2604003767
  • Open Access
  • Article

H Control for Multi-Agent Systems under Two-Way Amplify-and-Forward Relay Networks: The Event-Trigger Case

  • Jiaxin Chen,   
  • Yezheng Wang *,   
  • Fan Wang

Received: 25 Mar 2026 | Revised: 21 Apr 2026 | Accepted: 27 Apr 2026 | Published: 30 Apr 2026

Abstract

This paper addresses the finite-horizon H control problem for the two-way amplify-and-forward (AF) relay-assisted multi-agent system. To enhance communication quality and mitigate channel fading effects, a two-way AF relay protocol is introduced to coordinate data transmission among agents. Based on channel statistical characteristics and incorporating an event-triggered mechanism, this paper designs an H∞ control protocol to ensure that the dynamic system satisfies the specified H∞ performance metrics within a finite horizon. First, sufficient conditions are established for the system to satisfy the given H∞ performance requirements. Then, by solving two coupled backward Riccati difference equations under the H∞ performance constraints, the feedback gain matrix of the event-triggered controller is determined. Finally, the effectiveness of the proposed control strategy is verified through numerical simulations.

References 

  • 1.

    Hou, Y.; Zhao, J.; Zhang, R.; et al. UAV swarm cooperative target search: A multi-agent reinforcement learning approach. IEEE Trans. Intell. Veh. 2024, 9, 568–578.

  • 2.

    Li, L.; Shi, P.; Ahn, C.K. Distributed iterative FIR consensus filter for multi-agent systems over sensor networks. IEEE Trans. Cybern. 2022, 52, 4647–4660.

  • 3.

    Yao, T.; Xu, Y.; Wang, H.; et al. Multi-agent fuzzy reinforcement learning with LLM for cooperative navigation of endovascular robotics. IEEE Trans. Fuzzy Syst. 2026, 34, 1109–1119.

  • 4.

    Sebasti´an, E.; Duong, T.; Atanasov, N.; et al. Physics-informed multiagent reinforcement learning for distributed multirobot problems. IEEE Trans. Robot. 2025, 41, 4499–4517.

  • 5.

    Jia, M.; Cui, Z.; Hug, G. Enhancing LLMs for power system simulations: A feedback-driven multi-agent framework. IEEE Trans. Smart Grid 2025, 16, 5556–5572.

  • 6.

    Chen, T.; Zhang, C.; Jing, W.; et al. Distributed multi-agent fusion state estimation method based on finite-time average consensus for large-scale power systems. Inf. Fusion 2026, 127, 103753.

  • 7.

    Ning, B.; Han, Q.-L.; Zuo, Z.; et al. Fixed-time and prescribed-time consensus control of multi-agent systems and its applications: A survey of recent trends and methodologies. IEEE Trans. Ind. Inform. 2023, 19, 1121–1135.

  • 8.

    Abebe, H.B.; Hwang, C.-L. Bipartite formation-change of radial-cascade connected multi-UAV using distributed active disturbance estimator-based fixed-time tracking control. Int. J. Syst. Sci. 2025, 1–20. https://doi.org/10.1080/00207721.2025.2581779.

  • 9.

    Chen, B.; Hu, J.; Zhao, Y.; et al. Finite-time velocity-free rendezvous control of multiple AUV systems with intermittent communication. IEEE Trans. Syst. Man Cybern. Syst. 2022, 52, 6618–6629.

  • 10.

    Ozsoyeller, D.; Ozkasap, O.O.; Aloqaily, M. M-rendezvous: Multi-agent asynchronous rendezvous search technique. Future Gener. Comput. Syst. 2022, 126, 185–195.

  • 11.

    Gai, W.; Zheng, Y.; Yang, Y.; et al. Disturbance-observer-based distributed formation control for multi-agent systems with dynamic event-triggered mechanism. Int. J. Syst. Sci. 2025, 56, 4115–4130.

  • 12.

     Yu, L.; Ding, J.; Peng, H.; et al. Sampled-data based containment control for a class of nonlinear multi-agent systems with dynamic leaders and control saturation. Int. J. Netw. Dyn. Intell. 2025, 4, 100011.

  • 13.

    Li, C.; Liu, Y.; Gao, M.; et al. Fault-tolerant formation consensus control for time-varying multi-agent systems with stochastic communication protocol. Int. J. Netw. Dyn. Intell. 2024, 3, 100004.

  • 14.

    Cai, Y.; Yang, X.; Yang, Y.; et al. Leader-following privacy-preserving consensus control of nonlinear multi-agent systems: A state decomposition approach. Int. J. Syst. Sci. 2025, 56, 2284–2295.

  • 15.

    Li, H.; Liu, S.; Meng, G.; et al. Dynamic observer-based H∞ consensus control of fractional-order multi-agent systems. IEEE Trans. Autom. Sci. Eng. 2025, 22, 12720–12729.

  • 16.

    Lin, H.; Dong, J.; Park, J.H. Observer-based H∞ fault-tolerant tracking control of multi-agent systems with nonideal communication links and external disturbances. IEEE Trans. Autom. Sci. Eng. 2025, 22, 14096–14107.

  • 17.

    Zhuang, H.; Wu, S.; Razoumny, V.Y.; et al. H∞ control for cooperative multi-agent systems: Event-triggered off-policy reinforcement learning approach. Neurocomputing 2025, 647, 130576.

  • 18.

    Na, H.-W.; Park, P. LMI approach of H∞ consensus for multi-agent systems under Markov switching topology by dynamic output-feedback controller. ISA Trans. 2025, 157, 1–10.

  • 19.

    Zhou, T.; Liu, C.; Wang, W. Nonfragile robust H∞ containment control for multi-agent systems with a time-varying delay. J. Frankl. Inst. 2024, 361, 106732.

  • 20.

    Tajudeen, M.M.; Banu, K.A.; Rajchakit, G. H∞ secure control for complex dynamical networks with actuator failure under attacks via adaptive event-triggered mechanism. Circuits Syst. Signal Process. 2025, 44, 4704–4722.

  • 21.

    Li, J.; Wang, Z.; Hu, J.; et al. Cubature Kalman fusion filtering under amplify-and-forward relays with randomly varying channel parameters. IEEE/CAA J. Autom. Sin. 2025, 12, 356–368.

  • 22.

    Li, G.; Wang, Z.; Bai, X.; et al. Sequential fusion estimation for renewable energy microgrids under hybrid attacks: Handling filter-and-forward relays. IEEE Trans. Ind. Inform. 2025, 21, 8224–8235.

  • 23.

    Meng, X.; Wang, Z.; Wang, F.; et al. State estimation for nonlinear complex dynamical networks with random coupling strengths: A decode-and-forward relay-based strategy. IEEE Trans. Syst. Man Cybern. Syst. 2024, 54, 4749–4760.

  • 24.

    Tan, H.; Shen, B.; Li, Q.; et al. Recursive filtering for stochastic systems with filter-and-forward successive relays. IEEE/CAA J. Autom. Sin. 2024, 11, 1202–1212.

  • 25.

    Wang, F.; Wang, Z.; Liang, J.; et al. Recursive filtering for two-dimensional systems with amplify-and-forward relays: Handling degraded measurements and dynamic biases. Inf. Fusion 2024, 108, 102368.

  • 26.

    Wang, F.; Wang, Z.; Liang, J.; et al. Recursive state estimation for two-dimensional systems over decode-and-forward relay channels: A local minimum-variance approach. Inf. Sci. 2024, 678, 120928.

  • 27.

    Rankov, B.; Wittneben, A. Spectral efficient protocols for half-duplex fading relay channels. IEEE J. Sel. Areas Commun. 2007, 25, 379–389.

  • 28.

    Fu, Z.; Moon, J.; Hwang, S.; et al. Covert communications in multi-antenna two-way relay systems. IEEE Trans. Veh. Technol. 2025, 74, 14069–14080.

  • 29.

    Zhao, Z.; Zhu, X.; Zhang, Y.; et al. Joint RIS and beamforming design for secure and energy-efficient two-way relay communications. IEEE Trans. Mob. Comput. 2025, 24, 7440–7457.

  • 30.

    Liu, L.; Zhao, Y.; Yang, Y.; et al. Power allocation for cell-free massive MIMO two-way relay systems with low-resolution ADCs. IEEE Trans. Commun. 2025, 73, 8181–8197.

  • 31.

    Zhang, T.; Li, B.; Chen, G.; et al. Secure communication for UAV two-way relay networks. Chin. J. Aeronaut. 2025, 38, 103421.

  • 32.

    Kurma, S.; Sharma, P.K.; Dhok, S.; et al. Adaptive AF/DF two-way relaying in FD multiuser URLLC system with user mobility. IEEE Trans. Wirel. Commun. 2022, 21, 10224–10241.

  • 33.

    Ma, J.; Huang, C.; Li, Q. Energy efficiency of full- and half-duplex decode-and-forward relay channels. IEEE Internet Things J. 2022, 9, 9730–9748.

  • 34.

    Tong, J.; Zhong, C. Full-duplex two-way AF relaying systems with imperfect interference cancellation in Nakagami-m
    fading channels. Sci. China Inf. Sci. 2021, 64, 182310.

  • 35.

    Althunibat, S.; Mesleh, R. Two-way relay systems: Evaluating the impact of pre-equalization and constellation design. IEEE
    Trans. Veh. Technol. 2026, 1–10. https://doi.org/10.1109/TVT.2026.3668798.

  • 36.

    Zakir, Z.; Al Seragi, E.M.; Ahmad, W.; et al. Self-identifying amplify-and-forward relay for localization assistance. IEEE
    Trans. Microw. Theory Techn. 2025, 73, 6809–6824.

  • 37.

    Cao, L.; Cheng, Z.; Liu, Y.; et al. Event-based adaptive NN fixed-time cooperative formation for multi-agent systems. IEEE
    Trans. Neural Netw. Learn. Syst. 2024, 35, 6467–6477.

  • 38.

    Ye, Y.; Fan, D.; Zhang, X. Adaptive event-triggered control for uncertain strict-feedback nonlinear systems with actuator
    faults: A fully actuated system approach. Int. J. Syst. Sci. 2025, 56, 3085–3097.

  • 39.

    Zhao, L.; Lu, J.; Liu, Y.; et al. Dynamic event-triggered control for leader-following consensus of nonlinear multi-agent
    systems against malicious attacks. IEEE Trans. Inf. Forensics Secur. 2025, 20, 2424–2436.

  • 40.

    Han, H.; Jin, H. Impulsive control of nonlinear multi-agent systems: A hybrid fuzzy adaptive and event-triggered strategy.
    IEEE Trans. Fuzzy Syst. 2025, 33, 1889–1898.

  • 41.

    Grienggrai, R.; Banu, K.A.; Aparna, T.; et al. Event-triggered secure control for Markov jump neural networks with
    time-varying delays and subject to cyber-attacks via state estimation fuzzy approach. Int. J. Syst. Sci. 2025, 56, 211–226.

  • 42.

    Liang, Y.; Xiao, L.; Yang, D.; et al. Joint trajectory and resource optimization for UAV-aided two-way relay networks. IEEE
    Trans. Veh. Technol. 2021, 71, 639–652.

  • 43.

    Penrose, R. On best approximate solutions of linear matrix equations. Math. Proc. Camb. Philos. Soc. 1956, 52, 17–19.

  • 44.

    Mathai, A.; Provost, S. Quadratic Forms in Random Variables: Theory and Applications; Dekker: New York, NY, USA, 1992.

  • 45.

    Dai, D.; Li, J.; Song, Y.; et al. Event-based recursive filtering for nonlinear bias-corrupted systems with amplify-and-forward relays. Syst. Sci. Control Eng. 2024, 12, 2332419.

  • 46.

    Liang, C.; He, D.; Xu, C. Distributed H∞ moving horizon estimation over energy harvesting sensor networks. Int. J. Syst. Sci. 2025, 56, 3743–3757.

  • 47.

    Cai, S.; Liang, J. Recursive filtering for nonlinear systems with relay communication, energy harvesting and correlated noises. Int. J. Netw. Dyn. Intell. 2025, 4, 100021.

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How to Cite
Chen, J.; Wang, Y.; Wang, F. H Control for Multi-Agent Systems under Two-Way Amplify-and-Forward Relay Networks: The Event-Trigger Case. Complex Systems Stability & Control 2026, 2 (2), 6. https://doi.org/10.53941/cssc.2026.100009.
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