Research article

Lyapunov-based stabilization control design of space 2-D linear parabolic distributed parameter systems employing mobile sensors and actuators

  • Published: 25 May 2026
  • MSC : 35K57, 93C20, 93D15

  • For the actual physical temporal-space process, the spatial two-dimensional (2-D) case makes more sense. With the increase of space dimension, the difficulty of control design increases sharply. This study investigates the asymptotic stabilization issue for 2-D linear parabolic distributed parameter systems (DPSs) defined over spatial domains, where the control architecture incorporates dynamically collocated sensors and actuators. First, in light of the number of mobile sensor/actuator pairs, the 2-D spatial domain is divided into the corresponding quantity of spatial subdomains. At the same time, the mobile sensor/actuator pairs are forced to move in their respective subdomains under the restriction of projection modification algorithm. Afterwards, based on operator semigroup theory, the well-posedness of open-loop and closed-loop spatial 2-D DPSs is both studied. Aiming at the stabilization control of spatial 2-D DPSs under mobile sensor/actuator pairs, we put forward an integrated design scheme of mobile sensor/actuator guidance and static output feedback controller to guarantee the asymptotic stability of the 2-D closed-loop system. Finally, it can be concluded from a simulation example that the proposed integrated design method is effective.

    Citation: Xiao-Wei Zhang, Xiang-Jie Pu, Xiaoli Li, Zi-Peng Wang. Lyapunov-based stabilization control design of space 2-D linear parabolic distributed parameter systems employing mobile sensors and actuators[J]. AIMS Mathematics, 2026, 11(5): 14668-14692. doi: 10.3934/math.2026602

    Related Papers:

  • For the actual physical temporal-space process, the spatial two-dimensional (2-D) case makes more sense. With the increase of space dimension, the difficulty of control design increases sharply. This study investigates the asymptotic stabilization issue for 2-D linear parabolic distributed parameter systems (DPSs) defined over spatial domains, where the control architecture incorporates dynamically collocated sensors and actuators. First, in light of the number of mobile sensor/actuator pairs, the 2-D spatial domain is divided into the corresponding quantity of spatial subdomains. At the same time, the mobile sensor/actuator pairs are forced to move in their respective subdomains under the restriction of projection modification algorithm. Afterwards, based on operator semigroup theory, the well-posedness of open-loop and closed-loop spatial 2-D DPSs is both studied. Aiming at the stabilization control of spatial 2-D DPSs under mobile sensor/actuator pairs, we put forward an integrated design scheme of mobile sensor/actuator guidance and static output feedback controller to guarantee the asymptotic stability of the 2-D closed-loop system. Finally, it can be concluded from a simulation example that the proposed integrated design method is effective.



    加载中


    [1] W. Kang, X. N. Wang, B. Z. Guo, Observer-based fuzzy quantized control for a stochastic third-order parabolic PDE system, IEEE Trans. Syst. Man Cybern. Syst., 53 (2023), 485–494. https://doi.org/10.1109/TSMC.2022.3184077 doi: 10.1109/TSMC.2022.3184077
    [2] Z. Liu, Z. Zhao, C. K. Ahn, Boundary constrained control of flexible string systems subject to disturbances, IEEE Trans. Circuits Syst. II Express Briefs, 67 (2020), 112–116. https://doi.org/10.1109/TCSII.2019.2901283 doi: 10.1109/TCSII.2019.2901283
    [3] J. F. Zhang, J. W. Wang, H. K. Lam, H. X. Li, Boundary output tracking of nonlinear parabolic differential systems via fuzzy PID control, IEEE Trans. Fuzzy Syst., 32 (2024), 6863–6877. https://doi.org/10.1109/TFUZZ.2024.3432554 doi: 10.1109/TFUZZ.2024.3432554
    [4] H. Wei, X. Cui, Y. Zhang, J. Zhang, $H_\infty$ deployment of nonlinear multi-agent systems with Markov switching topologies over a finite-time interval based on T–S fuzzy PDE control, AIMS Math., 9 (2024), 4076–4097. https://doi.org/10.3934/math.2024199 doi: 10.3934/math.2024199
    [5] Z. Zhao, X. He, Z. Ren, G. Wen, Boundary adaptive robust control of a flexible riser system with input nonlinearities, IEEE Trans. Syst. Man Cybern. Syst., 49 (2019), 1971–1980. https://doi.org/10.1109/TSMC.2018.2882734 doi: 10.1109/TSMC.2018.2882734
    [6] X. Song, J. Man, S. Song, C. K. Ahn, Finite-time fault estimation and tolerant control for nonlinear interconnected distributed parameter systems with Markovian switching channels, IEEE Trans. Circuits Syst. I Reg. Pap., 69 (2022), 1347–1359. https://doi.org/10.1109/TCSI.2021.3129372 doi: 10.1109/TCSI.2021.3129372
    [7] M. Krstic, A. Smyshlyaev, Boundary control of PDEs: A course on backstepping designs, Philadelphia: SIAM, 2008. https://doi.org/10.1137/1.9780898718607
    [8] A. Smyshlyaev, M. Krstic, Adaptive control of parabolic PDEs, Princeton: Princeton University Press, 2010. https://doi.org/10.1515/9781400835362
    [9] L. Su, W. Guo, J. M. Wang, M. Krstic, Boundary stabilization of wave equation with velocity recirculation, IEEE Trans. Autom. Control, 62 (2017), 4760–4767. https://doi.org/10.1109/TAC.2017.2688128 doi: 10.1109/TAC.2017.2688128
    [10] J. Deutscher, A backstepping approach to the output regulation of boundary controlled parabolic PDEs, Automatica, 57 (2015), 56–64. https://doi.org/10.1016/j.automatica.2015.04.008 doi: 10.1016/j.automatica.2015.04.008
    [11] B. Z. Guo, R. X. Zhao, Output regulation for a heat equation with unknown exosystem, Automatica, 138 (2022), 110159. https://doi.org/10.1016/j.automatica.2022.110159 doi: 10.1016/j.automatica.2022.110159
    [12] B. Z. Guo, H. C. Zhou, The active disturbance rejection control to stabilization for multi-dimensional wave equation with boundary control matched disturbance, IEEE Trans. Autom. Control, 60 (2015), 143–157. https://doi.org/10.1109/TAC.2014.2335511 doi: 10.1109/TAC.2014.2335511
    [13] R. Katz, E. Fridman, Delayed finite-dimensional observer-based control of 1-D parabolic PDEs, Automatica, 123 (2021), 109364. https://doi.org/10.1016/j.automatica.2020.109364 doi: 10.1016/j.automatica.2020.109364
    [14] X. Lu, W. Zou, M. Huang, A novel spatiotemporal LS-SVM method for complex distributed parameter systems with applications to curing thermal process, IEEE Trans. Ind. Informat., 12 (2016), 1156–1165. https://doi.org/10.1109/TII.2016.2557805 doi: 10.1109/TII.2016.2557805
    [15] X. Lu, W. Zou, M. Huang, An adaptive modeling method for time-varying distributed parameter processes with curing process applications, Nonlinear Dyn., 82 (2015), 865–876. https://doi.org/10.1007/s11071-015-2201-3 doi: 10.1007/s11071-015-2201-3
    [16] W. He, X. He, M. Zou, H. Li, PDE model-based boundary control design for a flexible robotic manipulator with input backlash, IEEE Trans. Control Syst. Technol., 27 (2019), 790–797. https://doi.org/10.1109/TCST.2017.2780055 doi: 10.1109/TCST.2017.2780055
    [17] X. Song, R. Zhang, S. Song, Y. Zhang, Fuzzy adaptive-event-triggered control for semi-linear parabolic PDE systems with stochastic actuator failures, Appl. Math. Comput., 426 (2022), 127127. https://doi.org/10.1016/j.amc.2022.127127 doi: 10.1016/j.amc.2022.127127
    [18] J. W. Wang, J. F. Zhang, H. N. Wu, Boundary fuzzy output tracking control of nonlinear parabolic infinite-dimensional dynamic systems: Application to cooling process in hot strip mills, IEEE Trans. Fuzzy Syst., 31 (2023), 1460–1473. https://doi.org/10.1109/TFUZZ.2022.3203524 doi: 10.1109/TFUZZ.2022.3203524
    [19] J. W. Wang, Y. H. Wei, P. Shi, Spatiotemporal adaptive fuzzy control for state profile tracking of nonlinear infinite-dimensional systems on a hypercube, IEEE Trans. Fuzzy Syst., 32 (2024), 683–696. https://doi.org/10.1109/TFUZZ.2023.3307619 doi: 10.1109/TFUZZ.2023.3307619
    [20] X. Dai, Y. Wang, S. Tian, Y. Chen, Z. Zhao, Fuzzy iterative learning control for nonlinear parabolic distributed parameter systems, Fuzzy Sets Syst., 521 (2025), 109603. https://doi.org/10.1016/j.fss.2025.109603 doi: 10.1016/j.fss.2025.109603
    [21] J. F. Zhang, J. W. Wang, H. K. Lam, H. X. Li, Boundary output tracking of nonlinear parabolic differential systems via fuzzy PID control, IEEE Trans. Fuzzy Syst., 32 (2024), 6863–6877. https://doi.org/10.1109/TFUZZ.2024.3432554 doi: 10.1109/TFUZZ.2024.3432554
    [22] X. Dai, H. Zuo, F. Deng, Mean square finite-time stability and stabilization of impulsive stochastic distributed parameter systems, IEEE Trans. Syst. Man Cybern. Syst., 55 (2025), 4064–4075. https://doi.org/10.1109/TSMC.2025.3547949 doi: 10.1109/TSMC.2025.3547949
    [23] X. Dai, Y. Xu, F. Deng, Mean-square finite and prescribed-time stability for nonlinear stochastic parabolic distributed parameter systems, Commun. Nonlinear Sci. Numer. Simul., 145 (2025), 108688. https://doi.org/10.1016/j.cnsns.2025.108688 doi: 10.1016/j.cnsns.2025.108688
    [24] F. Zeng, B. Ayalew, Estimation and coordinated control for distributed parameter processes with a moving radiant actuator, J. Process Control, 20 (2010), 743–753. https://doi.org/10.1016/j.jprocont.2010.04.005 doi: 10.1016/j.jprocont.2010.04.005
    [25] Y. H. Wei, J. W. Wang, Q. Zhang, Reinforcement learning-based optimal formation control of multiple robotic rollers in cooperative rolling compaction, Robotics Auton. Syst., 189 (2025), 104947. https://doi.org/10.1016/j.robot.2025.104947 doi: 10.1016/j.robot.2025.104947
    [26] M. A. Demetriou, Guidance of a moving collocated actuator/sensor for improved control of distributed parameter systems, In: 2008 47th IEEE conference on decision and control, 2008. https://doi.org/10.1109/CDC.2008.4739040
    [27] W. Mu, B. Cui, W. Li, Z. Jiang, Improving control and estimation for distributed parameter systems utilizing mobile actuator-sensor network, ISA Trans., 53 (2014), 1087–1095. https://doi.org/10.1016/j.isatra.2014.05.004 doi: 10.1016/j.isatra.2014.05.004
    [28] S. Cheng, D. A. Paley, Optimal control of a 1D diffusion process with a team of mobile actuators under jointly optimal guidance, In: 2020 American control conference, 2020. https://doi.org/10.23919/acc45564.2020.9147830
    [29] H. Fu, B. Cui, B. Zhuang, J. Zhang, Anti-collision and obstacle avoidance of mobile sensor-plus-actuator networks over distributed parameter systems with time-varying delay, Int. J. Control Autom. Syst., 19 (2021), 2373–2384. https://doi.org/10.1007/s12555-020-0317-9 doi: 10.1007/s12555-020-0317-9
    [30] Y. Liu, J. W. Wang, Z. Wu, Z. Ren, S. Xie, Robust $H_{\infty}$ control for semilinear parabolic distributed parameter systems with external disturbances via mobile actuators and sensors, IEEE Trans. Cybern., 53 (2023), 4880–4893. https://doi.org/10.1109/TCYB.2022.3150171 doi: 10.1109/TCYB.2022.3150171
    [31] W. Kang, E. Fridman, C. X. Liu, Stabilization by switching of parabolic PDEs with spatially scheduled actuators and sensors, Automatica, 147 (2023), 110668. https://doi.org/10.1016/j.automatica.2022.110668 doi: 10.1016/j.automatica.2022.110668
    [32] X. W. Zhang, Q. Zhou, H. N. Wu, J. L. Wang, Z. P. Wang, Lyapunov-based stabilization mobile control design of linear parabolic PDE systems, Chaos Soliton Fract., 175 (2023), 114002. https://doi.org/10.1016/j.chaos.2023.114002 doi: 10.1016/j.chaos.2023.114002
    [33] X. W. Zhang, H. N. Wu, $H_{\infty}$ control design for non-linear distributed parameter systems with mobile actuators and sensors, IET Control Theory Appl., 13 (2019), 2228–2238. https://doi.org/10.1049/iet-cta.2019.0092 doi: 10.1049/iet-cta.2019.0092
    [34] H. N. Wu, X. W. Zhang, Static output feedback stabilization for a linear parabolic PDE system with time-varying delay via mobile collocated actuator/sensor pairs, Automatica, 117 (2020), 108993. https://doi.org/10.1016/j.automatica.2020.108993 doi: 10.1016/j.automatica.2020.108993
    [35] X. W. Zhang, H. N. Wu, Fuzzy stabilization design for semilinear parabolic PDE systems with mobile actuators and sensors, IEEE Trans. Fuzzy Syst., 28 (2020), 474–486. https://doi.org/10.1109/TFUZZ.2019.2908139 doi: 10.1109/TFUZZ.2019.2908139
    [36] X. W. Zhang, H. N. Wu, Fuzzy control design of nonlinear time-delay parabolic PDE systems under mobile collocated actuators and sensors, IEEE Trans. Cybern., 52 (2022), 3947–3956. https://doi.org/10.1109/TCYB.2020.3020087 doi: 10.1109/TCYB.2020.3020087
    [37] X. W. Zhang, H. N. Wu, J. L. Wang, Y. Ji, N. Rong, Observer-based boundary fuzzy control design of nonlinear parabolic PDE systems using mobile sensors, IEEE Trans. Fuzzy Syst., 31 (2023), 3485–3494. https://doi.org/10.1109/TFUZZ.2023.3260102 doi: 10.1109/TFUZZ.2023.3260102
    [38] S. Cheng, D. A. Paley, Cooperative estimation and control of a diffusion-based spatiotemporal process using mobile sensors and actuators, Auton. Robots, 47 (2023), 715–731. https://doi.org/10.1007/s10514-023-10105-9 doi: 10.1007/s10514-023-10105-9
    [39] N. A. Gatsonis, M. A. Demetriou, T. Egorova, Real-time prediction of gas contaminant concentration from a ground intruder using a UAV, In: 2015 IEEE international symposium on technologies for homeland security, 2015. https://doi.org/10.1109/THS.2015.7225276
    [40] M. A. Demetriou, Controlling 2D PDEs using mobile collocated actuators-sensors and their simultaneous guidance constrained over path-dependent reachability regions, In: 2021 American control conference, 2021. https://doi.org/10.23919/acc50511.2021.9482892
    [41] Y. Q. Chen, Z. Wang, J. Liang, Actuation scheduling in mobile actuator networks for spatial-temporal feedback control of a diffusion process with dynamic obstacle avoidance, In: IEEE international conference mechatronics and automation, 2005. https://doi.org/10.1109/ICMA.2005.1626644
    [42] Y. Q. Chen, Z. Wang, J. Liang, Optimal dynamic actuator location in distributed feedback control of a diffusion process, In: Proceedings of the 44th IEEE conference on decision and control, 2005. https://doi.org/10.1109/cdc.2005.1583065
    [43] S. Cheng, D. A. Paley, Optimal control of a 2D diffusion-advection process with a team of mobile actuators under jointly optimal guidance, Automatica, 133 (2021), 109866. https://doi.org/10.1016/j.automatica.2021.109866 doi: 10.1016/j.automatica.2021.109866
    [44] S. Cheng, D. A. Paley, Optimal guidance and estimation of a 2D diffusion-advection process by a team of mobile sensors, Automatica, 137 (2022), 110112. https://doi.org/10.1016/j.automatica.2021.110112 doi: 10.1016/j.automatica.2021.110112
    [45] M. A. Demetriou, Guidance of mobile actuator-plus-sensor networks for improved control and estimation of distributed parameter systems, IEEE Trans. Autom. Control, 55 (2010), 1570–1584. https://doi.org/10.1109/tac.2010.2042229 doi: 10.1109/tac.2010.2042229
    [46] M. A. Demetriou, Adaptive control of 2-D PDEs using mobile collocated actuator/sensor pairs with augmented vehicle dynamics, IEEE Trans. Autom. Control, 57 (2012), 2979–2993. https://doi.org/10.1109/tac.2012.2196402 doi: 10.1109/tac.2012.2196402
    [47] J. W. Wang, Y. Q. Liu, C. Y. Sun, Observer-based dynamic local piecewise control of a linear parabolic PDE using non-collocated local piecewise observation, IET Control Theory Appl., 12 (2018), 346–358. https://doi.org/10.1049/iet-cta.2017.0797 doi: 10.1049/iet-cta.2017.0797
    [48] R. F. Curtain, H. Zwart, An introduction to infinite-dimensional linear systems theory, New York: Springer, 1995. https://doi.org/10.1007/978-1-4612-4224-6
    [49] J. W. Wang, J. M. Wang, Dynamic compensator design of linear parabolic MIMO PDEs in $N$-dimensional spatial domain, IEEE Trans. Autom. Control, 66 (2021), 1399–1406. https://doi.org/10.1109/TAC.2020.2994165 doi: 10.1109/TAC.2020.2994165
    [50] A. Pazy, Semigroups of linear operators and applications to partial differential equations, New York: Springer, 1983. https://doi.org/10.1007/978-1-4612-5561-1
    [51] H. Peng, Q. Zhu, Finite-time stability and stabilization of highly nonlinear stochastic systems via the noise control, IEEE Trans. Autom. Control, 2026, in press. https://doi.org/10.1109/TAC.2026.3660601
    [52] Q. Zhu, Event-triggered sampling problem for exponential stability of stochastic nonlinear delay systems driven by Lévy processes, IEEE Trans. Autom. Control, 70 (2025), 1176–1183. https://doi.org/10.1109/tac.2024.3448128 doi: 10.1109/tac.2024.3448128
    [53] H. Xu, Q. Zhu, Stability of discrete-time impulsive stochastic systems with hybrid non-deterministic delays, IEEE Trans. Autom. Control, 2026, in press. https://doi.org/10.1109/TAC.2026.3666702
    [54] J. W. Wang, F. Wang, H. N. Wu, Z. Y. Liu, Safe RL-based adaptive cooperative game control of wing deformation and flight state tracking for morphing hypersonic vehicles, IEEE Trans. Aerosp. Electron. Syst., 61 (2025), 10826–10838. https://doi.org/10.1109/taes.2025.3560610 doi: 10.1109/taes.2025.3560610
  • Reader Comments
  • © 2026 the Author(s), licensee AIMS Press. This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0)
通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索

Metrics

Article views(36) PDF downloads(4) Cited by(0)

Article outline

Figures and Tables

Figures(4)  /  Tables(1)

Other Articles By Authors

/

DownLoad:  Full-Size Img  PowerPoint
Return
Return

Catalog