Adaptive Neural Output Feedback Control for USVs Under False-data-injection Attacks
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摘要: 本文主要研究網絡環境下無人水面船舶 (Unmanned surface vessels, USVs) 遭受虛假數據注入式 (False-data-injection, FDI) 攻擊的跟蹤控制問題. 其中, 內部和外部不確定以及輸入飽和約束等實際因素均考慮在設計中. 在控制設計過程中, 為避免將船舶速度的攻擊信號引入閉環系統, 采用分類重構思想, 構造一種新的神經網絡 (Neural network, NN) 狀態觀測器, 同時重構船舶速度和攻擊信號. 進一步, 在backstepping 設計框架下, 利用重構的攻擊信號補償USVs 運動學通道因虛假數據注入式攻擊引起的非匹配不確定項. 在動力學設計通道中, 利用自適應神經技術和單參數學習法, 重構由內部和外部不確定組成的復合不確定部分, 進而提出自適應神經輸出反饋控制方案. 理論分析表明, 即便在FDI 攻擊、內外不確定以及執行器飽和約束的情況下, 所提控制方案能迫使USVs 跟蹤給定的參考軌跡. 同時, 仿真和比較結果闡明了所提控制方案的有效性和優越性.Abstract: This paper investigates the tracking control issue of unmanned surface vessels (USVs) under the attack of false-data-injection (FDI) in the network environment, and these actual factors such as internal and external uncertainties and input saturation constraints are also considered in the design. In the control design, to avoid FDI attack signals from the velocity channel being introduced into the closed-loop system, the idea of classification reconstruction is developed. Based on this idea, a novel neural network (NN) state observer is constructed to reconstruct vessels velocity and FDI attack signals. Furthermore, under the backstepping design framework, utilizing the reconstructed attack signals to compensate the mismatched uncertainties in USVs kinematic channel, which is caused by false-data-injection attacks. In the dynamic design channel, adaptive neural technology and single parameter learning method are used to reconstruct the lumped uncertain parts, which consist of internal and external uncertainties, and then the adaptive neural output feedback control scheme is proposed. The theoretical analysis shows that the proposed control scheme can make USVs track a given reference trajectory, even in the presence of FDI attacks, internal and external uncertainties, and actuator saturation constraints. At the same time, the simulation and comparison results illustrate the effectiveness and superiority of the proposed control scheme.
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圖 3 軌跡誤差${{\boldsymbol{S}}}_1$對比圖
Fig. 3 Comparison chart of trajecto errors ${{\boldsymbol{S}}}_1$
圖 4 控制輸入${\boldsymbol {\tau}}$對比圖
Fig. 4 Comparison chart of control imputs${\boldsymbol {\tau}}$
圖 5 參數估計值$\hat{{\boldsymbol{\vartheta}}}$
Fig. 5 Parameter estimate values$\hat{{\boldsymbol{\vartheta}}}$
圖 6 速度估計誤差$\tilde{{{\boldsymbol{v}}}}$對比
Fig. 6 Comparision of velocity estimation errors$\tilde{{{\boldsymbol{v}}}}$
圖 7 位置估計誤差$\tilde{{\boldsymbol{\eta}}}$對比
Fig. 7 Comparison of position estimation errors$\tilde{{\boldsymbol{\eta}}}$
圖 8 有無${\boldsymbol{\sigma}}$時${{\boldsymbol{S}}}_1$對比
Fig. 8 Comparison of${{\boldsymbol{S}}}_1$with or without${\boldsymbol{\sigma}}$
圖 9 有無${\boldsymbol{\sigma}}$時$\hat{{{\boldsymbol{v}}}}$對比
Fig. 9 Comparison of$\hat{{{\boldsymbol{v}}}}$with or without${\boldsymbol{\sigma}}$
表 1 設計參數及初始值
Table 1 Design parameters and initial states
指標 項式 數值 觀測器 $ k $ 12 $ k_1 $ 0.1 $ k_2 $ 210 $ k_w $ 0.1 $ k_o $ 6 $ {\boldsymbol{\kappa}}_o $ 10$ \times $diag{8, 8, 2} 控制律 $ {\boldsymbol {c}}_1 $ diag{1.3, 1.4, 5.0} $ {\boldsymbol {c}}_2 $ 5$ \times $diag{9, 8, 10} $\omega_f$ 30 $ {\boldsymbol{\Lambda}}_c $ diag{5, 5, 5} $ {\boldsymbol {k}}_c $ 0.1$ \times $diag{1, 1, 1} $ {\boldsymbol{\varsigma}} $ diag{0.01, 0.01, 0.01} 環境擾動 $ {\boldsymbol{\wp}} $ diag{?2, ?2, ?2} $ {\boldsymbol{\Upsilon}} $ 2$ \times [1.5, 1.5, 1]^{\rm T} $ 輸入飽和限制 $ {\boldsymbol{\kappa}} $ $ [0.9, 0.9, 0.9]^{\rm T} $ $ {\boldsymbol{\tau}}_{m} $ $ [10, 10, 5]^{\rm T} $ $ Q_o $ 0.3 $ {\boldsymbol {k}}_Q $ diag{3, 2, 1} $ {\boldsymbol {k}}_{w_\tau} $ diag{10, 10, 10} 初始值 $ {\boldsymbol{\eta}}(0) $ $ [-1, -1, 0.1]^{\rm T} $ $ \hat{{\boldsymbol{\eta}}}(0) $ $ [-1, -1, 0.1]^{\rm T} $ $ {\boldsymbol {v}}(0) $ [0, 0, 0]T $ {\boldsymbol {S}}(0) $ $ [0.02, 0.02, 0.01]^{\rm T} $ $ \hat{\boldsymbol W}_o(0) $ $ [0.1, 0.1, 0.2]^{\rm T} $ $ \hat{\boldsymbol W}_c(0) $ $ [0.1, 0.1, 0.2]^{\rm T} $ 
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表 2 不同攻擊下的控制性能對比
Table 2 Comparison of control performance under different attacks
指標 項式 未攻擊 1 倍攻擊 4 倍攻擊 8 倍攻擊 $\int_{0}^{t}\frac{\tau_i(t_f)}{t_f\;+\;0.001}{\rm d}t_f$ $ \tau_1 $ 1.524 1.522 1.535 1.605 $ \tau_2 $ 1.245 1.270 1.428 1.742 $ \tau_3 $ 0.476 0.477 0.484 0.495 $ \int_{0}^{t}|S_{1,i}|{\rm d}t_f $ $ S_{1,1} $ 3.334 3.263 3.097 2.986 $ S_{1,2} $ 3.333 3.302 3.235 3.191 $ S_{1,3} $ 0.412 0.412 0.413 0.412 $\int_{0}^{t}| \tilde{v}_i|{\rm d}t_f$ $ \tilde{v}_1 $ 0.072 0.758 3.052 6.108 $ \tilde{v}_2 $ 0.074 0.632 2.519 5.065 $ \tilde{v}_3 $ 0.008 0.018 0.093 0.193
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