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Journal articles on the topic 'Dynamic output feedback'

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Published: 4 June 2021
Last updated: 8 June 2024

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1

Verschelde, J., and Y. Wang. "Computing Dynamic Output Feedback Laws." IEEE Transactions on Automatic Control 49, no. 8 (August 2004): 1393–97. http://dx.doi.org/10.1109/tac.2004.832680.

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2

Zohdy, M. A., A. A. Abdul-Wahab, N. K. Loh, and Jun Liu. "On Robust Parametric Dynamic Output Feedback." Journal of Dynamic Systems, Measurement, and Control 112, no. 3 (September 1, 1990): 507–12. http://dx.doi.org/10.1115/1.2896172.

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This paper presents a new and unified treatment of feedback control for linear multivariable time-invariant systems, using reduced-order dynamic output feedback to recover state feedback properties. A set of free design parameters are effectively exploited in achieving desirable performance tradeoffs, through solving Lyapunov-like matrix equations.
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3

Larsen, M., and P. V. Kokotovic. "On passivation with dynamic output feedback." IEEE Transactions on Automatic Control 45, no. 6 (June 2001): 962–67. http://dx.doi.org/10.1109/9.928608.

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4

PING, Xu-Bin, Bao-Cang DING, and Chong-Zhao HAN. "Dynamic Output Feedback Robust Model Predictive Control." Acta Automatica Sinica 38, no. 1 (December 14, 2012): 31–37. http://dx.doi.org/10.3724/sp.j.1004.2012.00031.

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5

CHEN, CHERN-LIN, and YUAN-YIH HSU. "Pole assignment using dynamic output feedback compensators." International Journal of Control 45, no. 6 (June 1987): 1985–94. http://dx.doi.org/10.1080/00207178708933861.

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6

Suykens, J. A. K., P. F. Curran, and L. O. Chua. "Master-Slave Synchronization Using Dynamic Output Feedback." International Journal of Bifurcation and Chaos 07, no. 03 (March 1997): 671–79. http://dx.doi.org/10.1142/s0218127497000467.

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A method of linear dynamic output feedback for master-slave synchronization of two identical Lur'e systems is introduced. In this scheme, synchronization is obtained using one or at least fewer measurement signals and control signals than the number of state variables of the Lur'e system. A sufficient condition for global asymptotic stability of the error system is derived from a quadratic Lyapunov function and is expressed as a matrix inequality. The dynamic controller is designed by solving a constrained nonlinear optimization problem. The method is demonstrated on Chua's circuit and a hyperchaotic circuit consisting of 2-double scroll cells.
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7

Ozguler, A., and V. Eldem. "Disturbance decoupling problems via dynamic output feedback." IEEE Transactions on Automatic Control 30, no. 8 (August 1985): 756–64. http://dx.doi.org/10.1109/tac.1985.1104046.

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8

Rodrigues, M. A., and D. Odloak. "Robust Stable MPC via Dynamic Output Feedback." IFAC Proceedings Volumes 33, no. 10 (June 2000): 809–14. http://dx.doi.org/10.1016/s1474-6670(17)38639-1.

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9

Aldeen, M. "A Low Order Output Feedback Dynamic Controller." IFAC Proceedings Volumes 28, no. 10 (July 1995): 67–71. http://dx.doi.org/10.1016/s1474-6670(17)51494-9.

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10

Rosenthal, J., and X. A. Wang. "Output feedback pole placement with dynamic compensators." IEEE Transactions on Automatic Control 41, no. 6 (June 1996): 830–43. http://dx.doi.org/10.1109/9.506235.

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11

Han, Cun Wu, De Hui Sun, Lei Liu, and Song Bi. "Adaptive Congestion Control via Dynamic Output Feedback." Applied Mechanics and Materials 571-572 (June 2014): 30–33. http://dx.doi.org/10.4028/www.scientific.net/amm.571-572.30.

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This paper presents an adaptive congestion control algorithm for Internet with time-varying uncertainties. The controller is designed via dynamic output feedback. Simulation result shows that the proposed algorithm has good performance.
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12

Ding, Baocang, Biao Huang, and Fangwei Xu. "Dynamic output feedback robust model predictive control." International Journal of Systems Science 42, no. 10 (October 2011): 1669–82. http://dx.doi.org/10.1080/00207721003624543.

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13

He, Tianyi, Guoming G. Zhu, and Sean S. M. Swei. "Smooth Switching LPV Dynamic Output-feedback Control." International Journal of Control, Automation and Systems 18, no. 6 (December 26, 2019): 1367–77. http://dx.doi.org/10.1007/s12555-019-0088-3.

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14

Larin, V. B., and A. A. Tunik. "Dynamic output feedback compensation of external disturbances." International Applied Mechanics 42, no. 5 (May 2006): 606–16. http://dx.doi.org/10.1007/s10778-006-0128-6.

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15

Hovakimyan, Naira, Rolf Rysdyk, and Anthony J. Calise. "Dynamic neural networks for output feedback control." International Journal of Robust and Nonlinear Control 11, no. 1 (2000): 23–39. http://dx.doi.org/10.1002/1099-1239(200101)11:1<23::aid-rnc545>3.0.co;2-n.

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16

Amato, Francesco, Marco Ariola, and Carlo Cosentino. "Finite-time stabilization via dynamic output feedback." Automatica 42, no. 2 (February 2006): 337–42. http://dx.doi.org/10.1016/j.automatica.2005.09.007.

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17

Chang, Jeang-Lin. "Dynamic Output Feedback Disturbance Rejection Controller Design." Asian Journal of Control 15, no. 2 (May 31, 2012): 606–13. http://dx.doi.org/10.1002/asjc.544.

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18

Marino, Riccardo, and Patrizio Tomei. "Dynamic output feedback linearization and global stabilization." Systems & Control Letters 17, no. 2 (August 1991): 115–21. http://dx.doi.org/10.1016/0167-6911(91)90036-e.

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19

Battilotti, S. "Stabilization via dynamic output feedback for systems with output nonlinearities." Systems & Control Letters 23, no. 6 (December 1994): 411–19. http://dx.doi.org/10.1016/0167-6911(94)90095-7.

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20

Snippe, H. P., and J. H. van Hateren. "Dynamics of Nonlinear Feedback Control." Neural Computation 19, no. 5 (May 2007): 1179–214. http://dx.doi.org/10.1162/neco.2007.19.5.1179.

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Feedback control in neural systems is ubiquitous. Here we study the mathematics of nonlinear feedback control. We compare models in which the input is multiplied by a dynamic gain (multiplicative control) with models in which the input is divided by a dynamic attenuation (divisive control). The gain signal (resp. the attenuation signal) is obtained through a concatenation of an instantaneous nonlinearity and a linear low-pass filter operating on the output of the feedback loop. For input steps, the dynamics of gain and attenuation can be very different, depending on the mathematical form of the nonlinearity and the ordering of the nonlinearity and the filtering in the feedback loop. Further, the dynamics of feedback control can be strongly asymmetrical for increment versus decrement steps of the input. Nevertheless, for each of the models studied, the nonlinearity in the feedback loop can be chosen such that immediately after an input step, the dynamics of feedback control is symmetric with respect to increments versus decrements. Finally, we study the dynamics of the output of the control loops and find conditions under which overshoots and undershoots of the output relative to the steady-state output occur when the models are stimulated with low-pass filtered steps. For small steps at the input, overshoots and undershoots of the output do not occur when the filtering in the control path is faster than the low-pass filtering at the input. For large steps at the input, however, results depend on the model, and for some of the models, multiple overshoots and undershoots can occur even with a fast control path.
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21

Liu, Qing Quan. "Dynamic Output Feedback Control with a Preview of Disturbance." Advanced Materials Research 433-440 (January 2012): 7089–96. http://dx.doi.org/10.4028/www.scientific.net/amr.433-440.7089.

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This paper addresses the dynamic output feedback stabilization problem for linear time-invariant systems where the process disturbance preview is available to the controller via communication networks. A lower bound of data rates of communication channels, above which there exists a feedback control policy to stabilize the unstable plant with unbounded disturbance, is presented. Furthermore, the problem of bandwidth allocation in the communication channel is analyzed based on the system dynamics. Simulation results show the validity of the proposed scheme.
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22

Yang, Qiang, Ming Zhu, Tao Jiang, Jin He, Jianying Yuan, and Jianda Han. "Decentralized Robust Adaptive Output Feedback Stabilization for Interconnected Nonlinear Systems with Uncertainties." Journal of Control Science and Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/3656578.

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Based on adaptive nonlinear damping, a novel decentralized robust adaptive output feedback stabilization comprising a decentralized robust adaptive output feedback controller and a decentralized robust adaptive observer is proposed for a large-scale interconnected nonlinear system with general uncertainties, such as unknown nonlinear parameters, bounded disturbances, unknown nonlinearities, unmodeled dynamics, and unknown interconnections, which are nonlinear function of not only states and outputs but also unmodeled dynamics coming from other subsystems. In each subsystem, the proposed stabilization only has two adaptive parameters, and it is not needed to generate an additional dynamic signal or estimate the unknown parameters. Under certain assumptions, the proposed scheme guarantees that all the dynamic signals in the interconnected nonlinear system are bounded. Furthermore, the system states and estimate errors can approach arbitrarily small values by choosing the design parameters appropriately large. Finally, simulation results illustrated the effectiveness of the proposed scheme.
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23

Kaldmäe, Arvo, and Ülle Kotta. "Input–output linearization of discrete-time systems by dynamic output feedback." European Journal of Control 20, no. 2 (March 2014): 73–78. http://dx.doi.org/10.1016/j.ejcon.2013.12.004.

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24

Tong, Shaocheng, Changliang Liu, and Yongming Li. "Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systems." International Journal of Applied Mathematics and Computer Science 20, no. 4 (December 1, 2010): 637–53. http://dx.doi.org/10.2478/v10006-010-0047-x.

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Robust adaptive fuzzy filters output feedback control of strict-feedback nonlinear systemsIn this paper, an adaptive fuzzy robust output feedback control approach is proposed for a class of single input single output (SISO) strict-feedback nonlinear systems without measurements of states. The nonlinear systems addressed in this paper are assumed to possess unstructured uncertainties, unmodeled dynamics and dynamic disturbances, where the unstructured uncertainties are not linearly parameterized, and no prior knowledge of their bounds is available. In recursive design, fuzzy logic systems are used to approximate unstructured uncertainties, and K-filters are designed to estimate unmeasured states. By combining backstepping design and a small-gain theorem, a stable adaptive fuzzy output feedback control scheme is developed. It is proven that the proposed adaptive fuzzy control approach can guarantee the all the signals in the closed-loop system are uniformly ultimately bounded, and the output of the controlled system converges to a small neighborhood of the origin. The effectiveness of the proposed approach is illustrated by a simulation example and some comparisons.
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25

Ristevski, Stefan, K. Merve Dogan, Tansel Yucelen, and Jonathan A. Muse. "Output Feedback Adaptive Control of Uncertain Dynamic Systems with Actuator Dynamics." Journal of Guidance, Control, and Dynamics 44, no. 12 (December 2021): 2311–17. http://dx.doi.org/10.2514/1.g005782.

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26

Geromel, JosÉ C., Patrizio Colaneri, and Paolo Bolzern. "Dynamic Output Feedback Control of Switched Linear Systems." IEEE Transactions on Automatic Control 53, no. 3 (April 2008): 720–33. http://dx.doi.org/10.1109/tac.2008.919860.

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27

Araújo, José M., Péricles R. Barros, and Carlos ET Dórea. "Dynamic output feedback control of constrained descriptor systems." Transactions of the Institute of Measurement and Control 35, no. 8 (June 25, 2013): 1129–38. http://dx.doi.org/10.1177/0142331213487921.

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28

Wang, Gexia, and Zhiming Wang. "Dynamic output feedback of linear networked control systems." Automation and Remote Control 69, no. 3 (March 2008): 412–18. http://dx.doi.org/10.1134/s0005117908030077.

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29

Schmitendorf, W. E., and W. Schirm. "Stabilization via dynamic output feedback - A numerical approach." Journal of Guidance, Control, and Dynamics 14, no. 5 (September 1991): 1083–86. http://dx.doi.org/10.2514/3.20760.

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30

Kazemy, Ali, Xian-Ming Zhang, and Qing-Long Han. "Dynamic output feedback control for seismic-excited buildings." Journal of Sound and Vibration 411 (December 2017): 88–107. http://dx.doi.org/10.1016/j.jsv.2017.08.017.

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31

Lu, Guo-ping, Yu-fan Zheng, and Daniel W. C. Ho. "Nonlinear robust H∞ control via dynamic output feedback." Systems & Control Letters 39, no. 3 (March 2000): 193–202. http://dx.doi.org/10.1016/s0167-6911(99)00086-9.

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32

Bezrodnyi, V. I., L. V. Vovk, E. I. Zabello, and E. A. Tikhonov. "Output kinetics of lasers with dynamic distributed feedback." Journal of Applied Spectroscopy 46, no. 1 (January 1987): 31–36. http://dx.doi.org/10.1007/bf00660278.

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33

Ferrante, Francesco, and Luca Zaccarian. "Dynamic reset output feedback with guaranteed convergence rate." IFAC-PapersOnLine 52, no. 16 (2019): 102–7. http://dx.doi.org/10.1016/j.ifacol.2019.11.763.

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34

Han, Z. X., G. Feng, B. L. Walcott, and J. Ma. "Dynamic output feedback controller design for fuzzy systems." IEEE Transactions on Systems, Man and Cybernetics, Part B (Cybernetics) 30, no. 1 (2000): 204–10. http://dx.doi.org/10.1109/3477.826962.

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35

Ilchmann, A., and A. Isidori. "Adaptive Dynamic Output Feedback Stabilisation of Nonlinear Systems." Asian Journal of Control 4, no. 3 (October 22, 2008): 246–54. http://dx.doi.org/10.1111/j.1934-6093.2002.tb00352.x.

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36

Daoutidis, Prodromos, and Panagiotis D. Christofides. "Dynamic feedforward/output feedback control of nonlinear processes." Chemical Engineering Science 50, no. 12 (June 1995): 1889–907. http://dx.doi.org/10.1016/0009-2509(95)00016-x.

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37

Edwards, Christopher, Nai One Lai, and Sarah K. Spurgeon. "On discrete dynamic output feedback min–max controllers." Automatica 41, no. 10 (October 2005): 1783–90. http://dx.doi.org/10.1016/j.automatica.2005.05.003.

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38

Song, Xiaona, and Zhen Wang. "Dynamic Output Feedback Control for Fractional-Order Systems." Asian Journal of Control 15, no. 3 (August 24, 2012): 834–48. http://dx.doi.org/10.1002/asjc.592.

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39

Brivadis, Lucas, Jean-Paul Gauthier, Ludovic Sacchelli, and Ulysse Serres. "New perspectives on output feedback stabilization at an unobservable target." ESAIM: Control, Optimisation and Calculus of Variations 27 (2021): 102. http://dx.doi.org/10.1051/cocv/2021097.

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We address the problem of dynamic output feedback stabilization at an unobservable target point. The challenge lies in according the antagonistic nature of the objective and the properties of the system: the system tends to be less observable as it approaches the target. We illustrate two main ideas: well chosen perturbations of a state feedback law can yield new observability properties of the closed-loop system, and embedding systems into bilinear systems admitting observers with dissipative error systems allows to mitigate the observability issues. We apply them on a case of systems with linear dynamics and nonlinear observation map and make use of an ad hoc finite-dimensional embedding. More generally, we introduce a new strategy based on infinite-dimensional unitary embeddings. To do so, we extend the usual definition of dynamic output feedback stabilization in order to allow infinite-dimensional observers fed by the output. We show how this technique, based on representation theory, may be applied to achieve output feedback stabilization at an unobservable target.
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40

Min, Yang, Xiaoli Luan, Zhengtao Ding, and Fei Liu. "Given-time consensus for stochastic Markov jump networks by dynamic output feedback." Transactions of the Institute of Measurement and Control 40, no. 10 (August 1, 2017): 3160–68. http://dx.doi.org/10.1177/0142331217718618.

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This paper focuses on the given-time consensus of stochastic Markov jump networks with disturbances based on dynamic output feedback control. By exploring the relative output information, a distributed dynamic output feedback protocol is designed to guarantee that the disagreement dynamics of networks keeps within the prescribed bound in a fixed time interval. With the new model transformation approach, the obtained results are more general and lead to less conservativeness. An example of industrial material heating unit verifies the engineering application of the proposed algorithm for networks in the presence of both Markov jump topologies and external disturbances.
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41

Dong, Xiwang, Fanlin Meng, Zongying Shi, Geng Lu, and Yisheng Zhong. "Output containment control for swarm systems with general linear dynamics: A dynamic output feedback approach." Systems & Control Letters 71 (September 2014): 31–37. http://dx.doi.org/10.1016/j.sysconle.2014.06.007.

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42

Zhang, Xiaoyu, Wei He, and Yanqin Zhang. "An Adaptive Output Feedback Controller for Boost Converter." Electronics 11, no. 6 (March 15, 2022): 905. http://dx.doi.org/10.3390/electronics11060905.

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The main contribution of this paper is to propose an adaptive reduced-order state observer for boost converter to reconstruct the inductor current and load conductance. Note that the unknown parameter appears in the output dynamics, which poses a detectability obstacle, imposing a more stringent requirement on the system behavior. As a result, the design of an adaptive reduced-order state observer is more challenging. In this paper, using the dynamic extension technique, we transform the state observation into the parameter estimation. Constructing the parameter observer, the current and load conductance can be estimated. Introducing the estimated terms to a saturated PI passivity-based control, an adaptive output feedback saturated controller is presented. To assess the control performance, the simulation and experimental results are given.
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43

Kazantzidou, Christina, Robert Schmid, and Lorenzo Ntogramatzidis. "Nonovershooting state feedback and dynamic output feedback tracking controllers for descriptor systems." International Journal of Control 91, no. 8 (June 15, 2017): 1785–800. http://dx.doi.org/10.1080/00207179.2017.1331377.

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44

Zhou, Kai, Min Ai, Dongyang Sun, Ningzhi Jin, and Xiaogang Wu. "Field Weakening Operation Control Strategies of PMSM Based on Feedback Linearization." Energies 12, no. 23 (November 28, 2019): 4526. http://dx.doi.org/10.3390/en12234526.

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Based on current research into the mathematical model of the permanent magnet synchronous motor (PMSM) and the feedback linearization theory, a control strategy established upon feedback linearization is proposed. The Lie differential operation is performed on the output variable to obtain the state feedback of the nonlinear system, and the dynamic characteristics of the original system are transformed into linear dynamic characteristics. A current controller based on the input–output feedback linearization algorithm is designed to realize the input–output linearization control of the PMSM. The current controller decouples the d–q axis current from the flux linkage information of the motor and outputs a control voltage. When the motor speed reaches above the base speed, the field-forward and straight-axis current components are newly distributed to achieve field weakening control, which can realize the smooth transition between the constant torque region and weak magnetic region. Simulation and experimental results show the feasibility and viability of the strategy.
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45

Matsumura, Fumio, Masayuki Fujita, and Kazuhiro Hatake. "Output Regulation in Magnetic Bearing Systems by a Dynamic Output Feedback Controller." IEEJ Transactions on Industry Applications 112, no. 10 (1992): 977–83. http://dx.doi.org/10.1541/ieejias.112.977.

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46

Lai, Nai One, Christopher Edwards, and Sarah K. Spurgeon. "On Output Tracking Using Dynamic Output Feedback Discrete-Time Sliding-Mode Controllers." IEEE Transactions on Automatic Control 52, no. 10 (October 2007): 1975–81. http://dx.doi.org/10.1109/tac.2007.904256.

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47

Schmid, Robert, and Hassan Dehghani Aghbolagh. "Nonovershooting Cooperative Output Regulation of Linear Multiagent Systems by Dynamic Output Feedback." IEEE Transactions on Control of Network Systems 6, no. 2 (June 2019): 526–36. http://dx.doi.org/10.1109/tcns.2018.2846180.

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48

Li, Shaobao, Gang Feng, Juan Wang, Xiaoyuan Luo, and Xinping Guan. "Cooperative linear output regulation for networked systems by dynamic measurement output feedback." International Journal of Systems Science 47, no. 6 (July 3, 2014): 1445–52. http://dx.doi.org/10.1080/00207721.2014.932468.

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49

Ping, Xubin, Bo Qian, and Ning Sun. "Dynamic Output Feedback Robust MPC with Input Saturation Based on Zonotopic Set-Membership Estimation." Mathematical Problems in Engineering 2016 (2016): 1–13. http://dx.doi.org/10.1155/2016/5292375.

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For quasi-linear parameter varying (quasi-LPV) systems with bounded disturbance, a synthesis approach of dynamic output feedback robust model predictive control (OFRMPC) with the consideration of input saturation is investigated. The saturated dynamic output feedback controller is represented by a convex hull involving the actual dynamic output controller and an introduced auxiliary controller. By taking both the actual output feedback controller and the auxiliary controller with a parameter-dependent form, the main optimization problem can be formulated as convex optimization. The consideration of input saturation in the main optimization problem reduces the conservatism of dynamic output feedback controller design. The estimation error set and bounded disturbance are represented by zonotopes and refreshed by zonotopic set-membership estimation. Compared with the previous results, the proposed algorithm can not only guarantee the recursive feasibility of the optimization problem, but also improve the control performance at the cost of higher computational burden. A nonlinear continuous stirred tank reactor (CSTR) example is given to illustrate the effectiveness of the approach.
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50

Mitkowski, Wojciech, Waldemar Bauer, and Marta Zagórowska. "Discrete-time feedback stabilization." Archives of Control Sciences 27, no. 2 (June 1, 2017): 309–22. http://dx.doi.org/10.1515/acsc-2017-0020.

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Abstract This paper presents an algorithm for designing dynamic compensator for infinitedimensional systems with bounded input and bounded output operators using finite dimensional approximation. The proposed method was then implemented in order to find the control function for thin rod heating process. The optimal sampling time was found depending on discrete output measurements.
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