the validity of the state feedback controller in bifurcation control.

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28

HE, Shuai-Tian. "Design of State Feedback Control Adjustable Parameter." Acta Automatica Sinica 34, no. 5 (May 20, 2008): 613–16. http://dx.doi.org/10.3724/sp.j.1004.2008.00613.

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29

Jumaa Alkurawy, Lafta Esmaeel, Khalid Gadban Mohammed, and Ammar Issa Ismael. "State feedback control for human inspiratory system." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 3 (June 1, 2022): 2405. http://dx.doi.org/10.11591/ijece.v12i3.pp2405-2413.

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<span>The mathematical modeling of human respiratory system is an essentially part in saving precision information of diagnostic about the disease of cardiovascular respiratory system. The physics of respiratory system and cardiovascular are completely interconnected with each other. In this paper, we will study the state feedback control for the inspiratory system during study the characteristics of the response output with the stability. The model of system is nonlinear and linearized it by Tayler method to be simple to matching with the control theory. We convert the system from differential equation to state equation to find the optimal control that helps to drive the respiratory system. Simulations are managed to indicate the proposed method effectiveness. The results of simulations are validated by using a real information form the health center.</span>

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30

Yang, Vigor, Alok Sinha, and Youn-Tih Fung. "State-feedback control of longitudinal combustion instabilities." Journal of Propulsion and Power 8, no. 1 (January 1992): 66–73. http://dx.doi.org/10.2514/3.23443.

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31

ŻAKJ, STANISLAW H., and CARL A. MACCARLEY. "State-feedback control of non-linear systems†." International Journal of Control 43, no. 5 (May 1986): 1497–514. http://dx.doi.org/10.1080/00207178608933554.

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32

ELMADBOULY, ESAM E. "Nuclear power plant cascaded state Feedback control." International Journal of Control 45, no. 2 (February 1987): 681–92. http://dx.doi.org/10.1080/00207178708933760.

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33

OWENS, T. J., and J. O'REILLY. "Parametric state-feedback control with response insensitivity." International Journal of Control 45, no. 3 (March 1987): 791–809. http://dx.doi.org/10.1080/00207178708933770.

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34

OWENS, T. J. "Parametric state-feedback control with model reduction." International Journal of Control 47, no. 5 (May 1988): 1299–306. http://dx.doi.org/10.1080/00207178808906097.

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35

Cai, Guo-Ping, and C. W. Lim. "Continuous Suboptimal Control with Partial State Feedback." Journal of Vibration and Control 11, no. 4 (April 2005): 561–78. http://dx.doi.org/10.1177/1077546305052038.

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It is well known that the classical optimal control method requires availability of all state variables of the controlled system for control feedback. This requires a measurable system, namely that all state variables may be obtained by measurement of sensors or by estimation of observers. However, some state variables in control feedback actually have a small effect on control performance. Neglecting these state variables does not greatly affect the performance of control. In this paper, we investigate a continuous suboptimal control method with partial-state feedback. First, the state variables with significant effect on the performance of control are determined using second-order sensitivity (i.e. second-order derivative of performance index with respect to control gain). Then, the suboptimal controller is designed utilizing only the determined state variables. Numerical examples are presented to demonstrate the application of the proposed control algorithm. It is shown that the relative importance of each state variable can be indicated clearly by the second-order sensitivity. The suboptimal control method presented is effective in reducing maximum responses of the structure. Furthermore, the continuous suboptimal control method may achieve almost the same level of control effectiveness as the discrete suboptimal control method.

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36

Li, Rui, Meng Yang, and Tianguang Chu. "State Feedback Stabilization for Boolean Control Networks." IEEE Transactions on Automatic Control 58, no. 7 (July 2013): 1853–57. http://dx.doi.org/10.1109/tac.2013.2238092.

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37

SUGIYAMA, Kazuaki, and Toshiyuki OHTSUKA. "l1 State Feedback Control of Active Suspension." JSME International Journal Series C 43, no. 3 (2000): 505–12. http://dx.doi.org/10.1299/jsmec.43.505.

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38

Esmailzadeh, E., and H. D. Taghirad. "STATE-FEEDBACK CONTROL FOR PASSENGER RIDE DYNAMICS." Transactions of the Canadian Society for Mechanical Engineering 19, no. 4 (December 1995): 495–507. http://dx.doi.org/10.1139/tcsme-1995-0027.

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An analytical investigation of a half-car model with passenger dynamics, subjected to random road disturbance, is performed. Two different methods of defining the performance index for optimal controller design are proposed. Nondeterministic inputs are applied to simulate the road surface conditions more realistically. Results obtained illustrate that using an optimal state-feedback controller, with passenger acceleration included in the performance index, would exhibit not only an improved passenger ride comfort, but also, a better road handling and stability.

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39

Li, H., M. Y. Chow, and Z. Sun. "State feedback stabilisation of networked control systems." IET Control Theory & Applications 3, no. 7 (July 1, 2009): 929–40. http://dx.doi.org/10.1049/iet-cta.2008.0260.

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40

Zhao, Xueyan, and Feiqi Deng. "Divided State Feedback Control of Stochastic Systems." IEEE Transactions on Automatic Control 60, no. 7 (July 2015): 1870–85. http://dx.doi.org/10.1109/tac.2015.2396647.

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41

Long, Xinhua, Song Ren, and Pingxu Zheng. "Delayed State Feedback Control for Milling Process." Procedia IUTAM 22 (2017): 115–22. http://dx.doi.org/10.1016/j.piutam.2017.08.015.

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42

Yu, Jie, and Athanasios Sideris. "Optimal induced l1-norm state feedback control." Automatica 35, no. 5 (May 1999): 819–27. http://dx.doi.org/10.1016/s0005-1098(98)00214-3.

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43

Fernandes, Darlan, Rogerio Almeida, Tatiana Guedes, A. J. Sguarezi Filho, and F. F. Costa. "State feedback control for DC-photovoltaic systems." Electric Power Systems Research 143 (February 2017): 794–801. http://dx.doi.org/10.1016/j.epsr.2016.08.037.

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44

Krogh, B. H., and S. Kowalewski. "State feedback control of condition/event systems." Mathematical and Computer Modelling 23, no. 11-12 (June 1996): 161–73. http://dx.doi.org/10.1016/0895-7177(96)00070-2.

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45

Canudas de Wit, C., and N. Fixot. "Robot control via robust estimated state feedback." IEEE Transactions on Automatic Control 36, no. 12 (1991): 1497–501. http://dx.doi.org/10.1109/9.106170.

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46

Schmitendorf, W. E., and C. V. Hollot. "Simultaneous stabilization via linear state feedback control." IEEE Transactions on Automatic Control 34, no. 9 (1989): 1001–5. http://dx.doi.org/10.1109/9.35818.

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47

SUGIYAMA, Kazuaki, and Toshiyuki OHTSUKA. "l1 State Feedback Control of Active Suspension." Transactions of the Japan Society of Mechanical Engineers Series C 65, no. 631 (1999): 955–61. http://dx.doi.org/10.1299/kikaic.65.955.

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48

HAMMER, JACOB. "State feedback for non-linear control systems." International Journal of Control 50, no. 5 (November 1989): 1961–80. http://dx.doi.org/10.1080/00207178908953476.

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49

Shamma, Jeff S. "Nonlinear state feedback for ℓ1 optimal control." Systems & Control Letters 21, no. 4 (October 1993): 265–70. http://dx.doi.org/10.1016/0167-6911(93)90067-g.

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50

L'Afflitto, Andrea, Wassim M. Haddad, and Efstathios Bakolas. "Partial-state stabilization and optimal feedback control." International Journal of Robust and Nonlinear Control 26, no. 5 (April 21, 2015): 1026–50. http://dx.doi.org/10.1002/rnc.3349.

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