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Dr. Alexander Semionovich Poznyak Gorbatch: Biography

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New Perspectives and Applications of Modern Control Theory

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Abstract

Alexander S. Poznyak (Alexander Semion Pozniak Gorbatch) was born on December 6, 1946 in Moscow and graduated from Moscow Physical Technical Institute (MPhTI) in 1970. He earned Ph.D. and Doctor Degrees from the Institute of Control Sciences of Russian Academy of Sciences in 1978 and 1989, respectively. From 1973 up to 1993, he served in this institute as researcher and leading researcher, and in 1993 he accepted a post of full professor (3-F) at CINVESTAV of IPN in Mexico.

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Books, Articles and Conferences

  1. Aguilar, R., Martinez-Guerra, R., Poznyak, A.S.: Nonlinear PID controller for the regulation of fixed bed bioreactors. In: Proceedings of the 41st IEEE Conference on Decision and Control, vol. 4, pp. 4126–4131 (2002). https://doi.org/10.1109/CDC.2002.1185014

  2. Alazki, H., Ordaz, P., Poznyak, A.S.: Robust bounded control for the flexible arm robot. In: Proceedings of the 52nd IEEE Conference on Decision and Control, pp. 3061–3066 (2013). https://doi.org/10.1109/CDC.2013.6760349

  3. Alazki, H., Poznyak, A.S.: Output linear feedback tracking for discrete-time stochastic model using robust attractive ellipsoid method with LMI application. In: Proceedings of the 2009 6th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE), pp. 1–6 (2009). https://doi.org/10.1109/ICEEE.2009.5393429

  4. Alazki, H., Poznyak, A.S.: Constraint robust stochastic discrete-time tracking: attractive ellipsoids technique. In: Proceedings of the 7th International Conference on Electrical Engineering Computing Science and Automatic Control, pp. 99–104 (2010). https://doi.org/10.1109/ICEEE.2010.5608567

  5. Alazki, H., Poznyak, A.S.: Probabilistic analysis of robust attractive ellipsoids for quasi-linear discrete-time models. In: Proceedings of the 49th IEEE Conference on Decision and Control (CDC), pp. 579–584 (2010). https://doi.org/10.1109/CDC.2010.5717662

  6. Alazki, H., Poznyak, A.S.: Averaged attractive ellipsoid technique applied to inventory projectional control with uncertain stochastic demands. In: Proceedings of the 50th IEEE Conference on Decision and Control and European Control Conference, pp. 2082–2087 (2011). https://doi.org/10.1109/CDC.2011.6160847

  7. Alazki, H., Poznyak, A.S.: Robust stochastic tracking for discrete-time models: designing of ellipsoid where random trajectories converge with probability one. Int. J. Syst. Sci. 43(8), 1519–1533 (2012). https://doi.org/10.1080/00207721.2010.547664

  8. Alazki, H., Poznyak, A.S.: A class of robust bounded controllers tracking a nonlinear discrete-time stochastic system: attractive ellipsoid technique application. J. Frankl. Inst. Eng. Appl. Math. 350(5), 1008–1029 (2013). https://doi.org/10.1016/j.jfranklin.2013.02.001

  9. Alazki, H., Poznyak, A.S.: Robust output stabilization for a class of nonlinear uncertain stochastic systems under multiplicative and additive noises: the attractive ellipsoid method. J. Ind. Manag. Optim. 12(1), 169–186 (2016). https://doi.org/10.3934/jimo.2016.12.169

  10. Alazki, H.S., Poznyak Gorbatch, A.S.: Inventory constraint control with uncertain stochastic demands: attractive ellipsoid technique application. IMA J. Math. Control Inf. 29(3), 399–425 (2012). https://doi.org/10.1093/imamci/dnr038

  11. Alvarez, I., Poznyak, A.S.: Game theory applied to urban traffic control problem. Proc. ICCAS 2010, 2164–2169 (2010). https://doi.org/10.1109/ICCAS.2010.5670234

  12. Alvarez, I., Poznyak, A.S., Malo, A.: Urban traffic control problem via a game theory application. In: Proceedings of the 46th IEEE Conference on Decision and Control, pp. 2957–2961 (2007). https://doi.org/10.1109/CDC.2007.4434820

  13. Alvarez, I., Poznyak, A.S., Malo, A.: Urban traffic control problem a game theory approach. In: Proceedings of the 47th IEEE Conference on Decision and Control, pp. 2168–2172 (2008). https://doi.org/10.1109/CDC.2008.4739461

  14. Azhmyakov, V., Poznyak, A.S.: A variational characterization of the sliding mode control processes. In: Proceedings of the American Control Conference (ACC), pp. 5383–5388 (2012). https://doi.org/10.1109/ACC.2012.6315542

  15. Azhmyakov, V., Boltyanski, V., Poznyak, A.S.: The dynamic programming approach to multi-model robust optimization. Nonlinear Anal. Theory, Methods Appl. Int. Multidiscip. J. 72(2), 1110–1119 (2010). https://doi.org/10.1016/j.na.2009.07.050

  16. Azhmyakov, V., Boltyanski, V.G., Poznyak, A.S.: First order optimization techniques for impulsive hybrid dynamical systems. In: Proceedings of International Workshop on Variable Structure Systems, pp. 173–178 (2008). https://doi.org/10.1109/VSS.2008.4570703

  17. Azhmyakov, V., Boltyanski, V.G., Poznyak, A.S.: On the dynamic programming approach to multi-model robust optimal control problems. In: Proceedings of the American Control Conference, pp. 4468–4473 (2008). https://doi.org/10.1109/ACC.2008.4587199

  18. Azhmyakov, V., Boltyanski, V.G., Poznyak, A.S.: Optimal control of impulsive hybrid systems. Nonlinear Anal. Hybrid Syst. 2(4), 1089–1097 (2008). https://doi.org/10.1016/j.nahs.2008.09.003

  19. Azhmyakov, V., Cabrera Martinez, J., Poznyak, A.S.: Optimal fixed-levels control for nonlinear systems with quadratic cost-functionals. Optim. Control Appl. Methods 37(5), 1035–1055 (2016). https://doi.org/10.1002/oca.2223

  20. Azhmyakov, V., Egerstedt, M., Fridman, L., Poznyak, A.S.: Approximability of nonlinear affine control systems. Nonlinear Anal. Hybrid Syst. 5(2), 275–288 (2011). https://doi.org/10.1016/j.nahs.2010.07.005

  21. Azhmyakov, V., Galvan-Guerra, R., Poznyak, A.S.: On the hybrid LQ-based control design for linear networked systems. J. Frankl. Inst. Eng. Appl. Math. 347(7), 1214–1226 (2010). https://doi.org/10.1016/j.jfranklin.2010.05.012

  22. Azhmyakov, V., Martinez, J.C., Poznyak, A.S., Serrezuela, R.R.: Optimization of a class of nonlinear switched systems with fixed-levels control inputs. In: Proceedings of the American control Conference (ACC), pp. 1770–1775 (2015). https://doi.org/10.1109/ACC.2015.7170989

  23. Azhmyakov, V., Polyakov, A., Poznyak, A.S.: Consistent approximations and variational description of some classes of sliding mode control processes. J. Frankl. Inst. Eng. Appl. Math. 351(4), 1964–1981 (2014). https://doi.org/10.1016/j.jfranklin.2013.01.011

  24. Azhmyakov, V., Poznyak, A.S., Gonzalez, O.: On the robust control design for a class of nonlinearly affine control systems: the attractive ellipsoid approach. J. Ind. Manag. Optim. 9(3), 579–593 (2013). https://doi.org/10.3934/jimo.2013.9.579

  25. Azhmyakov, V., Poznyak, A.S., Juárez, R.: On the practical stability of control processes governed by implicit differential equations: the invariant ellipsoid based approach. J. Frankl. Inst. Eng. Appl. Math. 350(8), 2229–2243 (2013). https://doi.org/10.1016/j.jfranklin.2013.04.016

  26. Baev, S., Shkolnikov, I., Shtessel, Y., Poznyak, A.S.: Parameter identification of non-linear system using traditional and high order sliding modes. In: Proceedings of the American Control Conference, p. 6 (2006). https://doi.org/10.1109/ACC.2006.1656620

  27. Baev, S., Shkolnikov, I.A., Shtessel, Y.B., Poznyak, A.S.: Sliding mode parameter identification of systems with measurement noise. Int. J. Syst. Sci. 38(11), 871–878 (2007). https://doi.org/10.1080/00207720701622809

  28. Bejarano, F.J., Fridman, L., Poznyak, A.S.: Output integral sliding mode with application to the LQ - optimal control. In: Proceedings of the International Workshop on Variable Structure Systems VSS’06, pp. 68–73 (2006). https://doi.org/10.1109/VSS.2006.1644495

  29. Bejarano, F.J., Fridman, L., Poznyak, A.S.: Estimation of unknown inputs, with application to fault detection, via partial hierarchical observation. In: Proceedings of the European Control Conference (ECC), pp. 5154–5161 (2007)

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  30. Bejarano, F.J., Fridman, L., Poznyak, A.S.: Exact state estimation for linear systems with unknown inputs based on hierarchical super-twisting algorithm. Int. J. Robust Nonlinear Control 17(18), 1734–1753 (2007). https://doi.org/10.1002/rnc.1190

  31. Bejarano, F.J., Fridman, L., Poznyak, A.S.: Hierarchical observer for strongly detectable systems via second order sliding mode. In: Proceedings of the 46th IEEE Conference on Decision and Control, pp. 3709–3714 (2007). https://doi.org/10.1109/CDC.2007.4434968

  32. Bejarano, F.J., Fridman, L.M., Poznyak, A.S.: Output integral sliding mode control based on algebraic hierarchical observer. Int. J. Control 80(3), 443–453 (2007). https://doi.org/10.1080/00207170601080205

  33. Bejarano, F.J., Fridman, L.M., Poznyak, A.S.: Output integral sliding mode for min-max optimization of multi-plant linear uncertain systems. IEEE Trans. Autom. Control 54(11), 2611–2620 (2009). https://doi.org/10.1109/TAC.2009.2031718

  34. Bejarano, F.J., Fridman, L.M., Poznyak, A.S.: Unknown input and state estimation for unobservable systems. SIAM J. Control Optim. 48(2), 1155–1178 (2009). https://doi.org/10.1137/070700322

  35. Bejarano, F.J., Poznyak, A.S., Fridman, L.: Hierarchical second-order sliding-mode observer for linear time invariant systems with unknown inputs. Int. J. Syst. Sci. Princ. Appl. Syst. Integr. 38(10), 793–802 (2007). https://doi.org/10.1080/00207720701409280

  36. Bejarano, F.J., Poznyak, A.S., Fridman, L.: Min-max output integral sliding mode control for multiplant linear uncertain systems. In: Proceedings of the American Control Conference, pp. 5875–5880 (2007). https://doi.org/10.1109/ACC.2007.4282716

  37. Bejarano, F.J., Poznyak, A.S., Fridman, L.M.: Observation of linear systems with unknown inputs via high-order sliding-modes. Int. J. Syst. Sci. 38(10), 773–791 (2007). https://doi.org/10.1080/00207720701409538

  38. Boltyanski, V.G., Poznyak, A.S.: Robust maximum principle for minimax mayer problem with uncertainty from a compact measured set. In: Proceedings of the American Control Conference (IEEE Cat. No.CH37301), vol. 1, pp. 310–315 (2002). https://doi.org/10.1109/ACC.2002.1024822

  39. Boltyanski, V.G., Poznyak, A.S.: A compact uncertainty set. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_17

  40. Boltyanski, V.G., Poznyak, A.S.: Dynamic programming for robust optimization. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_12

  41. Boltyanski, V.G., Poznyak, A.S.: Extremal problems in banach spaces. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_7

  42. Boltyanski, V.G., Poznyak, A.S.: Finite collection of dynamic systems. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_8

  43. Boltyanski, V.G., Poznyak, A.S.: Introduction. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_1

  44. Boltyanski, V.G., Poznyak, A.S.: Linear multimodel time optimization. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_10

  45. Boltyanski, V.G., Poznyak, A.S.: Linear quadratic optimal control. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_4

  46. Boltyanski, V.G., Poznyak, A.S.: LQ-stochastic multimodel control. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_16

  47. Boltyanski, V.G., Poznyak, A.S.: The maximum principle. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_2

  48. Boltyanski, V.G., Poznyak, A.S.: A measurable space as uncertainty set. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_11

  49. Boltyanski, V.G., Poznyak, A.S.: Min-max sliding-mode control. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_13

  50. Boltyanski, V.G., Poznyak, A.S.: Multimodel Bolza and LQ problem. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_9

  51. Boltyanski, V.G., Poznyak, A.S.: Multimodel differential games. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_14

  52. Boltyanski, V.G., Poznyak, A.S.: Multiplant robust control. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_15

  53. Boltyanski, V.G., Poznyak, A.S.: The Robust Maximum Principle. Foundations and Applications. Birkhauser, New York, Systems and Control (2012)

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  54. Boltyanski, V.G., Poznyak, A.S.: The tent method in finite-dimensional spaces. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_6

  55. Boltyanski, V.G., Poznyak, A.S.: Time-optimization problem. The Robust Maximum Principle (2012). https://doi.org/10.1007/978-0-8176-8152-4_5

  56. Bregeault, V., Brgeault, V., Plestan, F., Shtessel, Y., Poznyak, A.S.: Adaptive sliding mode control for an electropneumatic actuator. In: Proceedings of the 11th International Workshop on Variable Structure Systems (VSS), pp. 260–265 (2010). https://doi.org/10.1109/VSS.2010.5544714

  57. Cabrera, A., Poznyak, A.S., Poznyak, T., Aranda, J.: Some experiments on identification of a fed-batch culture via differential neural networks. In: Proceedings of the IEEE International Conference on Control Applications (CCA ’01), pp. 152–156 (2001). https://doi.org/10.1109/CCA.2001.973855

  58. Carrillo, L., Escobar, J.A., Clempner, J.B., Poznyak, A.S.: Optimization problems in chemical reactions using continuous-time Markov chains. J. Math. Chem. 54(6), 1233 (2016). https://doi.org/10.1007/s10910-016-0620-0

  59. Castillo, R.G., Clempner, J.B., Poznyak, A.S.: Solving the multi-traffic signal-control problem for a class of continuous-time Markov games. In: Proceedings of the 12th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) 2015, pp. 1–5 (2015). https://doi.org/10.1109/ICEEE.2015.7357932

  60. Chairez, I., Fuentes, R., Poznyak, A.S., Poznyak, T.: Robust identification of uncertain Schrödinger type complex partial differential equations. In: Proceedings of the 7th International Conference on Electrical Engineering, Computing Science and Automatic Control, pp. 170–175 (2010). https://doi.org/10.1109/ICEEE.2010.5608635

  61. Chairez, I., Fuentes, R., Poznyak, A.S., Poznyak, T.: Robust identification of uncertain Schrödinger type complex partial differential equations. In: Proceedings of the 7th International Conference on Electrical Engineering, Computing Science and Automatic Control, CCE 2010 (Formerly known as ICEEE) IEEE, Tuxtla Gutierrez, Mexico, 8–10 Sept 2010, pp. 170–175 (2010). https://doi.org/10.1109/ICEEE.2010.5608635

  62. Chairez, I., Fuentes, R., Poznyak, A.S., Poznyak, T., Escudero, M., Viana, L.: Neural network identification of uncertain 2D partial differential equations. In: Proceedings of the 6th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) 2009, pp. 1–6 (2009). https://doi.org/10.1109/ICEEE.2009.5393456

  63. Chairez, I., Fuentes, R., Poznyak, A.S., Poznyak, T., Escudero, M., Viana, L.: DNN-state identification of 2D distributed parameter systems. Int. J. Syst. Sci. 43(2), 296–307 (2012). https://doi.org/10.1080/00207721.2010.495187

  64. Chairez, I., Garca, A., Poznyak, A.S., Poznyak, T.: Model predictive control by differential neural networks approach. In: Proceedings of the International Joint Conference on Neural Networks (IJCNN), pp. 1–8 (2010). https://doi.org/10.1109/IJCNN.2010.5596521

  65. Chairez, I., Poznyak, A.S., Poznyak, T.: Dynamic neural observer with sliding mode learning. In: Proceedings of the 3rd International IEEE Conference on Intelligent Systems, pp. 600–605 (2006). https://doi.org/10.1109/IS.2006.348487

  66. Chairez, I., Poznyak, A.S., Poznyak, T.: New sliding-mode learning law for dynamic neural network observer. IEEE Trans. Circuits Syst. II: Express Briefs 53(12), 1338–1342 (2006). https://doi.org/10.1109/TCSII.2006.883096

  67. Chairez, I., Poznyak, A.S., Poznyak, T.: High order dynamic neuro observer: application for ozone generator. In: Proceedings of the International Workshop on Variable Structure Systems, pp. 291–295 (2008). https://doi.org/10.1109/VSS.2008.4570723

  68. Chairez, I., Poznyak, A.S., Poznyak, T.: High order sliding mode neurocontrol for uncertain nonlinear SISO systems: theory and applications. Modern Sliding Mode Control Theory (2008). https://doi.org/10.1007/978-3-540-79016-7_9

  69. Chairez, I., Poznyak, A.S., Poznyak, T.: Stable weights dynamics for a class of differential neural network observer. IET Control Theory Appl. 3(10), 1437–1447 (2009). https://doi.org/10.1049/iet-cta.2008.0261

  70. Clempner, J.B., Poznyak, A.S.: Convergence method, properties and computational complexity for Lyapunov games. Appl. Math. Comput. Sci. 21(2), 349–361 (2011). https://doi.org/10.2478/v10006-011-0026-x

  71. Clempner, J.B., Poznyak, A.S.: Analysis of best-reply strategies in repeated finite Markov chains games. In: Proceedings of the 52nd IEEE Conference on Decision and Control, pp. 568–573 (2013). https://doi.org/10.1109/CDC.2013.6759942

  72. Clempner, J.B., Poznyak, A.S.: Simple computing of the customer lifetime value: a fixed local-optimal policy approach. J. Syst. Sci. Syst. Eng. 23(4), 439 (2014). https://doi.org/10.1007/s11518-014-5260-y

  73. Clempner, J.B., Poznyak, A.S.: Computing the strong Nash equilibrium for Markov chains games. Appl. Math. Comput. 265, 911–927 (2015). https://doi.org/10.1016/j.amc.2015.06.005

  74. Clempner, J.B., Poznyak, A.S.: Modeling the multi-traffic signal-control synchronization: a Markov chains game theory approach. Eng. Appl. Artif. Intell. 43, 147–156 (2015). https://doi.org/10.1016/j.engappai.2015.04.009

  75. Clempner, J.B., Poznyak, A.S.: Stackelberg security games: computing the shortest-path equilibrium. Expert Syst. Appl. 42(8), 3967–3979 (2015). https://doi.org/10.1016/j.eswa.2014.12.034

  76. Clempner, J.B., Poznyak, A.S.: Analyzing an optimistic attitude for the leader firm in duopoly models: a strong Stackelberg equilibrium based on a Lyapunov game theory approach. Econ. Comput. Econ. Cybern. Stud. Res. 4(50), 41–60 (2016)

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  77. Clempner, J.B., Poznyak, A.S.: Conforming coalitions in Markov Stackelberg security games: setting max cooperative defenders vs. non-cooperative attackers. Appl. Soft Comput. 47, 1–11 (2016). https://doi.org/10.1016/j.asoc.2016.05.037

  78. Clempner, J.B., Poznyak, A.S.: Constructing the Pareto front for multi-objective Markov chains handling a strong Pareto policy approach. Comput. Appl. Math. 1 (2016). https://doi.org/10.1007/s40314-016-0360-6

  79. Clempner, J.B., Poznyak, A.S.: Convergence analysis for pure stationary strategies in repeated potential games: Nash, Lyapunov and correlated equilibria. Expert Syst. Appl. 46, 474–484 (2016). https://doi.org/10.1016/j.eswa.2015.11.006

  80. Clempner, J.B., Poznyak, A.S.: Solving the Pareto front for multiobjective Markov chains using the minimum Euclidean distance gradient-based optimization method. Math. Comput. Simul. 119, 142–160 (2016). https://doi.org/10.1016/j.matcom.2015.08.004

  81. Clempner, J.B., Poznyak, A.S.: Multiobjective Markov chains optimization problem with strong Pareto frontier: principles of decision making. Expert Syst. Appl. 68, 123–135 (2017). https://doi.org/10.1016/j.eswa.2016.10.027

  82. Clempner, J.B., Poznyak, A.S.: Using Manhattan distance for computing the multiobjective Markov chains problem. Int. J. Comput. Math. (2017) (To be published)

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  83. Clempner, J.B., Poznyak, A.S.: Using the extraproximal method for computing the shortest-path mixed Lyapunov equilibrium in Stackelberg security games. Math. Comput. Simul. 138, 14–30, (2017). https://doi.org/10.1016/j.matcom.2016.12.010. (To be published)

  84. Clempner, J.B., Poznyak, A.S.: A Tikhonov regularized penalty function approach for solving polylinear programming problems. J. Comput. Appl. Math. 328, 267–286 (2018)

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  85. Clempner, J. B., Poznyak, A.: Negotiating The Transfer Pricing Using The Nash Bargaining Solution. Int J Appl Math Comput Sci. (To be published)

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  86. Clempner, J.B., Poznyak, A.: A Tikhonov Regularization Parameter Approach For Solving Lagrange Constrained Optimization Problems. Eng Optimiz. (To be published)

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  87. Davila, J., Poznyak, A.S.: Sliding modes parameter adjustment in the presence of fast actuators using invariant ellipsoids method. In: Proceedings of the 6th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE) 2009, pp. 1–6 (2009). https://doi.org/10.1109/ICEEE.2009.5393474

  88. Davila, J., Poznyak, A.S.: Attracting ellipsoid method application to designing of sliding mode controllers. In: Proceedings of the 11th International Workshop on Variable Structure Systems (VSS), pp. 83–88 (2010). https://doi.org/10.1109/VSS.2010.5544627

  89. Davila, J., Poznyak, A.S.: Design of sliding mode controllers with actuators using attracting ellipsoid method. In: Proceedings of the 49th IEEE Conference on Decision and Control (CDC), pp. 72–77 (2010). https://doi.org/10.1109/CDC.2010.5717774

  90. Davila, J., Poznyak, A.S.: Dynamic sliding mode control design using attracting ellipsoid method. Automatica 47(7), 1467–1472 (2011). https://doi.org/10.1016/j.automatica.2011.02.023

  91. Davila, J., Poznyak, A.S.: Sliding mode parameter adjustment for perturbed linear systems with actuators via invariant ellipsoid method. Int. J. Robust Nonlinear Control 21(5), 473–487 (2011). https://doi.org/10.1002/rnc.1599

  92. Davila, J., Fridman, L., Poznyak, A.S.: Observation and identification of mechanical systems via second order sliding modes. Int. J. Control 79(10), 1251–1262 (2006). https://doi.org/10.1080/00207170600801635

  93. Escobar, J., Poznyak, A.S.: Continuous-time identification using LS-method under colored noise perturbations. In: Proceedings of the 46th IEEE Conference on Decision and Control, pp. 5516–5521 (2007). https://doi.org/10.1109/CDC.2007.4434168

  94. Escobar, J., Poznyak, A.S.: Robust continuous-time matrix estimation under dependent noise perturbations: sliding modes filtering and LSM with forgetting. CSSP 28(2), 257–282 (2009). https://doi.org/10.1007/s00034-008-9080-5

  95. Escobar, J., Poznyak, A.S.: Time-varying parameter estimation in continuous-time under colored perturbations using “equivalent control concept” and LSM with forgetting factor. In: Proceedings of the 11th International Workshop on Variable Structure Systems (VSS), pp. 209–214 (2010). https://doi.org/10.1109/VSS.2010.5544662

  96. Escobar, J., Poznyak, A.S.: Time-varying matrix estimation in stochastic continuous-time models under coloured noise using LSM with forgetting factor. Int. J. Syst. Sci. 42(12), 2009–2020 (2011). https://doi.org/10.1080/00207721003706852

  97. Escobar, J., Poznyak, A.S.: Benefits of variable structure techniques for parameter estimation in stochastic systems using least squares method and instrumental variables. Int. J. Adapt. Control Signal Process. 29(8), 1038–1054 (2015). https://doi.org/10.1002/acs.2521

  98. Fridman, L., Poznyak, A.S., Bejarano, F.: Decomposition of the min-max multi-model problem via integral sliding mode. Int. J. Robust Nonlinear Control 15(13), 559–574 (2005). https://doi.org/10.1002/rnc.1009

  99. Fridman, L., Poznyak, A.S., Bejarano, F.J.: Decomposition of the mini-max multimodel optimal problem via integral sliding mode control. Proceedings of the American Control Conference 1, 620–625 (2004)

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  1. Department of Control Automático, CINVESTAV-IPN, AP-14-740, Ciudad de México, México

    Alexander S. Poznyak

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    Julio B. Clempner

  2. Department of Automatic Control, Center for Research and Advanced Studies, Mexico city, Mexico

    Wen Yu

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Poznyak, A.S. (2018). Dr. Alexander Semionovich Poznyak Gorbatch: Biography. In: Clempner, J., Yu, W. (eds) New Perspectives and Applications of Modern Control Theory. Springer, Cham. https://doi.org/10.1007/978-3-319-62464-8_1

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