To solve the containment control problem of multi-unmanned surface vehicles (USVs) with input and output quantization communication, we propose a distributed containment method using sliding mode control (SMC) technology. First, with only the quantized value of position information being available, a super-twisting algorithm (STA)-based observer is used to recover the unmeasured velocities of the follower USVs in a finite time. Second, based on the STA-based observer, a distributed SMC strategy is developed to guide the follower USVs closely into the convex hull formed by the leader USVs under quantized communication. Furthermore, the stability analysis is given to guarantee that sliding variables and containment position errors can converge to specified ranges related to the quantization parameters and the parameters of the STA-based observer. Finally, simulation results demonstrate the feasibility of the designed SMC approach.
ChenCHanYZhuS, et al. (2023) Neural network-based fixed-time tracking and containment control of second-order heterogeneous nonlinear multiagent systems. IEEE Transactions on Neural Networks and Learning Systems35: 11565–11579.
2.
ChenWDingDGeX, et al. (2018) ℋ∞ containment control of multiagent systems under event-triggered communication scheduling: The finite-horizon case. IEEE Transactions on Cybernetics50(4): 1372–1382.
3.
DavilaJFridmanLLevantA (2005) Second-order sliding-mode observer for mechanical systems. IEEE Transactions on Automatic Control50(11): 1785–1789.
4.
DongZQiSYuM, et al. (2022) An improved dynamic surface sliding mode method for autonomous cooperative formation control of underactuated USVs with complex marine environment disturbances. Polish Maritime Research29(3): 47–60.
5.
DouWDingSYuX (2023) Event-triggered second-order sliding-mode control of uncertain nonlinear systems. IEEE Transactions on Systems, Man, and Cybernetics: Systems53: 7269–7279.
6.
FuJWanYWenG, et al. (2019) Distributed robust global containment control of second-order multiagent systems with input saturation. IEEE Transactions on Control of Network Systems6(4): 1426–1437.
7.
GuNWangDPengZ, et al. (2021) Model-free containment control of underactuated surface vessels under switching topologies based on guiding vector fields and data-driven neural predictors. IEEE Transactions on Cybernetics52(10): 10843–10854.
8.
HaoLYYuYLiTS, et al. (2021) Quantized output-feedback control for unmanned marine vehicles with thruster faults via sliding-mode technique. IEEE Transactions on Cybernetics52(9): 9363–9376.
9.
HeXWangQYuW (2014) Finite-time containment control for second-order multiagent systems under directed topology. IEEE Transactions on Circuits and Systems II: Express Briefs61(8): 619–623.
10.
HuQJiangBZhangY (2017) Observer-based output feedback attitude stabilization for spacecraft with finite-time convergence. IEEE Transactions on Control Systems Technology27(2): 781–789.
11.
JiangTYanYWuD, et al. (2022) Neural network based adaptive sliding mode tracking control of autonomous surface vehicles with input quantization and saturation. Ocean Engineering265: 112505.
12.
JiangYWangFYuH, et al. (2023) Adaptive prescribed-time containment control for multiple unmanned surface vehicles with uncertain dynamics and actuator dead-zones. Ocean Engineering289: 116269.
13.
KahveciNEIoannouPA (2013) Adaptive steering control for uncertain ship dynamics and stability analysis. Automatica49(3): 685–697.
14.
LevantA (1993) Sliding order and sliding accuracy in sliding mode control. International Journal of Control58(6): 1247–1263.
15.
LevantALivneM (2020) Robust exact filtering differentiators. European Journal of Control55: 33–44.
16.
LiDZhangWHeW, et al. (2018a) Two-layer distributed formation-containment control of multiple Euler–Lagrange systems by output feedback. IEEE Transactions on Cybernetics49(2): 675–687.
17.
LiJRenWXuS (2011) Distributed containment control with multiple dynamic leaders for double-integrator dynamics using only position measurements. IEEE Transactions on Automatic Control57(6): 1553–1559.
18.
LiTZhaoRChenCP, et al. (2018b) Finite-time formation control of under-actuated ships using nonlinear sliding mode control. IEEE Transactions on Cybernetics48(11): 3243–3253.
19.
LiZWuJZhanX, et al. (2022) Distributed adaptive predefined-time bipartite containment algorithm for nonlinear multi-agent systems with actuator faults. IEEE Transactions on Circuits and Systems II: Express Briefs70(6): 2141–2145.
20.
LiuZWHouHWangYW (2022) Formation-containment control of multiple underactuated surface vessels with sampling communication via hierarchical sliding mode approach. ISA Transactions124: 458–467.
21.
LuYLinYWangZ, et al. (2023) Output containment control for heterogeneous discrete-time linear descriptor multi-agent systems by a feedforward output regulation approach. Transactions of the Institute of Measurement and Control45(1): 3–16.
22.
LüHHeWHanQL, et al. (2020) Finite-time containment control for nonlinear multi-agent systems with external disturbances. Information Sciences512: 338–351.
23.
MaJLiuKTanC (2022) Finite-time robust containment control for autonomous surface vehicle with input saturation constraint. Ocean Engineering252: 111111.
24.
MaLChengCGuoJ, et al. (2023) Direct yaw-moment control of electric vehicles based on adaptive sliding mode. Mathematical Biosciences and Engineering20(7): 13334–13355.
25.
MorenoJAOsorioM (2012) Strict Lyapunov functions for the super-twisting algorithm. IEEE Transactions on Automatic Control57(4): 1035–1040.
26.
NingJLiTChenCP (2022) Neuro-adaptive distributed formation tracking control of under-actuated unmanned surface vehicles with input quantization. Ocean Engineering265: 112492.
27.
ParkBSYooSJ (2022) Quantized-communication-based neural network control for formation tracking of networked multiple unmanned surface vehicles without velocity information. Engineering Applications of Artificial Intelligence114: 105160.
28.
PengZWangJWangD (2016) Containment maneuvering of marine surface vehicles with multiple parameterized paths via spatial-temporal decoupling. IEEE/ASME Transactions on Mechatronics22(2): 1026–1036.
29.
QuYZhaoWYuZ, et al. (2022) Distributed prescribed performance containment control for unmanned surface vehicles based on disturbance observer. ISA Transactions125: 699–706.
30.
SkjetneRFossenTIKokotovićPV (2005) Adaptive maneuvering, with experiments, for a model ship in a marine control laboratory. Automatica41(2): 289–298.
31.
SongJZhengWXNiuY (2021) Self-triggered sliding mode control for networked PMSM speed regulation system: A PSO-optimized super-twisting algorithm. IEEE Transactions on Industrial Electronics69(1): 763–773.
32.
ThokerZALoneSA (2023) Super-twisting sliding mode control of a static synchronous compensator: An application in a wind–Diesel hybrid system. Transactions of the Institute of Measurement and Control45(15): 2955–2967.
33.
ThummalapetaMLiuYC (2023) Survey of containment control in multi-agent systems: Concepts, communication, dynamics, and controller design. International Journal of Systems Science54(14): 2809–2835.
34.
WangHTanHPengZ (2023a) Quantized communications in containment maneuvering for output constrained marine surface vehicles: Theory and experiment. IEEE Transactions on Industrial Electronics71(1): 880–889.
35.
WangLLiuXCaoJ, et al. (2021) Fixed-time containment control for nonlinear multi-agent systems with external disturbances. IEEE Transactions on Circuits and Systems II: Express Briefs69(2): 459–463.
36.
WangWTongS (2019) Adaptive fuzzy containment control of nonlinear strict-feedback systems with full state constraints. IEEE Transactions on Fuzzy Systems27(10): 2024–2038.
37.
WangXGuangWHuangT, et al. (2023b) Optimized adaptive finite-time consensus control for stochastic nonlinear multiagent systems with non-affine nonlinear faults. IEEE Transactions on Automation Science and Engineering. Epub ahead of print 23August. DOI: 10.1186 /1471-2288-7-30.
38.
WangXPangNXuY, et al. (2024) On state-constrained containment control for nonlinear multiagent systems using event-triggered input. IEEE Transactions on Systems, Man, and Cybernetics: Systems54: 2530–2538.
39.
WangYLHanQL (2018) Network-based modelling and dynamic output feedback control for unmanned marine vehicles in network environments. Automatica91: 43–53.
40.
XiaXXiaCSunC (2023) Distributed formation tracking control of underactuated surface vehicles based on event-triggered control. Transactions of the Institute of Measurement and Control46(4): 729–740.
41.
XiongXPalAKLiuZ, et al. (2020) Discrete-time adaptive super-twisting observer with predefined arbitrary convergence time. IEEE Transactions on Circuits and Systems II: Express Briefs68(6): 2057–2061.
42.
XuTDuanZSunZ, et al. (2022) A unified control method for consensus with various quantizers. Automatica136: 110090.
43.
YanYWangRYuS, et al. (2022) Event-triggered output feedback sliding mode control of mechanical systems. Nonlinear Dynamics107: 3543–3555.
44.
YanYYuS (2018) Sliding mode tracking control of autonomous underwater vehicles with the effect of quantization. Ocean Engineering151: 322–328.
45.
YanYYuSGaoX, et al. (2023) Continuous and periodic event-triggered sliding-mode control for path following of underactuated surface vehicles. IEEE Transactions on Cybernetics54(1): 449–461.
46.
YanYYuXSunC (2016) Quantization effect on sliding mode control of uncertain dynamical systems. Asian Journal of Control18(3): 1142–1146.
47.
YangPHuXWangZ, et al. (2022) Sliding mode fault tolerant consensus control for multi-agent systems based on super-twisting observer. Journal of Systems Engineering and Electronics33(6): 1309–1319.
48.
YangYXiaoYLiT (2021) A survey of autonomous underwater vehicle formation: Performance, formation control, and communication capability. IEEE Communications Surveys & Tutorials23(2): 815–841.
49.
YooSJParkBS (2017) Guaranteed performance design for distributed bounded containment control of networked uncertain underactuated surface vessels. Journal of the Franklin Institute354(3): 1584–1602.
50.
YooSJParkBS (2023) Approximation-free design for distributed formation tracking of networked uncertain underactuated surface vessels under fully quantized environment. Nonlinear Dynamics111(7): 6411–6430.
51.
YuXFengYManZ (2020) Terminal sliding mode control–an overview. IEEE Open Journal of the Industrial Electronics Society2: 36–52.
52.
YuZLiuZZhangY, et al. (2019) Distributed finite-time fault-tolerant containment control for multiple unmanned aerial vehicles. IEEE Transactions on Neural Networks and Learning Systems31(6): 2077–2091.
53.
ZhangHZhouYLiuY, et al. (2020) Cooperative bipartite containment control for multiagent systems based on adaptive distributed observer. IEEE Transactions on Cybernetics52(6): 5432–5440.
54.
ZhangTXuZLiJ, et al. (2019) A third-order super-twisting extended state observer for dynamic performance enhancement of sensorless IPMSM drives. IEEE Transactions on Industrial Electronics67(7): 5948–5958.
55.
ZhangZWenCXingL, et al. (2022) Adaptive output feedback control of nonlinear systems with mismatched uncertainties under input/output quantization. IEEE Transactions on Automatic Control67(9): 4801–4808.
56.
ZhaoZZhangJLiuZ, et al. (2023) Adaptive quantized fault-tolerant control of a 2-DOF helicopter system with actuator fault and unknown dead zone. Automatica148: 110792.
57.
ZhouJWenCWangW, et al. (2019) Adaptive backstepping control of nonlinear uncertain systems with quantized states. IEEE Transactions on Automatic Control64(11): 4756–4763.
