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Journal articles on the topic 'Feedback Control Theory'

Author: Grafiati

Published: 4 June 2021

Last updated: 3 February 2022

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1

James, M. R. "Optimal Quantum Control Theory." Annual Review of Control, Robotics, and Autonomous Systems 4, no. 1 (2021): 343–67. http://dx.doi.org/10.1146/annurev-control-061520-010444.

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This article explains some fundamental ideas concerning the optimal control of quantum systems through the study of a relatively simple two-level system coupled to optical fields. The model for this system includes both continuous and impulsive dynamics. Topics covered include open- and closed-loop control, impulsive control, open-loop optimal control, quantum filtering, and measurement feedback optimal control.

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2

Peresada, S., S. Kovbasa, S. Korol, and N. Zhelinskyi. "FEEDBACK LINEARIZING FIELD-ORIENTED CONTROL OF INDUCTION GENERATOR: THEORY AND EXPERIMENTS." Tekhnichna Elektrodynamika 2017, no. 2 (2017): 48–56. http://dx.doi.org/10.15407/techned2017.02.048.

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3

Weiss, Gerald. "Feedback control: Theory and design." Automatica 22, no. 6 (1986): 761–62. http://dx.doi.org/10.1016/0005-1098(86)90018-x.

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4

Ros, Javier, Alberto Casas, Jasiel Najera, and Isidro Zabalza. "64048 QUANTITATIVE FEEDBACK THEORY CONTROL OF A HEXAGLIDE TYPE PARALLEL MANIPULATOR(Control of Multibody Systems)." Proceedings of the Asian Conference on Multibody Dynamics 2010.5 (2010): _64048–1_—_64048–10_. http://dx.doi.org/10.1299/jsmeacmd.2010.5._64048-1_.

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5

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

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6

Stirling, Julian. "Control theory for scanning probe microscopy revisited." Beilstein Journal of Nanotechnology 5 (March 21, 2014): 337–45. http://dx.doi.org/10.3762/bjnano.5.38.

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We derive a theoretical model for studying SPM feedback in the context of control theory. Previous models presented in the literature that apply standard models for proportional-integral-derivative controllers predict a highly unstable feedback environment. This model uses features specific to the SPM implementation of the proportional-integral controller to give realistic feedback behaviour. As such the stability of SPM feedback for a wide range of feedback gains can be understood. Further consideration of mechanical responses of the SPM system gives insight into the causes of exciting mechan

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7

OGURA, Saori, Takumi EBINE, Koichi HASHIMOTO, and Hidenori KIMURA. "Visual Feedback Control Based on H^|^infin; Control Theory." Transactions of the Society of Instrument and Control Engineers 30, no. 12 (1994): 1505–11. http://dx.doi.org/10.9746/sicetr1965.30.1505.

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8

Mathis, Mackenzie W., and Steffen Schneider. "Motor control: Neural correlates of optimal feedback control theory." Current Biology 31, no. 7 (2021): R356—R358. http://dx.doi.org/10.1016/j.cub.2021.01.087.

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9

Clemniens, A. J., and J. B. Keats. "Bayesian Inference for Feedback Control. I: Theory." Journal of Irrigation and Drainage Engineering 118, no. 3 (1992): 397–415. http://dx.doi.org/10.1061/(asce)0733-9437(1992)118:3(397).

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10

Nwokah, Osita, Suhada Jayasuriya, and Yossi Chait. "Parametric robust control by quantitative feedback theory." Journal of Guidance, Control, and Dynamics 15, no. 1 (1992): 207–14. http://dx.doi.org/10.2514/3.20820.

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11

Hess, R. A., and D. K. Henderson. "Flexible vehicle control using quantitative feedback theory." Journal of Guidance, Control, and Dynamics 18, no. 5 (1995): 1062–67. http://dx.doi.org/10.2514/3.21505.

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12

Gershon, E., and U. Shaked. "H∞ feedback-control theory in biochemical systems." International Journal of Robust and Nonlinear Control 18, no. 1 (2007): 14–50. http://dx.doi.org/10.1002/rnc.1195.

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13

Madhav, Manu S., and Noah J. Cowan. "The Synergy Between Neuroscience and Control Theory: The Nervous System as Inspiration for Hard Control Challenges." Annual Review of Control, Robotics, and Autonomous Systems 3, no. 1 (2020): 243–67. http://dx.doi.org/10.1146/annurev-control-060117-104856.

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Here, we review the role of control theory in modeling neural control systems through a top-down analysis approach. Specifically, we examine the role of the brain and central nervous system as the controller in the organism, connected to but isolated from the rest of the animal through insulated interfaces. Though biological and engineering control systems operate on similar principles, they differ in several critical features, which makes drawing inspiration from biology for engineering controllers challenging but worthwhile. We also outline a procedure that the control theorist can use to dr

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14

Daryin, A. N., and A. B. Kurzhanski. "Impulse Control Inputs and the Theory of Fast Feedback Control." IFAC Proceedings Volumes 41, no. 2 (2008): 4869–74. http://dx.doi.org/10.3182/20080706-5-kr-1001.00818.

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15

Moin, Parviz, and Thomas Bewley. "Feedback Control of Turbulence." Applied Mechanics Reviews 47, no. 6S (1994): S3—S13. http://dx.doi.org/10.1115/1.3124438.

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A brief review of current approaches to active feedback control of the fluctuations arising in turbulent flows is presented, emphasizing the mathematical techniques involved. Active feedback control schemes are categorized and compared by examining the extent to which they are based on the governing flow equations. These schemes are broken down into the following categories: adaptive schemes, schemes based on heuristic physical arguments, schemes based on a dynamical systems approach, and schemes based on optimal control theory applied directly to the Navier-Stokes equations. Recent advances i

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16

Olesen, Veronica, Claes Breitholtz, and Torsten Wik. "Tank Reactor Temperature Control using Quantitative Feedback Theory." IFAC Proceedings Volumes 41, no. 2 (2008): 4970–75. http://dx.doi.org/10.3182/20080706-5-kr-1001.00835.

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17

Chen, Ben M., Tong H. Lee, Kemao Peng, and V. Venkataramanan. "COMPOSITE NONLINEAR FEEDBACK CONTROL: THEORY AND AN APPLICATION." IFAC Proceedings Volumes 35, no. 1 (2002): 31–36. http://dx.doi.org/10.3182/20020721-6-es-1901.00086.

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18

YANIV, O., and I. HOROWITZ. "Quantitative feedback theory for active vibration control synthesis." International Journal of Control 51, no. 6 (1990): 1251–58. http://dx.doi.org/10.1080/00207179008934130.

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19

Meerkov, S. M., and T. Runolfsson. "Theory of residence-time control by output feedback." Dynamics and Control 1, no. 1 (1991): 63–81. http://dx.doi.org/10.1007/bf02169425.

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20

Del Vecchio, Domitilla, Aaron J. Dy, and Yili Qian. "Control theory meets synthetic biology." Journal of The Royal Society Interface 13, no. 120 (2016): 20160380. http://dx.doi.org/10.1098/rsif.2016.0380.

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The past several years have witnessed an increased presence of control theoretic concepts in synthetic biology. This review presents an organized summary of how these control design concepts have been applied to tackle a variety of problems faced when building synthetic biomolecular circuits in living cells. In particular, we describe success stories that demonstrate how simple or more elaborate control design methods can be used to make the behaviour of synthetic genetic circuits within a single cell or across a cell population more reliable, predictable and robust to perturbations. The descr

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21

Li, Fuhuo. "Control Systems and Number Theory." International Journal of Mathematics and Mathematical Sciences 2012 (2012): 1–28. http://dx.doi.org/10.1155/2012/508721.

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We try to pave a smooth road to a proper understanding of control problems in terms of mathematical disciplines, and partially show how to number-theorize some practical problems. Our primary concern is linear systems from the point of view of our principle of visualization of the state, an interface between the past and the present. We view all the systems as embedded in the state equation, thus visualizing the state. Then we go on to treat the chain-scattering representation of the plant of Kimura 1997, which includes the feedback connection in a natural way, and we consider theH∞-control pr

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22

Tong, M. D., and W. K. Chen. "Perfect Multivariable Feedback Theory." Journal of Circuits, Systems and Computers 07, no. 02 (1997): 129–51. http://dx.doi.org/10.1142/s0218126697000103.

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The paper nicely combines the state-space description with the input-output description and elegantly formulates the multivariable feedback theory as well as obtains a number of useful results for modern network and control theory. In particular, it reveals various kinds of duality between a multivariable feedback network and its associated inverse network, such as structure duality, transfer function matrix (determinant) duality and duality on controllability (observability). It also thoroughly studies four pairs of the (null) return difference matrices of a multivariable feedback network and

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23

Yang, Tao. "Control of Chaos Using Sampled-Data Feedback Control." International Journal of Bifurcation and Chaos 08, no. 12 (1998): 2433–38. http://dx.doi.org/10.1142/s0218127498001947.

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In this paper we present a theory for control of chaotic systems using sampled data. The output of the chaotic system is sampled at a given sampling rate and the sampled output is used by a feedback subsystem to construct a control signal, which is held constant by a holding subsystem. Hence, during each control iteration, the control input remains unchanged. Theoretical results on the asymptotic stability of the resulting controlled chaotic systems are presented. Numerical experimental results via Chua's circuit are used to verify the theoretical results.

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24

Pyragas, Kestutis. "Delayed feedback control of chaos." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 364, no. 1846 (2006): 2309–34. http://dx.doi.org/10.1098/rsta.2006.1827.

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Time-delayed feedback control is well known as a practical method for stabilizing unstable periodic orbits embedded in chaotic attractors. The method is based on applying feedback perturbation proportional to the deviation of the current state of the system from its state one period in the past, so that the control signal vanishes when the stabilization of the target orbit is attained. A brief review on experimental implementations, applications for theoretical models and most important modifications of the method is presented. Recent advancements in the theory, as well as an idea of using an

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25

Farrell, Philip S. E., and Sandra Chéry. "PTA: Perceptual Control Theory Based Task Analysis." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 42, no. 18 (1998): 1314–18. http://dx.doi.org/10.1177/154193129804201808.

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Task Analysis is a fundamental tool for analyzing human-machine systems, and has been applied in major aircraft projects supporting the Canadian Forces. The literature describes many task analysis methods under two major categories: behavioral and cognitive task analysis. This paper proposes a new task analysis based on Perceptual Control Theory (PCT) called PTA that encompasses all other analyses. PTA adopts an ego-centric approach, analyses goals and feedback, determines the cognitive compatibility, and specifies information requirements for interface and/or systems design. PTA was applied t

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26

LASIECKA, IRENA. "MATHEMATICAL CONTROL THEORY IN STRUCTURAL ACOUSTIC PROBLEMS." Mathematical Models and Methods in Applied Sciences 08, no. 07 (1998): 1119–53. http://dx.doi.org/10.1142/s0218202598000524.

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We consider control problems formulated within the context of structural acoustic models. The goal is to reduce the level of a noise or unwanted pressure in the interior of an acoustic chamber. This is accomplished by applying passive and active boundary and point controls in a feedback form. Mathematical (PDE) aspects of the underlying control problems are presented.

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27

Todorov, Emanuel, and Michael I. Jordan. "Optimal feedback control as a theory of motor coordination." Nature Neuroscience 5, no. 11 (2002): 1226–35. http://dx.doi.org/10.1038/nn963.

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28

Moon, S. M., R. L. Clark, and D. G. Cole. "The recursive generalized predictive feedback control: theory and experiments." Journal of Sound and Vibration 279, no. 1-2 (2005): 171–99. http://dx.doi.org/10.1016/j.jsv.2003.12.034.

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29

Vadali, S. R., and E. S. Kim. "Feedback control of tethered satellites using Lyapunov stability theory." Journal of Guidance, Control, and Dynamics 14, no. 4 (1991): 729–35. http://dx.doi.org/10.2514/3.20706.

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30

HOUPIS, C. H., R. R. SATING, S. RASMUSSEN, and S. SHELDON. "Quantitative feedback theory technique and applications." International Journal of Control 59, no. 1 (1994): 39–70. http://dx.doi.org/10.1080/00207179408923069.

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31

YANIV, ODED, and ISAAC HOROWITZ. "Quantitative feedback theory—reply to criticisms." International Journal of Control 46, no. 3 (1987): 945–62. http://dx.doi.org/10.1080/00207178708547405.

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32

Baños, Alfonso. "Nonlinear quantitative feedback theory." International Journal of Robust and Nonlinear Control 17, no. 2-3 (2006): 181–202. http://dx.doi.org/10.1002/rnc.1104.

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33

Stevens, A. L. "Quantitative feedback theory: fundamentals and applications." Automatica 37, no. 4 (2001): 632–34. http://dx.doi.org/10.1016/s0005-1098(00)00200-4.

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34

HOROWITZ, ISAAC, and ADRIAN IOINOVICI. "Quantitative feedback theory for multiple-input-multiple output feedback systems with control input failures†." International Journal of Control 43, no. 6 (1986): 1803–21. http://dx.doi.org/10.1080/00207178608933573.

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35

Anelone, Anet J. N., María F. Villa-Tamayo, and Pablo S. Rivadeneira. "Oncolytic virus therapy benefits from control theory." Royal Society Open Science 7, no. 7 (2020): 200473. http://dx.doi.org/10.1098/rsos.200473.

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Oncolytic virus therapy aims to eradicate tumours using viruses which only infect and destroy targeted tumour cells. It is urgent to improve understanding and outcomes of this promising cancer treatment because oncolytic virus therapy could provide sensible solutions for many patients with cancer. Recently, mathematical modelling of oncolytic virus therapy was used to study different treatment protocols for treating breast cancer cells with genetically engineered adenoviruses. Indeed, it is currently challenging to elucidate the number, the schedule, and the dosage of viral injections to achie

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36

Chen, Gexin, Pengshuo Jia, Guishan Yan, et al. "Research on Feedback-Linearized Sliding Mode Control of Direct-Drive Volume Control Electro-Hydraulic Servo System." Processes 9, no. 9 (2021): 1676. http://dx.doi.org/10.3390/pr9091676.

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In this paper, a control strategy combining the feedback linearization theory and sliding mode variable structure theory is proposed to solve various nonlinear factors, uncertainty of external disturbance and high-precision pressure control problems in the Direct-Drive Volume Control (DDVC) electro-hydraulic servo system. The nonlinear mathematical model of the DDVC electro-hydraulic servo system is established, and the nonlinear factors in the system are accurately linearized by the feedback linearization theory. The uncertainty of external disturbance in the system is compensated by the slid

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37

Chua, Romeo, and Digby Elliott. "Visual control of target-directed movements." Behavioral and Brain Sciences 20, no. 2 (1997): 304–6. http://dx.doi.org/10.1017/s0140525x97241440.

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Visual feedback regulation during movement is not fully captured in Plamondon's kinematic theory. However, numerous studies indicate that visual response-produced feedback is a powerful determinant of performance and kinematic characteristics of target-directed movement.

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38

Perez, R. A., O. D. I. Nwokah, and D. F. Thompson. "Almost Decoupling by Quantitative Feedback Theory." Journal of Dynamic Systems, Measurement, and Control 115, no. 1 (1993): 27–37. http://dx.doi.org/10.1115/1.2897404.

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This paper uses almost decoupling theory to obtain a systematic solution to the MIMO-QFT problem by an n times solution of the SISO-QFT sensitivity constraint problem. This is similar to the current MIMO-QFT formulation that requires in principle an n times solution for the elements of the closed-loop transfer matrix. The problem is also in a form where direct comparison with H∞ control is feasible. However, due to the use of unstructured perturbation description, this design route along with all H∞ based design methods will invariably produce more conservative (higher bandwidth) controllers t

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39

Bagheri, S., and D. S. Henningson. "Transition delay using control theory." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 369, no. 1940 (2011): 1365–81. http://dx.doi.org/10.1098/rsta.2010.0358.

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This review gives an account of recent research efforts to use feedback control for the delay of laminar–turbulent transition in wall-bounded shear flows. The emphasis is on reducing the growth of small-amplitude disturbances in the boundary layer using numerical simulations and a linear control approach. Starting with the application of classical control theory to two-dimensional perturbations developing in spatially invariant flows, flow control based on control theory has progressed towards more realistic three-dimensional, spatially inhomogeneous flow configurations with localized sensing/

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40

Nwokah, Osita D. I., and Chin-Horng Yau. "Quantitative Feedback Design of Decentralized Control Systems." Journal of Dynamic Systems, Measurement, and Control 115, no. 2B (1993): 452–64. http://dx.doi.org/10.1115/1.2899085.

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In the spirit of practical applicability, design transparency and quantitative specifications, this paper presents a new robust decentralized control design framework—model reference quantitative feedback design (MRQFD)—for multivariable control systems with large plant uncertainty and strong cross-coupling. The MRQFD method provides a connection between Rosenbrock’s Nyquist array and Horowitz’s quantitative feedback theory. There are two main stages in the MRQFD method. First, an internal model reference loop, based on non-negative matrix theory, is used to obtain robust generalized diagonal

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41

Emary, Clive. "Delayed feedback control in quantum transport." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 371, no. 1999 (2013): 20120468. http://dx.doi.org/10.1098/rsta.2012.0468.

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Feedback control in quantum transport has been predicted to give rise to several interesting effects, among them quantum state stabilization and the realization of a mesoscopic Maxwell's daemon. These results were derived under the assumption that control operations on the system are affected instantaneously after the measurement of electronic jumps through it. In this contribution, I describe how to include a delay between detection and control operation in the master equation theory of feedback-controlled quantum transport. I investigate the consequences of delay for the state stabilization

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42

Idan, Moshe, Anthony J. Calise, and Naira Hovakimyan. "Adaptive Output Feedback Control Methodology: Theory and Practical Implementation Aspects." Journal of Guidance, Control, and Dynamics 27, no. 4 (2004): 710–15. http://dx.doi.org/10.2514/1.11166.

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43

TAKAI, Shigemasa. "State Feedback Control of Discrete Event Systems Using Lattice Theory." Transactions of the Society of Instrument and Control Engineers 32, no. 4 (1996): 533–38. http://dx.doi.org/10.9746/sicetr1965.32.533.

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44

ITO, Kazuyuki, and Kiyotaka SHIMIZU. "Dynamic Feedback Control of General Nonlinear Systems via Passivity Theory." Transactions of the Society of Instrument and Control Engineers 37, no. 1 (2001): 92–94. http://dx.doi.org/10.9746/sicetr1965.37.92.

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45

Song, Bo, Jianguo Zhao, Ning Xi, et al. "Compressive Feedback-Based Motion Control for Nanomanipulation—Theory and Applications." IEEE Transactions on Robotics 30, no. 1 (2014): 103–14. http://dx.doi.org/10.1109/tro.2013.2291619.

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46

Ali, Hazem I., Samsul Bahari B. Mohd Noor, SM Bashi, and Mohammad Hamiruce Marhaban. "Quantitative Feedback Theory control design using particle swarm optimization method." Transactions of the Institute of Measurement and Control 34, no. 4 (2011): 463–76. http://dx.doi.org/10.1177/0142331210397084.

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In this paper, a particle swarm optimization (PSO) method is proposed to design Quantitative Feedback Theory (QFT) control. This method minimizes a proposed cost function subject to appropriate robust stability and performance QFT constraints. The PSO algorithm is simple and easy to implement, and can be used to automate the loop shaping procedures of the standard QFT. The proposed method is applied to the high uncertainty pneumatic servo actuator system as an example to illustrate the design procedure of the proposed algorithm. The proposed method is compared with the standard QFT control. Th

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47

Reynolds, Odell R., M. Pachter, and C. H. Houpis. "Full envelope flight control system design using quantitative feedback theory." Journal of Guidance, Control, and Dynamics 19, no. 1 (1996): 23–29. http://dx.doi.org/10.2514/3.21575.

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48

Rao, G. S. C. N. Durga, Ch V. N. Raja, and D. Narendra Kumar. "Control of Two Link SCARA Robot Using Quantitative Feedback Theory." International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering 03, no. 12 (2014): 13755–62. http://dx.doi.org/10.15662/ijareeie.2014.0312050.

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49

Thapa Magar, Kaman, Mark Balas, Susan Frost, and Nailu Li. "Adaptive State Feedback—Theory and Application for Wind Turbine Control." Energies 10, no. 12 (2017): 2145. http://dx.doi.org/10.3390/en10122145.

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50

Benjamin, Christopher. "Feedback for enhanced student performance: lessons from simple control theory." Engineering Education 7, no. 2 (2012): 16–23. http://dx.doi.org/10.11120/ened.2012.07020016.

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