This paper investigates an adaptive event-triggered interval observer for omni-directional automated guided vehicles (OAGVs) subject to external disturbances. First, the kinematic model of the OAGV is established, and its state-space equation is derived using the Euler–Lagrange equation. Then, an adaptive event-triggered approach is employed for interval observer design. Meanwhile, a dynamic weighting factor coupling the upper and lower bounds of the estimation states is introduced, and the weighted estimation error is proven to be bounded in finite time. Furthermore, the Zeno phenomenon is avoided. Finally, numerical simulation results validate the effectiveness of the proposed adaptive event-triggered interval observer for OAGVs.
BorgersDPHeemelsWMH (2014) Event-separation properties of event-triggered control systems. IEEE Transactions on Automatic Control59(10): 2644–2656.
2.
BuiTLDoanPTKimHK, et al. (2014) Adaptive motion controller design for an omnidirectional AGV based on laser sensor. In: ZelinkaIDuyVChaJ (eds) AETA 2013: Recent Advances in Electrical Engineering and Related Sciences. Berlin and Heidelberg: Springer, pp. 509–523.
ChaiXWangQDiaoQ, et al. (2022) Sampled-data-based dynamic event-triggered formation control for nonlinear multi-agent systems. Transactions of the Institute of Measurement and Control44(14): 2719–2728.
5.
ChenPJYangSYChenYP, et al. (2021) Slip estimation and compensation control of omnidirectional wheeled automated guided vehicle. Electronics10(7): 840.
6.
ChoiJ (2025) Advanced omni-directional mobility system for human-friendly industrial warehouse operations. IEEE Transactions on Industry Applications61: 4364–4372.
7.
DimarogonasDVFrazzoliEJohanssonKH (2011) Distributed event-triggered control for multi-agent systems. IEEE Transactions on Automatic Control57(5): 1291–1297.
8.
FengBYeQ (2021) Operations management of smart logistics: A literature review and future research. Frontiers of Engineering Management8: 344–355.
9.
GeXHanQLZhangXM, et al. (2021) Dynamic event-triggered control and estimation: A survey. International Journal of Automation and Computing18(6): 857–886.
Gucik-DerignyDRaïssiTZolghadriA (2016) A note on interval observer design for unknown input estimation. International Journal of Control89(1): 25–37.
12.
HuSYueDYinX, et al. (2016) Adaptive event-triggered control for nonlinear discrete-time systems. International Journal of Robust and Nonlinear Control26(18): 4104–4125.
13.
HuangJCheHRaïssiT, et al. (2021) Functional interval observer for discrete-time switched descriptor systems. IEEE Transactions on Automatic Control67(5): 2497–2504.
14.
HuangJFanJDinhTN, et al. (2023) Event-triggered interval estimation method for cyber–physical systems with unknown inputs. ISA Transactions135: 1–12.
15.
HuangJLiCSunY, et al. (2025) Improved functional interval observer for Mecanum-wheels omnidirectional automated guided vehicle. International Journal of Robust and Nonlinear Control35(1): 120–140.
16.
HuongDCTrinhH (2023) Dynamic event-triggered distributed interval functional observers for interconnected systems. Asian Journal of Control25(3): 2194–2203.
17.
JavedMAMuramFUPunnekkatS, et al. (2021) Safe and secure platooning of automated guided vehicles in industry 4.0. Journal of Systems Architecture121: 102309.
18.
KhanAXieWZhangB, et al. (2021) A survey of interval observers design methods and implementation for uncertain systems. Journal of the Franklin Institute358(6): 3077–3126.
19.
KimJWooSKimJ, et al. (2012) Inertial navigation system for an automatic guided vehicle with Mecanum wheels. International Journal of Precision Engineering and Manufacturing13: 379–386.
20.
LemmonM (2010) Event-triggered feedback in control, estimation, and optimization. Networked Control Systems406: 293–358.
21.
LiCHuangJSunY, et al. (2023) Observer-based sliding mode control for Omni-Directional AGV. In:2023 6th international conference on robotics, control and automation engineering (RCAE), Suzhou, China, 3–5 November, pp. 147–151. New York: IEEE.
22.
LiCHuangJSunY, et al. (2024) Interval estimation for Omni-directional automated guided vehicle: An approach based on reachability analysis. Journal of the Franklin Institute361(16): 107139.
23.
LiHWuCYinS, et al. (2015) Observer-based fuzzy control for nonlinear networked systems under unmeasurable premise variables. IEEE Transactions on Fuzzy Systems24(5): 1233–1245.
24.
LiXHeDZhangQ, et al. (2025) Reinforcement learning-based adaptive event-triggered control of multi-agent systems with time-varying dead-zone. Applied Mathematics and Computation486: 129059.
25.
MeseguerJPuigVEscobetT, et al. (2010) Observer gain effect in linear interval observer-based fault detection. Journal of Process Control20(8): 944–956.
26.
MeslemNRabehiDRamdaniN (2022) Event-triggered interval-based state estimator for continuous-time linear systems. Journal of the Franklin Institute359(16): 9168–9192.
27.
NaderiSRezaieBFaraminM (2020) Designing an interval type-2 fuzzy disturbance observer for a class of nonlinear systems based on modified particle swarm optimization. Applied Intelligence50(11): 3731–3747.
28.
RotondoDCristofaroAJohansenTA, et al. (2019) Robust fault and icing diagnosis in unmanned aerial vehicles using LPV interval observers. International Journal of Robust and Nonlinear Control29(16): 5456–5480.
29.
TabuadaP (2007) Event-triggered real-time scheduling of stabilizing control tasks. IEEE Transactions on Automatic Control52(9): 1680–1685.
30.
TaheriHQiaoBGhaeminezhadN (2015) Kinematic model of a four Mecanum wheeled mobile robot. International Journal of Computer Applications113(3): 6–9.
31.
WanJLiXDaiHN, et al. (2020) Artificial-intelligence-driven customized manufacturing factory: Key technologies, applications, and challenges. Proceedings of the IEEE109(4): 377–398.
32.
XuFTanJRaïssiT, et al. (2020) Design of optimal interval observers using set-theoretic methods for robust state estimation. International Journal of Robust and Nonlinear Control30(9): 3692–3705.
33.
YinZHuangJZhangY (2023) Event-triggered interval observer design for a class of Euler-Lagrange systems with disturbances. Transactions of the Institute of Measurement and Control. Epub ahead of print 2 May. DOI: 10.1177/01423312231165095.
34.
YuYDingS (2024) Dynamic event-triggered predictive control for DoS attacks-based discrete-time networked linear systems. Transactions of the Institute of Measurement and Control46(2): 351–358.
35.
YuanRDouJLiJ, et al. (2023) Multi-robot task allocation in e-commerce RMFS based on deep reinforcement learning. Mathematical Biosciences and Engineering20(2): 1903–1918.
36.
ZhangHHuangJHeS (2022) Fractional-order interval observer for multiagent nonlinear systems. Fractal and Fractional6(7): 355.
37.
ZhangSHeJYangY, et al. (2024) Outlier-resistant observer-based control for interval type-2 TS fuzzy systems under adaptive event-triggered protocols. Transactions of the Institute of Measurement and Control46(1): 183–192.
