Andrew S. Lee, S. Andrew Gadsden, Stephen A. Wilkerson and Mohammad AlShabi


  1. [1] B. Ristic, S. Arulampalam, and N. Gordon, Beyond the Kalmanfilter: Particle filters for tracking applications. (Boston, MA:Artech House, 2004).
  2. [2] M. Avzayesh, M. Abdel-Hafez, M. AlShabi, and S.A. Gadsden,The smooth variable structure filter: A comprehensive review,Digital Signal Processing, 110, 2021, 102912.
  3. [3] S.A. Gadsden, Smooth variable structure filtering: Theory andapplications. (Hamilton, ON: McMaster University, 2011).
  4. [4] H.H. Afshari, S.A. Gadsden, and S.R. Habibi, Gaussian filtersfor parameter and state estimation: A review of theory andrecent trends, Signal Processing, 135, 2017, 218–238.
  5. [5] V.I. Utkin, Variable structure systems with sliding modes, IEEETransactions on Automatic Control, 22(2), 1977, 212–222.
  6. [6] V.I. Utkin, Sliding mode and their application in variablestructure systems. (Moscow: Mir Publ., 1978).
  7. [7] A.F. Fillipov, Differential equation with discontinuous righthand side, 62. Providence, RI: American Mathematical SocietyTransactions, 1969.
  8. [8] V.I. Utkin, Sliding modes in control optimization. (New York,NY: Springer-Verlag, 1992).
  9. [9] J.J.E. Slotine, J. Hedrick, and E. Misawa, On sliding observersfor nonlinear systems, ASME Journal of Dynamic Systems,Measurement and Control, 109(3), 1987, 245–252.
  10. [10] J.J.E. Slotine and W. Li, Applied nonlinear control. (EnglewoodCliffs, NJ: Prentice-Hall, 1991).8
  11. [11] S.A. Gadsden and A.S. Lee, Advances of the smooth variablestructure filter: Square-root and two-pass formulations, Journalof Applied Remote Sensing, 11(1), 2017, 1–19.
  12. [12] M. Al-Shabi, The general toeplitz/observability SVSF. (Hamil-ton, ON: McMaster University, 2011).
  13. [13] C. Milosavlejic, General conditions for the existence of aquasi-sliding mode on the switching hyperplane in discretevariable structure systems, Automatic Remote Control, 46,1985, 307–315.
  14. [14] K. Furuta, Sliding mode control of a discrete system, SystemsControl Letters, 14, 1990, 145–152.
  15. [15] S.Z. Sarpturk, Y. Istefanopoulos, and O. Kaynak, On thestability of discrete-time sliding mode control systems, IEEETransactions on Automatic Control, AC-32(10), 1987, 930–932.
  16. [16] S.K. Spurgeon, Sliding mode observers: A survey, InternationalJournal of Systems Science, 39(8), 2008, 751–764.
  17. [17] S.H. Qaiser, A.I. Bhatti, M. Iqbal, R. Samar, and J. Qadir,Estimation of precursor concentration in a research reactor byusing second order sliding mode observer, Nuclear Engineeringand Design, 239, 2009, 2134–2140.
  18. [18] S.H. Qaiser, A.I. Bhatti, R. Samar, M. Iqbal, and J. Qadir,Higher order sliding mode observer based estimation ofprecursor concentration in a research reactor, Proc. 4th IEEEConf. on Emerging Technologies, Rawalpindi, 2008, 338–343.
  19. [19] C. Edwards and S. Spurgeon, On the development ofdiscontinuous observers, International Journal of Control, 59,1994, 1211–1229.
  20. [20] J.-J.E. Slotine, J.K. Hedrick, and E.A. Misawa, On slidingobservers for nonlinear systems, Proc. American Control Conf.,Seattle, WA, 1986, 1794–1800.
  21. [21] B. Walcott and S. Zak, State observation of nonlinear uncertaindynamical systems, IEEE Transactions on Automatic Control,AC-32(2), 1987, 166–170.
  22. [22] B. Walcott, M. Corless, and S. Zak, Comparative study ofstate observation techniques, International Journal of Control,45(6), 1987, 2109–2132.
  23. [23] C. Tan and C. Edwards, Sliding mode observers for robustdetection and reconstruction of actuator and sensor faults,International Journal of Robust and Nonlinear Control, 13(1),2003, 443–463.
  24. [24] S.R. Habibi, The smooth variable structure filter, Proceedingsof the IEEE, 95(5), 2007, 1026–1059.
  25. [25] S.A. Gadsden, Smooth variable structure filtering: Theory andapplications, PhD Thesis, McMaster University, Hamilton, ON,Canada, 2011.
  26. [26] S.A. Gadsden, S.R. Habibi, and T. Kirubarajan, Kalman andsmooth variable structure filters for robust estimation, IEEETransactions on Aerospace and Electronic Systems, 50(2),2014, 1038–1050.
  27. [27] S.A. Gadsden, M. El Sayed, and S.R. Habibi, Derivation of anoptimal boundary layer width for the smooth variable structurefilter, Proc. ASME/IEEE American Control Conf. (ACC), SanFrancisco, CA, 2011, 4922–4927.
  28. [28] S.A. Gadsden and S.R. Habibi, A new robust filtering strategyfor linear systems, ASME Journal of Dynamic Systems,Measurement, and Control, 135(1), 2013, 9.
  29. [29] S.A. Gadsden, M. Al-Shabi, and S.R. Habibi, Estimationstrategies for the condition monitoring of a battery system ina hybrid electric vehicle, ISRN Signal Processing, 2011, 2011,120351.
  30. [30] J. Goodman, J. Kim, A.S. Lee, and S.A. Gadsden, A variablestructure-based estimation strategy applied to an RRR robotsystem, Journal of Robotics, Networking and Artificial Life,4(2), 2017, 142–145.
  31. [31] J. Kim, S. Bonadies, C.D. Eggleton, and S.A. Gadsden,Cooperative robot exploration strategy using an efficientbacktracking method for multiple robots, ASME Journal ofMechanisms and Robotics, 10(6), 2018, 7.
  32. [32] M. Al-Shabi, S.A. Gadsden, and S.R. Habibi, Kalman filteringstrategies utilizing the chattering effects of the smooth variablestructure filter, Signal Processing, 93(2), 2013, 420–431.
  33. [33] H.H. Afshari, The 2nd-order smooth variable structure filter(2nd-SVSF) for state estimation: Theory and applications,PhD Thesis, McMaster University, Hamilton, ON, Canada,2014.
  34. [34] S.A. Gadsden and A.S. Lee, Advances of the smooth variablestructure filter: Square-root and two-pass formulations, Journalof Applied Remote Sensing, 11(1), 2017, 15018.
  35. [35] M. Al-Shabi and A. Elnady, Recursive smooth variable structurefilter for estimation processes in direct power control schemeunder balanced and unbalanced power grid, IEEE SystemsJournal, 14(1), 2019, 971–982.
  36. [36] S.A. Gadsden and M. Al-Shabi, The sliding innovation filter,IEEE Access, 8, 2020, 96129–96138.
  37. [37] A. Lee, S. Gadsden, and M. AlShabi, An adaptive formulationof the sliding innovation filter, IEEE Signal Processing Letters,28, 2021, 1295–1299.
  38. [38] M.A. AlShabi, S.A. Gadsden, M. El Haj Assad, and B.Khuwaileh, A multiple model-based sliding innovation filter,Proc. Signal Processing, Sensor/Information Fusion, andTarget Recognition XXX, Baltimore, MD, 2021, 1175608.
  39. [39] M. AlShabi, S. Andrew Gadsden, M. El Haj Assad, B.Khuwaileh, and S. Wilkerson, Application of the slidinginnovation filter to unmanned aerial systems, Proc. UnmannedSystems Technology XXIII, Baltimore, MD, 2021, 117580T.
  40. [40] S.A. Gadsden, S.R. Habibi, and T. Kirubarajan, Kalman andsmooth variable structure filters for robust estimation, IEEETransactions on Aerospace and Electronic Systems, 50(2),2014, 1038–1050.
  41. [41] S.A. Gadsden, M. Al-Shabi, I. Arasaratnam, and S.R. Habibi,Combined cubature Kalman and smooth variable structurefiltering: A robust estimation strategy, Signal Processing, 96,Mar. 2014, 290–299.
  42. [42] T.Q.S. Truong, Exploration of adaptive filters for targettracking in the presence of model uncertainty, Proc. 6th Int.Conf. on Intelligent Sensors, Sensor Networks and InformationProcessing, Brisbane, QLD, 2010, 1–6.
  43. [43] S.A. Gadsden, Y. Song, and S.R. Habibi, Novel model-basedestimators for the purposes of fault detection and diagnosis,IEEE/ASME Transactions on Mechatronics, 18(4), 2013,1237–1249.
  44. [44] M. Esfandiari and N. Sepehri, Controller design and stabilityanaylysis of ouput pressure regulation in electrohydrostaticactuators, AMSE, Journal of Dynamic Systems, Measurement,and Control, 141(4), 2019, 41008.
  45. [45] A. Maddahi, W. Kinsner, and N. Sepehri, Internal leakagedetection in electrohydrostatic actuators using multiscaleanalysis of experimental data, IEEE Transactions onInstrumentation and Measurement, 65(12), 2016, 2734–2747.
  46. [46] H.H. Afshari, S.A. Gadsden, and S.R. Habibi, Robust faultdiagnosis of an electro-hydrostatic actuator using the noveloptimal second-order SVSF and IMM Strategy, InternationalJournal of Fluid Power, 15(3), 2014, 181–196.
  47. [47] S.A. Gadsden and T. Kirubarajan, Development of a variablestructure-based fault detection and diagnosis strategy appliedto an electromechanical system, Proc. SPIE Signal Processing,Sensor/Information Fusion, and Target Recognition, XXVI,Anaheim, CA, 2017, 102001E.

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