This article investigates the fault detection and fault-tolerant control problem for an unmanned surface vehicle exposed to wave-induced disturbances and actuator faults in the physical layer, and delays and deception attacks in the cyber layer. First, a comprehensive vehicle model that includes physical disturbances, faults, time-varying delays, and Bernoulli random variable–based deception attacks is established. Second, an integrated fault detection filter and fault-tolerant controller design are developed to simultaneously provide a high degree of sensitivity to actuator faults and robustness and stability against cyber-physical threats (disturbances, faults, delays, and attacks). Delays and deception attacks are assumed to occur on the channel from fault detection filter to fault-tolerant controller. Finally, the performance and advantages of the integrated fault detection filter and fault-tolerant controller method with the solvability of inequality matrices are evaluated via comparative simulations in the unmanned surface vehicle with both low and high forward speeds.
LiuZXZhangYMYuX, et al. Unmanned surface vehicles: an overview of developments and challenges. Annu Rev Control2016; 41: 71–93.
2.
RumsonAG. The application of fully unmanned robotic systems for inspection of subsea pipelines. Ocean Eng2021; 235: 109214–109233.
3.
OuelmokhtarHBenmoussaYBenazzouzD, et al. Energy-based USV maritime monitoring using multi-objective evolutionary algorithms. Ocean Eng2022; 253: 111182–111195.
4.
KragelundSWaltonCKaminerI, et al. Generalized optimal control for autonomous mine countermeasures missions. IEEE J Oceanic Eng2021; 46(2): 466–496.
5.
ShanWJHuiLRWenLJ, et al. Cooperative unmanned surface vehicles and unmanned aerial vehicles platform as a tool for coastal monitoring activities. Ocean Coast Manage2023; 232: 106421.
6.
ZhangGYuWLiJ, et al. Model-based event-triggered adaptive formation control for underactuated surface vehicles via the minimal learning parameter technique. Proc IMechE, Part I: J Systems and Control Engineering2021; 236(3): 592–606.
7.
LiuZXZhangYMYuanC, et al. Adaptive path following control of unmanned surface vehicles considering environmental disturbances and system constraints. IEEE T Syst Man Cy: S2021; 51(1): 339–353.
8.
ZhaoZWangX. Event-triggered sliding mode trajectory tracking control for underactuated unmanned surface vessel. Proc IMechE, Part I: J Systems and Control Engineering2022; 237: 1087–1098.
9.
LiuCHuQZWangXG, et al. Event-triggered-based nonlinear model predictive control for trajectory tracking of underactuated ship with multi-obstacle avoidance. Ocean Eng2022; 253: 111278–111287.
10.
WangYLHanQL. Network-based fault detection filter and controller coordinated design for unmanned surface vehicles in network environments. IEEE T Ind Inform2016; 12(5): 1753–1765.
11.
NingZYuJWangT. Event-triggered fault detection filter design for uncertain stochastic systems with package dropouts. Proc IMechE, Part I: J Systems and Control Engineering2019; 233: 1351–1360.
12.
WangXDFeiZYYuJY, et al. Adaptive memory-based event-triggered fault detection for networked stochastic systems. IEEE T Circuits II2023; 70(1): 201–205.
13.
ZhangQYanHCWangM, et al. Asynchronous fault detection filter design for T–S fuzzy singular systems via dynamic event-triggered scheme. IEEE T Fuzzy Syst2023; 31(3): 970–981.
14.
MahalingamPKalpanaDSendhilkumarS, et al. Prefatory data analysis approach to synthetically generated pneumatic actuator data set. Proc IMechE, Part I: J Systems and Control Engineering2022; 236: 1807–1818.
15.
QianMLiYFHanT. Positive-unlabeled learning-based hybrid deep network for intelligent fault detection. IEEE T Ind Inform2022; 18(7): 4510–4519.
16.
AbbaspourAYenKKForouzannezhadP, et al. A neural adaptive approach for active fault-tolerant control design in UAV. IEEE T Syst Man Cy: S2020; 50(9): 3401–3411.
17.
AzmiHYazdizadehA. Adaptive delay dependent sliding mode fault-tolerant controller design for nonlinear systems with unknown time-varying input and state delays. Eur J Control2022; 69: 100756–100771.
18.
ZhouXHuangJQLuF, et al. A novel compound fault-tolerant method based on online sequential extreme learning machine with cycle reservoir for turbofan engine direct thrust control. Aerosp Sci Technol2022; 132: 108059–108071.
19.
ZhangCLGuoG. Extended prescribed performance fault-tolerant control of autonomous surface vessels using event-triggered inputs. Nonlinear Dynam2023; 111: 1315–1327.
20.
DuanDLiuCDaiJ, et al. Neural network–based optimal fault compensation control of the nonlinear multi-agent system and its application to UAVs formation flight. Proc IMechE, Part I: J Systems and Control Engineering2023; 237: 1635–1644.
21.
YangHYinSKaynakO. Neural network-based adaptive fault-tolerant control for Markovian jump systems with nonlinearity and actuator faults. IEEE T Syst Man Cy: S2021; 51(6): 3687–3698.
22.
WanLCaoYSunYC, et al. Fault-tolerant trajectory tracking control for unmanned surface vehicle with actuator faults based on a fast fixed-time system. ISA T2022; 130: 79–91.
23.
WangXDFeiZYGaoHJ, et al. Integral-based event-triggered fault detection filter design for unmanned surface vehicles. IEEE T Ind Inform2019; 15(10): 5626–5636.
24.
ZhangLNanHJZhaoZQ, et al. Adaptive disturbance observer-based dual-loop integral-type fast terminal sliding mode control for micro spacecraft and its gimbal tracking device. ISA T2022; 130: 121–135.
25.
LiLLLuoHDingSX, et al. Performance-based fault detection and fault-tolerant control for automatic control systems. Automatica2019; 99: 308–316.
26.
WangXHTanCP. Output feedback active fault tolerant control for a 3-DOF laboratory helicopter with sensor fault. IEEE T Autom Sci Eng. Epub ahead of print 26April2023. DOI: 10.1109/TASE.2023.3267132.
27.
WangXHWangYQZhangZY, et al. Sensor fault tolerant control for a 3-DOF helicopter considering detectability loss. IEEE T Circuits I2023; 70(10): 4112–4125.
28.
MaYJJiangBWangJ, et al. Adaptive fault-tolerant formation control for heterogeneous UAVs-UGVs systems with multiple actuator faults. IEEE T Aero Elec Sys2023; 59(5): 6705–6716.
29.
DaiSFZhaLJLiuJL, et al. Fault detection filter design for networked systems with cyber attacks. Appl Math Comput2022; 412: 126593–126606.
30.
YeZHZhangDWuZG. Adaptive event-based tracking control of unmanned marine vehicle systems with DoS attack. J Frankl Inst2021; 358(3): 1915–1939.
31.
ShiQFengMYLiXY, et al. A secure distributed information sharing algorithm based on attack detection in multi-task networks. IEEE T Circuits I2020; 67: 5125–5138.
32.
YadereliEGemciCAktaşAZ. A study on cyber-security of autonomous and unmanned vehicles. J Def Model Simul Appl Method Technol2015; 12: 369–381.
33.
FeiZYWangXDWangZH. Event-based fault detection for unmanned surface vehicles subject to denial-of-service attacks. IEEE T Syst Man Cy: S2022; 52(5): 3326–3336.
34.
MaYNieZQHuSL, et al. Fault detection filter and controller co-design for unmanned surface vehicles under DoS attacks. IEEE T Intell Transp2021; 22(3): 1422–1434.
35.
NematiAPeimaniMMobayenS, et al. Adaptive non-singular finite time control of nonlinear disturbed cyber-physical systems with actuator cyber-attacks and time-varying delays. Inform Sciences2022; 612: 1111–1126.
36.
WangDJChenFMengB, et al. Event-based secure H∞ load frequency control for delayed power systems subject to deception attacks. Appl Math Comput2021; 394: 125788–125800.
