網路通訊延遲下無人水面載具領導者–追隨者編隊之預估控制研究

Abstract

本研究探討無人水面載具（Unmanned Surface Vehicle, USV）在通訊延遲環境下之領導者–追隨者編隊控制問題。由於網路通訊延遲會導致跟隨者無法即時取得領導者狀態資訊，進而影響追蹤性能並可能造成系統不穩定。為解決此問題，本研究提出一種基於預估器（predictor）的編隊控制方法，利用歷史資訊重建領導者當前狀態，並結合非線性軌跡追蹤控制器進行延遲補償。在無延遲情況下，透過Lyapunov 方法證明編隊追蹤誤差系統之漸近穩定性；進一步考慮通訊延遲，證明預估器可有效重建領導者狀態，使延遲系統等價於無延遲系統，並透過cascade理論分析整體系統之穩定性。最後，本研究透過模擬與實驗，在不同通訊延遲條件下驗證所提出方法之有效性。模擬結果確認 predictor-based compensation 能降低通訊延遲造成的影響；實驗結果則進一步證明，所提出方法能改善實際 USV平台上的 leader–follower 編隊追蹤性能。結果顯示，所提出之方法能有效降低通訊延遲對編隊控制之影響，並維持穩定之編隊追蹤性能。

This study investigates the leader–follower formation control problem of unmanned surface vehicles (USVs) under communication delay. Communication delay prevents the follower from accessing real-time leader posture information, which degrades tracking performance and may destabilize the formation system. To address this issue, a predictor-based formation control method is proposed, in which the current leader posture is reconstructed from delayed measurements and transmitted input history, while the nominal nonlinear formation tracking controller is preserved. In the delay-free case, Lyapunov methods are employed to establish that the cascaded leader–follower formation error system is uniformly globally asymptotically stable (UGAS). When communication delay is present, the predictor is shown to reconstruct the current leader posture exactly under the assumed conditions, rendering the predictor-compensated delayed system equivalent to the nominal delay-free system. Based on this equivalence and cascade stability theory, the overall predictor-compensated leader–follower formation system is shown to be UGAS. Finally, simulations and field experiments are conducted to validate the proposed method under different communication-delay conditions. The simulation results verify the effectiveness of the predictor-based compensation, while the field experiments further demonstrate that the proposed method can improve leader–follower formation tracking performance on real USV platforms. The results show that the proposed approach effectively mitigates the adverse effects of communication delay and maintains stable formation tracking performance.