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Volume 13 Issue 8
Aug.  2026

IEEE/CAA Journal of Automatica Sinica

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H. Liu, Q.-L. Han, Z. Huang, Y. Li, and W. Wang, “Nonlinear set-membership estimation and its application to the design of an interacting multiple model estimator,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 8, pp. 1969–1981, Aug. 2026. doi: 10.1109/JAS.2025.125867
Citation: H. Liu, Q.-L. Han, Z. Huang, Y. Li, and W. Wang, “Nonlinear set-membership estimation and its application to the design of an interacting multiple model estimator,” IEEE/CAA J. Autom. Sinica, vol. 13, no. 8, pp. 1969–1981, Aug. 2026. doi: 10.1109/JAS.2025.125867

Nonlinear Set-Membership Estimation and Its Application to the Design of an Interacting Multiple Model Estimator

doi: 10.1109/JAS.2025.125867
Funds:  This work was partially supported by the National Natural Science Foundation of China (61703286, 62394342)
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  • In this paper, an interacting multiple model (IMM) nonlinear set-membership estimation (NSME) is investigated for nonlinear systems with unknown-but-bounded (UBB) noises. First, two different NSME approaches are developed based on whether the characteristics of different noises are employed. Based on the proposed NSME method, a novel IMM-NSME algorithm is developed, which can be utilized to deal with the state estimation of multiple nonlinear models. Furthermore, the interaction between estimators depends on the switching probabilities described by the probability transition matrix, where the corresponding model probabilities are updated according to the designed rules. Then, the IMM-NSME algorithm is applied to address vehicle tracking, which is modeled as a combination of the constant velocity (CV) model and constant turning rate and velocity (CTRV) model. Finally, numerical simulations are provided to illustrate the validity of the developed methods.

     

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  • [1]
    V. T. H. Le, C. Stoica, T. Alamo, E. F. Camacho, and D. Dumur, “Zonotopic guaranteed state estimation for uncertain systems,” Automatica, vol. 49, no. 11, pp. 3418–3424, Nov. 2013. doi: 10.1016/j.automatica.2013.08.014
    [2]
    H. G. Harno and Y. Kim, “Flight envelope estimation for helicopters under icing conditions via the zonotopic reachability analysis,” Aerosp. Sci. Technol., vol. 102, Art. no. 105859, Jul. 2020. doi: 10.1016/j.ast.2020.105859
    [3]
    C. Pek and M. Althoff, “Fail-safe motion planning for online verification of autonomous vehicles using convex optimization,” IEEE Trans. Rob., vol. 37, no. 3, pp. 798–814, Jun. 2021. doi: 10.1109/TRO.2020.3036624
    [4]
    E. Mousavinejad, X. H. Ge, Q.-L. Han, T. J. Lim, and L. Vlacic, “An ellipsoidal set-membership approach to distributed joint state and sensor fault estimation of autonomous ground vehicles,” IEEE/CAA J. Autom. Sinica, vol. 8, no. 6, pp. 1107–1118, Jun. 2021. doi: 10.1109/JAS.2021.1004015
    [5]
    M. D. Sikiric, “Zonotopes and parallelotopes,” Southeast Asian Bull. Math., vol. 41, pp. 197–207, 2017.
    [6]
    Z. H. Wang, C. C. Lim, and Y. Shen, “Interval observer design for uncertain discrete-time linear systems,” Syst. Control Lett., vol. 116, pp. 41–46, Jun. 2018. doi: 10.1016/j.sysconle.2018.04.003
    [7]
    Z. H. Zhang and G. H. Yang, “Interval observer-based fault isolation for discrete-time fuzzy interconnected systems with unknown interconnections,” IEEE Trans. Cybern., vol. 47, no. 9, pp. 2413–2424, Sep. 2017. doi: 10.1109/TCYB.2017.2707462
    [8]
    N. Meslem, A. Hably, and T. Raïssi, “Zonotopic unknown input state estimator for discrete-time linear systems,” Syst. Control Lett., vol. 162, Art. no. 105168, Apr. 2022. doi: 10.1016/j.sysconle.2022.105168
    [9]
    W. T. Tang, Z. H. Wang, Q. H. Zhang, and Y. Shen, “Set-membership estimation for linear time-varying descriptor systems,” Automatica, vol. 115, Art. no. 108867, May 2020. doi: 10.1016/j.automatica.2020.108867
    [10]
    M. Althoff and J. J. Rath, “Comparison of guaranteed state estimators for linear time-invariant systems,” Automatica, vol. 130, Art. no. 109662, Aug. 2021. doi: 10.1016/j.automatica.2021.109662
    [11]
    Y. Wang, Z. Wang, V. Puig, and G. Cembrano, “Zonotopic set-membership state estimation for discrete-time descriptor LPV systems,” IEEE Trans. Autom. Control, vol. 64, no. 5, pp. 2092–2099, May 2019. doi: 10.1109/TAC.2018.2863659
    [12]
    Y. Wang, V. Puig, and G. Cembrano, “Set-membership approach and Kalman observer based on zonotopes for discrete-time descriptor systems,” Automatica, vol. 93, pp. 435–443, Jul. 2018. doi: 10.1016/j.automatica.2018.03.082
    [13]
    V. T. H. Le, T. Alamo, E. F. Camacho, C. Stoica, and D. Dumur, “A new approach for guaranteed state estimation by zonotopes,” IFAC Proc. Vol., vol. 44, no. 1, pp. 9242–9247, Jan. 2011. doi: 10.3182/20110828-6-IT-1002.02496
    [14]
    V. T. H. Le, C. Stoica, T. Alamo, E. F. Camacho, and D. Dumur, “Zonotope-based set-membership estimation for multi-output uncertain systems,” in Proc. IEEE Int. Symp. Intelligent Control, Hyderabad, India, 2013, pp. 212–217.
    [15]
    C. Combastel, “Zonotopes and Kalman observers: Gain optimality under distinct uncertainty paradigms and robust convergence,” Automatica, vol. 55, pp. 265–273, May 2015. doi: 10.1016/j.automatica.2015.03.008
    [16]
    W. Tang, Z. Wang, Y. Shen, M. Rodrigues, and D. Theilliol, “Fault detection based on multi-objective observer and interval hull computation,” IFAC Pap. Online, vol. 51, no. 24, pp. 332–337, 2018. doi: 10.1016/j.ifacol.2018.09.598
    [17]
    H. Ethabet, D. Rabehi, D. Efimov, and T. Raïssi, “Interval estimation for continuous-time switched linear systems,” Automatica, vol. 90, pp. 230–238, Apr. 2018. doi: 10.1016/j.automatica.2017.12.035
    [18]
    W. Tang, Z. Wang, Y. Wang, T. Raïssi, and Y. Shen, “Interval estimation methods for discrete-time linear time-invariant systems,” IEEE Trans. Autom. Control, vol. 64, no. 11, pp. 4717–4724, Nov. 2019. doi: 10.1109/TAC.2019.2902673
    [19]
    J. K. Scott, D. M. Raimondo, G. R. Marseglia, and R. D. Braatz, “Constrained zonotopes: A new tool for set-based estimation and fault detection,” Automatica, vol. 69, pp. 126–136, Jul. 2016. doi: 10.1016/j.automatica.2016.02.036
    [20]
    N. Kochdumper and M. Althoff, “Constrained polynomial zonotopes,” Acta Inf., vol. 60, no. 3, pp. 279–316, May 2023. doi: 10.1007/s00236-023-00437-5
    [21]
    T. Alamo, J. M. Bravo, and E. F. Camacho, “Guaranteed state estimation by zonotopes,” Automatica, vol. 41, no. 6, pp. 1035–1043, Jun. 2005. doi: 10.1016/j.automatica.2004.12.008
    [22]
    A. A. de Paula, G. V. Raffo, and B. O. S. Teixeira, “Zonotopic filtering for uncertain nonlinear systems: Fundamentals, implementation aspects, and extensions[Applications of Control],” IEEE Control Syst., vol. 42, no. 1, pp. 19–51, Feb. 2022. doi: 10.1109/MCS.2021.3122311
    [23]
    H. A. P. Blom and Y. Bar-Shalom, “The interacting multiple model algorithm for systems with Markovian switching coefficients,” IEEE Trans. Autom. Control, vol. 33, no. 8, pp. 780–783, Aug. 1988. doi: 10.1109/9.1299
    [24]
    V. Lefkopoulos, M. Menner, A. Domahidi, and M. N. Zeilinger, “Interaction-aware motion prediction for autonomous driving: A multiple model Kalman filtering scheme,” IEEE Rob. Autom. Lett., vol. 6, no. 1, pp. 80–87, Jan. 2021. doi: 10.1109/LRA.2020.3032079
    [25]
    B. Jin, B. Jiu, T. Su, H. Liu, and G. Liu, “Switched Kalman filter-interacting multiple model algorithm based on optimal autoregressive model for manoeuvring target tracking,” IET Radar Sonar Navig., vol. 9, no. 2, pp. 199–209, Feb. 2015. doi: 10.1049/iet-rsn.2014.0142
    [26]
    M. Althoff, O. Stursberg, and M. Buss, “Reachability analysis of nonlinear systems with uncertain parameters using conservative linearization,” in Proc. 47th IEEE Conf. Decision and Control, Cancun, Mexico, Cancun, Mexico, 2008, pp. 4042–4048.
    [27]
    X. Yang and J. K. Scott, “A comparison of zonotope order reduction techniques,” Automatica, vol. 95, pp. 378–384, Sep. 2018. doi: 10.1016/j.automatica.2018.06.006

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