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Journal articles on the topic 'Algebraic control systems'

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Published: 4 June 2021
Last updated: 4 February 2022

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1

Legat, Benoît, and Raphaël M. Jungers. "Geometric control of algebraic systems." IFAC-PapersOnLine 54, no. 5 (2021): 79–84. http://dx.doi.org/10.1016/j.ifacol.2021.08.478.

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2

Bacciotti, Andrea. "Nonlinear control systems — an algebraic setting." Automatica 37, no. 12 (December 2001): 2079–80. http://dx.doi.org/10.1016/s0005-1098(01)00168-6.

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3

Conte, G., C. Moog, and A. Perdon. "Algebraic Methods for Nonlinear Control Systems." IEEE Transactions on Automatic Control 52, no. 12 (December 2007): 2395–96. http://dx.doi.org/10.1109/tac.2007.911476.

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4

YU, RUN-YI, and WEI-BING GAO. "Algebraic properties of decentralized control systems." International Journal of Control 50, no. 1 (July 1989): 81–88. http://dx.doi.org/10.1080/00207178908953348.

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5

Sperilă, Andrei, Florin S. Tudor, Bogdan D. Ciubotaru, and Cristian Oară. "ℋ∞ Control for Differential-Algebraic Systems." IFAC-PapersOnLine 53, no. 2 (2020): 4285–90. http://dx.doi.org/10.1016/j.ifacol.2020.12.2577.

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6

Li, Li. "H∞Control of Fractional Nonlinear Differential Systems." Advanced Materials Research 945-949 (June 2014): 2737–40. http://dx.doi.org/10.4028/www.scientific.net/amr.945-949.2737.

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In this paper, the stabilization of nonlinear fractional differential algebraic system is constructed. The fractional nonlinear differential algebraic systems (FNDAS) in presence of disturbance, we construct a fractional control strategy. The proposed stabilization and robust controller effectively take advantage of the structural characteristics of FNDAS and is simple in form.
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7

SATO, Kazuhiro. "Algebraic Controllability of Nonlinear Mechanical Control Systems." SICE Journal of Control, Measurement, and System Integration 7, no. 4 (2014): 191–98. http://dx.doi.org/10.9746/jcmsi.7.191.

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8

Roubíček, Tomáš, and Michael Valášek. "Optimal control of causal differential–algebraic systems." Journal of Mathematical Analysis and Applications 269, no. 2 (May 2002): 616–41. http://dx.doi.org/10.1016/s0022-247x(02)00040-9.

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9

Pommaret, J. "Algebraic analysis of linear multidimensional control systems." IMA Journal of Mathematical Control and Information 16, no. 3 (September 1, 1999): 275–97. http://dx.doi.org/10.1093/imamci/16.3.275.

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10

Wang, Yuan, and Eduardo D. Sontag. "Algebraic Differential Equations and Rational Control Systems." SIAM Journal on Control and Optimization 30, no. 5 (September 1992): 1126–49. http://dx.doi.org/10.1137/0330060.

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11

Grunenfelder, L. "Algebraic Aspects of Control Systems and Realizations." Journal of Algebra 165, no. 3 (May 1994): 446–64. http://dx.doi.org/10.1006/jabr.1994.1123.

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12

Ilchmann, Achim, and Jonas Kirchhoff. "Differential-algebraic systems are generically controllable and stabilizable." Mathematics of Control, Signals, and Systems 33, no. 3 (May 15, 2021): 359–77. http://dx.doi.org/10.1007/s00498-021-00287-x.

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AbstractWe investigate genericity of various controllability and stabilizability concepts of linear, time-invariant differential-algebraic systems. Based on well-known algebraic characterizations of these concepts (see the survey article by Berger and Reis (in: Ilchmann A, Reis T (eds) Surveys in differential-algebraic equations I, Differential-Algebraic Equations Forum, Springer, Berlin, pp 1–61. 10.1007/978-3-642-34928-7_1)), we use tools from algebraic geometry to characterize genericity of controllability and stabilizability in terms of matrix formats.
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13

LEE, JIN S., and P. K. C. WANG. "Feedback control of linear decentralized control systems: an algebraic approach." International Journal of Control 52, no. 6 (December 1990): 1371–90. http://dx.doi.org/10.1080/00207179008953601.

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14

Ayala, Víctor, Heriberto Román-Flores, and María Torreblanca Todco. "Control Sets of Linear Control Systems on Matrix Groups and Applications." Mathematical Problems in Engineering 2019 (July 4, 2019): 1–12. http://dx.doi.org/10.1155/2019/2963120.

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15

BELL, D. J., and X. Y. LU. "Differential algebraic control theory." IMA Journal of Mathematical Control and Information 9, no. 4 (1992): 361–83. http://dx.doi.org/10.1093/imamci/9.4.361.

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16

Shcheglova, A. A. "Controllability of nonlinear algebraic differential systems." Automation and Remote Control 69, no. 10 (October 2008): 1700–1722. http://dx.doi.org/10.1134/s0005117908100068.

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17

Roussel *, J. M., J. M. Faure, J. J. Lesage, and A. Medina §. "Algebraic approach for dependable logic control systems design." International Journal of Production Research 42, no. 14 (July 15, 2004): 2859–76. http://dx.doi.org/10.1080/00207540410001705266.

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18

Kumar, Aditya, and Prodromos Daoutidis. "Feedback control of nonlinear differential-algebraic-equation systems." AIChE Journal 41, no. 3 (March 1995): 619–36. http://dx.doi.org/10.1002/aic.690410319.

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19

Huillet, T., A. Monin, and G. Salut. "Lie algebraic canonical representations in nonlinear control systems." Mathematical Systems Theory 20, no. 1 (December 1987): 193–213. http://dx.doi.org/10.1007/bf01692065.

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20

Radisavljevic, V., and H. Baruh. "Pointwise Optimal Control of Dynamical Systems Described by Constrained Coordinates." Journal of Dynamic Systems, Measurement, and Control 121, no. 4 (December 1, 1999): 594–98. http://dx.doi.org/10.1115/1.2802521.

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A feedback control law is developed for dynamical systems described by constrained generalized coordinates. For certain complex dynamical systems, it is more desirable to develop the mathematical model using more general coordinates then degrees of freedom which leads to differential-algebraic equations of motion. Research in the last few decades has led to several advances in the treatment and in obtaining the solution of differential-algebraic equations. We take advantage of these advances and introduce the differential-algebraic equations and dependent generalized coordinate formulation to control. A tracking feedback control law is designed based on a pointwise-optimal formulation. The stability of pointwise optimal control law is examined.
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21

Aleksandrov, A. G. "Algebraic nonrobustness conditions." Automation and Remote Control 70, no. 9 (September 2009): 1487–98. http://dx.doi.org/10.1134/s0005117909090033.

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22

Raj, Phani, and Debasattam Pal. "Lie-Algebraic Criterion for Stability of Switched Differential-Algebraic Equations." IFAC-PapersOnLine 53, no. 2 (2020): 2004–9. http://dx.doi.org/10.1016/j.ifacol.2020.12.2702.

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23

NIU, HONG, and QINGLING ZHANG. "GENERALIZED PREDICTIVE CONTROL FOR DIFFERENCE-ALGEBRAIC BIOLOGICAL ECONOMIC SYSTEMS." International Journal of Biomathematics 06, no. 06 (November 2013): 1350037. http://dx.doi.org/10.1142/s179352451350037x.

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In this paper, a nonlinear difference-algebraic system is used to model some populations with stage structure when the harvest behavior and the economic interest are considered. The stability analysis is studied at the equilibrium points. After the nonlinear difference-algebraic system is changed into a linear system with the unmodeled dynamics, a generalized predictive controller with feedforward compensator is designed to stabilize the system. Adaptive-network-based fuzzy inference system (ANFIS) is used to make the unmodeled dynamic compensated. An example illustrates the effectiveness of the proposed control method.
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24

Pan, Somnath, and Jayanta Pal. "Discretization of Existing Continuous Control Systems." Journal of Dynamic Systems, Measurement, and Control 119, no. 2 (June 1, 1997): 315–18. http://dx.doi.org/10.1115/1.2801255.

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A new method is presented for discretizing an existing analog controller. The method is based on frequency response matching of the closed-loop digital system with that of the original analog system. The method requires solution of linear algebraic equations and is computationally simple. Efficacy of the method is illustrated through examples taken from the literature.
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25

van der Schaft, Arjan, and Bernhard Maschke. "Dirac and Lagrange Algebraic Constraints in Nonlinear Port-Hamiltonian Systems." Vietnam Journal of Mathematics 48, no. 4 (June 18, 2020): 929–39. http://dx.doi.org/10.1007/s10013-020-00419-x.

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AbstractAfter recalling the definitions of standard port-Hamiltonian systems and their algebraic constraints, called here Dirac algebraic constraints, an extended class of port-Hamiltonian systems is introduced. This is based on replacing the Hamiltonian function by a general Lagrangian submanifold of the cotangent bundle of the state space manifold, motivated by developments in (Barbero-Linan et al., J. Geom. Mech. 11, 487–510, 2019) and extending the linear theory as developed in (van der Schaft and Maschke, Syst. Control Lett. 121, 31–37, 2018) and (Beattie et al., Math. Control Signals Syst. 30, 17, 2018). The resulting new type of algebraic constraints equations are called Lagrange algebraic constraints. It is shown how Dirac algebraic constraints can be converted into Lagrange algebraic constraints by the introduction of extra state variables, and, conversely, how Lagrange algebraic constraints can be converted into Dirac algebraic constraints by the use of Morse families.
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26

Lessard, Laurent, and Sanjay Lall. "An Algebraic Approach to the Control of Decentralized Systems." IEEE Transactions on Control of Network Systems 1, no. 4 (December 2014): 308–17. http://dx.doi.org/10.1109/tcns.2014.2357501.

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27

Kumar, Aditya, and Prodromos Daoutidis. "Control of Nonlinear Differential-Algebraic-Equation Systems with Disturbances." Industrial & Engineering Chemistry Research 34, no. 6 (June 1995): 2060–76. http://dx.doi.org/10.1021/ie00045a015.

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28

Xiaoping, Liu. "Asymptotic output tracking of nonlinear differential-algebraic control systems." Automatica 34, no. 3 (March 1998): 393–97. http://dx.doi.org/10.1016/s0005-1098(97)00224-0.

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29

Liu, X. P., S. Rohani, and A. Jutan. "Tracking control of general nonlinear differential-algebraic equation systems." AIChE Journal 49, no. 7 (July 2003): 1743–60. http://dx.doi.org/10.1002/aic.690490713.

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30

GRUJIĆ, LJUBOMIR T. "Algebraic conditions for absolute tracking control of Lurie systems." International Journal of Control 48, no. 2 (August 1988): 729–54. http://dx.doi.org/10.1080/00207178808906207.

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31

Sperila, Andrei, Cristian Oara, and Bogdan D. Ciubotaru. "H 2 Output Feedback Control of Differential-Algebraic Systems." IEEE Control Systems Letters 6 (2022): 542–47. http://dx.doi.org/10.1109/lcsys.2021.3083399.

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32

Agrachev, Andrei A., and Daniel Liberzon. "Lie-Algebraic Stability Criteria for Switched Systems." SIAM Journal on Control and Optimization 40, no. 1 (January 2001): 253–69. http://dx.doi.org/10.1137/s0363012999365704.

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33

Willems, J. C. "Algebraic theory for multivariable linear systems." Automatica 21, no. 1 (January 1985): 109–10. http://dx.doi.org/10.1016/0005-1098(85)90103-7.

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34

CLARK, JOHN W., DENNIS G. LUCARELLI, and TZYH-JONG TARN. "CONTROL OF QUANTUM SYSTEMS." International Journal of Modern Physics B 17, no. 28 (November 10, 2003): 5397–411. http://dx.doi.org/10.1142/s021797920302051x.

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A quantum system subject to external fields is said to be controllable if these fields can be adjusted to guide the state vector to a desired destination in the state space of the system. Fundamental results on controllability are reviewed against the background of recent ideas and advances in two seemingly disparate endeavours: (i) laser control of chemical reactions and (ii) quantum computation. Using Lie-algebraic methods, sufficient conditions have been derived for global controllability on a finite-dimensional manifold of an infinite-dimensional Hilbert space, in the case that the Hamiltonian and control operators, possibly unbounded, possess a common dense domain of analytic vectors. Some simple examples are presented. A synergism between quantum control and quantum computation is creating a host of exciting new opportunities for both activities. The impact of these developments on computational many-body theory could be profound.
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35

LU, X. Y., and D. J. BELL. "Realization theory for differential algebraic input-output systems." IMA Journal of Mathematical Control and Information 10, no. 1 (1993): 33–47. http://dx.doi.org/10.1093/imamci/10.1.33.

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36

Zhang, Sheng, En-Mi Yong, Yu Zhou, and Wei-Qi Qian. "Dynamic backstepping control for pure-feedback non-linear systems." IMA Journal of Mathematical Control and Information 37, no. 2 (August 14, 2019): 674–97. http://dx.doi.org/10.1093/imamci/dnz019.

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Abstract A dynamic backstepping control method is proposed for non-linear systems in the pure-feedback form, for which the traditional backstepping method suffers from solving the implicit non-linear algebraic equation. This method treats the implicit algebraic equation directly via a dynamic way, by augmenting the (virtual) controls as states during each recursive step. Compared with the traditional backstepping method, one more Lyapunov design is executed in each step. As new dynamics are included in the design, the resulting control law is in the dynamic feedback form. Under appropriate assumptions, the proposed control scheme achieves the uniformly asymptotic stability and the closed-loop system is local input-to-state stable for various disturbance. Moreover, the control law may be simplified to the inverse-free form by setting large gains, which will alleviate the problem of `explosion of terms’. The effectiveness of this method is illustrated by the stabilization and tracking numerical examples.
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37

WON, C. H., and S. Biswas. "Optimal control using an algebraic method for control-affine non-linear systems." International Journal of Control 80, no. 9 (September 2007): 1491–502. http://dx.doi.org/10.1080/00207170701411375.

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38

TAUBER, SELMO. "ALGEBRAIC MODELS FOR MERGING SYSTEMS." International Journal of General Systems 11, no. 1 (April 1985): 79–88. http://dx.doi.org/10.1080/03081078508934901.

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39

Diop, Sette. "On sensor selection for differential algebraic systems observability." IFAC-PapersOnLine 53, no. 2 (2020): 4334–38. http://dx.doi.org/10.1016/j.ifacol.2020.12.2584.

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40

Adigu¨zel, E., and H. O¨z. "Direct Optimal Control of Nonlinear Systems Via Hamilton’s Law of Varying Action." Journal of Dynamic Systems, Measurement, and Control 117, no. 3 (September 1, 1995): 262–69. http://dx.doi.org/10.1115/1.2799115.

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Based on direct application of Hamilton’s Law of Varying Action in conjunction with an assumed-time-modes approach for both the generalized coordinates and input functions, a direct optimal control methodology is developed for the control of nonlinear, time varying, spatially discrete mechanical systems. Expansion coefficients of admissible time modes for the dependent variables of the dynamic system and those for the inputs constitute the states and controls, respectively. This representation permits explicit a priori integration in time of the energy expressions in Hamilton’s law and leads to the algebraic equations of motion for the system which replace the conventional differential state equations; therefore the customary extremum principles of calculus of variations involving differential form constraints are also bypassed. Similarly, the standard integral form of the quadratic regulator performance measure employed in the formulation of the optimality problem is transformed into an algebraic performance measure via assumed-time-modes expansion of the generalized coordinates and the control inputs. The proposed methodology results in an algebraic optimality problem from which a closed-form explicit solution for the nonlinear feedback control law is obtained directly. Simulations of two nonlinear nonconservative systems are, included.
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41

HOFFMANN, J. "Algebraic aspects of controllability for AR-systems." International Journal of Control 60, no. 5 (November 1994): 715–32. http://dx.doi.org/10.1080/00207179408921491.

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42

BANKS, S. P. "On non-linear systems and algebraic geometry." International Journal of Control 42, no. 2 (August 1985): 333–52. http://dx.doi.org/10.1080/00207178508933367.

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43

Zhang, Tiehui, Jun Liu, Hengyu Li, Shaorong Xie, and Luo Jun. "Group consensus coordination control in networked nonholonomic multirobot systems." International Journal of Advanced Robotic Systems 18, no. 4 (July 1, 2021): 172988142110277. http://dx.doi.org/10.1177/17298814211027701.

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In this article, the coordination control problem of group tracking consensus is considered for networked nonholonomic mobile multirobot systems (NNMMRSs). This problem framework generalizes the findings of complete consensus in NNMMRSs and group consensus in networked Lagrangian systems (NLSs), enjoying capacious application backgrounds. By leveraging a kinematic controller embedded in the adaptive torque control protocols, a new convergence criterion of group consensus is established. In contrast to the formulation under strict algebraic assumptions, it is found that group tracking consensus for NNMMRSs can be realized under a simple geometrical condition. The system stability analysis is dictated by the property of network topology with acyclic partition. Finally, the theoretical achievements are verified by illustrative numerical examples. The results show an interesting phenomenon that, for NNMMRSs, the state responses exhibit negative correlation with the algebraic connectivity and coupling strength.
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44

Kallrath, Josef. "Polylithic modeling and solution approaches using algebraic modeling systems." Optimization Letters 5, no. 3 (April 8, 2011): 453–66. http://dx.doi.org/10.1007/s11590-011-0320-4.

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45

Vykhovanets, V. S. "Algebraic decomposition of discrete functions." Automation and Remote Control 67, no. 3 (March 2006): 361–92. http://dx.doi.org/10.1134/s0005117906030039.

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46

Szabó, Z., and J. Bokor. "Feedback stabilization: the algebraic view." IFAC-PapersOnLine 53, no. 2 (2020): 4421–27. http://dx.doi.org/10.1016/j.ifacol.2020.12.375.

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47

Lund, Carsten, Lance Fortnow, Howard Karloff, and Noam Nisan. "Algebraic methods for interactive proof systems." Journal of the ACM 39, no. 4 (October 1992): 859–68. http://dx.doi.org/10.1145/146585.146605.

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48

Hillmann, Christian, and Olaf Stursberg. "Algebraic Synthesis for Online Adaptation of Dependable Discrete Control Systems." IFAC Proceedings Volumes 46, no. 22 (2013): 61–66. http://dx.doi.org/10.3182/20130904-3-uk-4041.00041.

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49

Chen, Lingshan, and Xiaoping Liu. "Noninteracting Control for a Class of Nonlinear Differential-Algebraic Systems." IFAC Proceedings Volumes 29, no. 1 (June 1996): 2126–31. http://dx.doi.org/10.1016/s1474-6670(17)57986-0.

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50

ZANG, Qiang, and Xian-Zhong DAI. "Output Feedback Stabilization Control for Nonlinear Di.erential-algebraic Equation Systems." Acta Automatica Sinica 35, no. 9 (November 13, 2009): 1244–48. http://dx.doi.org/10.3724/sp.j.1004.2009.01244.

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