Structure-Preserving Safe and Robust Formation Control of Autonomous Surface Vehicles via a Port-Hamiltonian Framework
Authors
Zehua Jia, Kun Xie, Xiaoshan Bai, Shan Xue, Weidong Zhang
Abstract
This article proposes a robust and safe structure-preserving formation control framework for multiple autonomous surface vehicles (ASVs) within a port-Hamiltonian (PH) formulation. Different from conventional signal-based designs, the proposed approach regulates formation behaviors from an energy perspective, where the desired formation configuration is explicitly embedded into the closed-loop Hamiltonian and shaped via interconnection and damping assignment passivity-based control (IDA-PBC). This energy-centric design yields a physically interpretable and engineering-friendly controller, facilitating systematic tuning and practical implementation. To enhance robustness against time-varying environmental disturbances and model uncertainties, a structure-preserving observer is introduced to estimate and compensate lumped uncertainties without disrupting the intrinsic PH interconnection and damping structure. Furthermore, prescribed performance control is incorporated into the PH framework as a safety-oriented auxiliary mechanism, by transforming safety-constrained formation errors into PH-compatible states, thereby guaranteeing intervehicle collision avoidance during close-proximity operations while maintaining PH structure. Rigorous stability analysis establishes the input-to-state stability of the resulting closed-loop system. Numerical simulations and robot operating system (ROS)/Gazebo-based experiments validate the effectiveness and practicality of the proposed structure-preserving observer-based IDA-PBC (SPO-IDA) formation control strategy for safe and robust multi-ASV formation control in dynamic marine environments.
Citation
- Journal: IEEE Transactions on Industrial Informatics
- Year: 2026
- Volume: 22
- Issue: 9
- Pages: 8080–8091
- Publisher: Institute of Electrical and Electronics Engineers (IEEE)
- DOI: 10.1109/tii.2026.3690546
BibTeX
@article{Jia_2026,
title={{Structure-Preserving Safe and Robust Formation Control of Autonomous Surface Vehicles via a Port-Hamiltonian Framework}},
volume={22},
ISSN={1941-0050},
DOI={10.1109/tii.2026.3690546},
number={9},
journal={IEEE Transactions on Industrial Informatics},
publisher={Institute of Electrical and Electronics Engineers (IEEE)},
author={Jia, Zehua and Xie, Kun and Bai, Xiaoshan and Xue, Shan and Zhang, Weidong},
year={2026},
pages={8080--8091}
}References
- Peng Z, Wang J, Wang D, Han Q-L (2021) An Overview of Recent Advances in Coordinated Control of Multiple Autonomous Surface Vehicles. IEEE Trans Ind Inf 17(2):732–745. https://doi.org/10.1109/tii.2020.300434 – 10.1109/tii.2020.3004343
- Shi Y, Shen C, Fang H, Li H (2017) Advanced Control in Marine Mechatronic Systems: A Survey. IEEE/ASME Trans Mechatron 22(3):1121–1131. https://doi.org/10.1109/tmech.2017.266052 – 10.1109/tmech.2017.2660528
- Zuo Z, Han Q-L, Ning B, Ge X, Zhang X-M (2018) An Overview of Recent Advances in Fixed-Time Cooperative Control of Multiagent Systems. IEEE Trans Ind Inf 14(6):2322–2334. https://doi.org/10.1109/tii.2018.281724 – 10.1109/tii.2018.2817248
- Zhu G, Ma Y, Hu S (2023) Event-Triggered Adaptive PID Fault-Tolerant Control of Underactuated ASVs Under Saturation Constraint. IEEE Trans Syst Man Cybern, Syst 53(8):4922–4933. https://doi.org/10.1109/tsmc.2023.325653 – 10.1109/tsmc.2023.3256538
- Jia Z, Lu H, Li S, Zhang W (2022) Distributed dynamic rendezvous control of the AUV-USV joint system with practical disturbance compensations using model predictive control. Ocean Engineering 258:111268. https://doi.org/10.1016/j.oceaneng.2022.11126 – 10.1016/j.oceaneng.2022.111268
- Dai S-L, He S, Cai H, Yang C (2022) Adaptive Leader–Follower Formation Control of Underactuated Surface Vehicles With Guaranteed Performance. IEEE Trans Syst Man Cybern, Syst 52(3):1997–2008. https://doi.org/10.1109/tsmc.2020.303612 – 10.1109/tsmc.2020.3036120
- Peng Z, Wang D, Li T, Han M (2020) Output-Feedback Cooperative Formation Maneuvering of Autonomous Surface Vehicles With Connectivity Preservation and Collision Avoidance. IEEE Trans Cybern 50(6):2527–2535. https://doi.org/10.1109/tcyb.2019.291471 – 10.1109/tcyb.2019.2914717
- Peng Z, Liu L, Wang J (2021) Output-Feedback Flocking Control of Multiple Autonomous Surface Vehicles Based on Data-Driven Adaptive Extended State Observers. IEEE Trans Cybern 51(9):4611–4622. https://doi.org/10.1109/tcyb.2020.300999 – 10.1109/tcyb.2020.3009992
- Wen G, Fu J, Wang B, Wang X, Shen H (2026) Robust Formation Tracking of ASVs With Nonconservative Collision Avoidance: A Control Barrier Function-Based Approach. IEEE Trans Ind Electron 73(6):9174–9186. https://doi.org/10.1109/tie.2025.364984 – 10.1109/tie.2025.3649849
- Wen G, Lam J, Fu J, Wang S (2024) Distributed MPC-Based Robust Collision Avoidance Formation Navigation of Constrained Multiple USVs. IEEE Trans Intell Veh 9(1):1804–1816. https://doi.org/10.1109/tiv.2023.331536 – 10.1109/tiv.2023.3315367
- Xu B, Dai Y, Suleman A, Shi Y (2025) Distributed fault-tolerant control of multi-UAV formation for dynamic leader tracking: A Lyapunov-based MPC framework. Automatica 175:112179. https://doi.org/10.1016/j.automatica.2025.11217 – 10.1016/j.automatica.2025.112179
- Jia Z, Zhang K, Shi Y, Zhang W (2024) Safety-Preserving Lyapunov-Based Model Predictive Rendezvous Control for Heterogeneous Marine Vehicles Subject to External Disturbances. IEEE Trans Cybern 54(9):5244–5256. https://doi.org/10.1109/tcyb.2024.337791 – 10.1109/tcyb.2024.3377919
- Van Parys R, Pipeleers G (2017) Distributed MPC for multi-vehicle systems moving in formation. Robotics and Autonomous Systems 97:144–152. https://doi.org/10.1016/j.robot.2017.08.00 – 10.1016/j.robot.2017.08.009
- He S, Wang M, Dai S-L, Luo F (2019) Leader–Follower Formation Control of USVs With Prescribed Performance and Collision Avoidance. IEEE Trans Ind Inf 15(1):572–581. https://doi.org/10.1109/tii.2018.283973 – 10.1109/tii.2018.2839739
- Wang P, Yu C, Lv M, Park JH (2024) Improving Formation Maneuvering of Unmanned Surface Vehicles: A Finite-Time Distributed Approach With Velocity Constraints. IEEE Trans Intell Veh 9(10):6195–6207. https://doi.org/10.1109/tiv.2024.336343 – 10.1109/tiv.2024.3363438
- Lv Z, Chen J, Xie J, Xu Z (2025) A Backstepping Tracking Control Strategy Based on Deep Reinforcement Learning for Vehicle Platoon. IEEE Trans Veh Technol 74(6):8707–8720. https://doi.org/10.1109/tvt.2025.353652 – 10.1109/tvt.2025.3536520
- Yan T, Xu Z, Yang SX (2023) Consensus Formation Tracking for Multiple AUV Systems Using Distributed Bioinspired Sliding Mode Control. IEEE Trans Intell Veh 8(2):1081–1092. https://doi.org/10.1109/tiv.2022.317564 – 10.1109/tiv.2022.3175647
- Qin H, Si J, Wang N, Gao L (2023) Fast fixed-time nonsingular terminal sliding-mode formation control for autonomous underwater vehicles based on a disturbance observer. Ocean Engineering 270:113423. https://doi.org/10.1016/j.oceaneng.2022.11342 – 10.1016/j.oceaneng.2022.113423
- Boo J, Chwa D (2023) Integral Sliding Mode Control-Based Robust Bidirectional Platoon Control of Vehicles With the Unknown Acceleration and Mismatched Disturbance. IEEE Trans Intell Transport Syst 24(10):10881–10894. https://doi.org/10.1109/tits.2023.328103 – 10.1109/tits.2023.3281033
- Brogliato B, Lozano R, Maschke B, Egeland O (2020) Dissipative Systems Analysis and Control. Springer International Publishin – 10.1007/978-3-030-19420-8
- Nageshrao SP, Lopes GAD, Jeltsema D, Babuska R (2016) Port-Hamiltonian Systems in Adaptive and Learning Control: A Survey. IEEE Trans Automat Contr 61(5):1223–1238. https://doi.org/10.1109/tac.2015.245849 – 10.1109/tac.2015.2458491
- Rashad R, Califano F, Stramigioli S (2019) Port-Hamiltonian Passivity-Based Control on SE(3) of a Fully Actuated UAV for Aerial Physical Interaction Near-Hovering. IEEE Robot Autom Lett 4(4):4378–4385. https://doi.org/10.1109/lra.2019.293286 – 10.1109/lra.2019.2932864
- Rashad R, Engelen JBC, Stramigioli S (2019) Energy Tank-Based Wrench/Impedance Control of a Fully-Actuated Hexarotor: A Geometric Port-Hamiltonian Approach. 2019 International Conference on Robotics and Automation (ICRA) 6418–642 – 10.1109/icra.2019.8793939
- Nageshrao SP, Lopes GAD, Jeltsema D, Babuska R (2016) Port-Hamiltonian Systems in Adaptive and Learning Control: A Survey. IEEE Trans Automat Contr 61(5):1223–1238. https://doi.org/10.1109/tac.2015.245849 – 10.1109/tac.2015.2458491
- Ortega R, van der Schaft A, Maschke B, Escobar G (2002) Interconnection and damping assignment passivity-based control of port-controlled Hamiltonian systems. Automatica 38(4):585–596. https://doi.org/10.1016/s0005-1098(01)00278- – 10.1016/s0005-1098(01)00278-3
- Ramírez H, Sbarbaro D, Ortega R (2009) On the control of non-linear processes: An IDA–PBC approach. Journal of Process Control 19(3):405–414. https://doi.org/10.1016/j.jprocont.2008.06.01 – 10.1016/j.jprocont.2008.06.018
- Gómez-Estern F, Van der Schaft AJ (2004) Physical Damping in IDA-PBC Controlled Underactuated Mechanical Systems. European Journal of Control 10(5):451–468. https://doi.org/10.3166/ejc.10.451-46 – 10.3166/ejc.10.451-468
- Guerrero-Sánchez ME, Hernández-González O, Valencia-Palomo G, Mercado-Ravell DA, López-Estrada FR, Hoyo-Montaño JA (2021) Robust IDA-PBC for under-actuated systems with inertia matrix dependent of the unactuated coordinates: application to a UAV carrying a load. Nonlinear Dyn 105(4):3225–3238. https://doi.org/10.1007/s11071-021-06776- – 10.1007/s11071-021-06776-7
- Duong T, Altawaitan A, Stanley J, Atanasov N (2024) Port-Hamiltonian Neural ODE Networks on Lie Groups for Robot Dynamics Learning and Control. IEEE Trans Robot 40:3695–3715. https://doi.org/10.1109/tro.2024.342843 – 10.1109/tro.2024.3428433
- Zhou W, Xu Z, Wu Y, Xiang J, Li Y (2023) Energy-based trajectory tracking control of under-actuated unmanned surface vessels. Ocean Engineering 288:116166. https://doi.org/10.1016/j.oceaneng.2023.11616 – 10.1016/j.oceaneng.2023.116166
- Lv C, Yu H, Chen J, Zhao N, Chi J (2022) Trajectory tracking control for unmanned surface vessel with input saturation and disturbances via robust state error IDA-PBC approach. Journal of the Franklin Institute 359(5):1899–1924. https://doi.org/10.1016/j.jfranklin.2022.01.03 – 10.1016/j.jfranklin.2022.01.036
- Jin L, Yu S, Zhao Q, Shi G, Wu X (2024) Fixed-time \(H_{\infty}\) tracking control of unmanned underwater vehicles with disturbance rejection via Port-Hamiltonian framework. Ocean Engineering 293:116533. https://doi.org/10.1016/j.oceaneng.2023.11653 – 10.1016/j.oceaneng.2023.116533
- Jia Z, Qiao L, Zhang W (2020) Adaptive tracking control of unmanned underwater vehicles with compensation for external perturbations and uncertainties using Port-Hamiltonian theory. Ocean Engineering 209:107402. https://doi.org/10.1016/j.oceaneng.2020.10740 – 10.1016/j.oceaneng.2020.107402
- Lv C, Wang Z, Zhang Y, Chen J, Yu H (2024) Cooperative formation control of multiple unmanned surface vessels based on state error port control Hamiltonian framework. Ocean Engineering 313:119410. https://doi.org/10.1016/j.oceaneng.2024.11941 – 10.1016/j.oceaneng.2024.119410
- van der Schaft A (2007) Port-Hamiltonian systems: an introductory survey. Proceedings of the International Congress of Mathematicians Madrid, August 22–30, 2006 1339–136 – 10.4171/022-3/65
- Jia Z, Hu Z, Zhang W (2019) Adaptive output-feedback control with prescribed performance for trajectory tracking of underactuated surface vessels. ISA Transactions 95:18–26. https://doi.org/10.1016/j.isatra.2019.04.03 – 10.1016/j.isatra.2019.04.035