Abstract
This paper is concerned with formation control of fully-actuated underwater vehicles (FUVs), focusing on improving system convergence speed and overcoming velocity measurement limitation. By employing the fixed-time control theory and command filtering technique, a full state feedback formation algorithm is proposed, which makes the follower track the leader in a given time with all signals in the system globally practically stabilized in fixed time. To avoid degraded control performance due to inaccurate velocity measurement, a fixed-time convergent observer is designed to estimate the velocity of FUVs. Then the authors give an observer-based fixed-time control method, with which acceptable formation performance can be achieved in fixed time without velocity measurement. The effectiveness and performance of the proposed method are demonstrated by numerical simulations.
Similar content being viewed by others
References
Cui R, Yang C, Li Y, et al., Adaptive neural network control of AUVs with control input nonlinearities using reinforcement learning, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2017, 47(6): 1019–1029.
Peng Z and Wang J, Output-feedback path-following control of autonomous underwater vehicles based on an extended state observer and projection neural networks, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018, 48(4): 535–544.
Li J, Du J, Sun Y, et al., Robust adaptive trajectory tracking control of underactuated autonomous underwater vehicles with prescribed performance, International Journal of Robust and Nonlinear Control, 2019, 29(14): 4629–4643.
Gao Z and Guo G, Fixed-time sliding mode formation control of AUVs based on a disturbance observer, IEEE/CAA Journal of Automatica Since, 2020, 7(2): 539–545.
Liu H, Lyu Y, Lewis F, et al., Robust time-varying formation control for multiple underwater vehicles subject to nonlinearities and uncertainties, International Journal of Robust and Nonlinear Control, 2019, 29(9): 2712–2724.
Shojaei K, Three-dimensional tracking control of autonomous underwater vehicles with limited torque and without velocity sensors, Robotica, 2018, 36(3): 374–394.
Shojaei K, Three-dimensional neural network tracking control of a moving target by underactuated autonomous underwater vehicles, Neural Computing and Applications, 2019, 31(2): 509–521.
Li J, Du J, and Chang W, Robust time-varying formation control for underactuated autonomous underwater vehicles with disturbances under input saturation, Ocean Engineering, 2019, 179: 180–188.
Cui R, Ge S S, How B, et al., Leader-follower formation control of underactuated autonomous underwater vehicles, Ocean Engineering, 2010, 37(17): 1491–1502.
Gao Z and Guo G, Adaptive formation control of autonomous underwater vehicles with model uncertainties, International Journal of Adaptive Control and Signal Processing, 2018, 32(7): 1067–1080.
Park B S, Adaptive formation control of underactuated autonomous underwater vehicles, Ocean Engineering, 2015, 96: 1–7.
Shojaei K, Neural network formation control of underactuated autonomous underwater vehicles with saturating actuators, Neurocomputing, 2016, 194: 372–384.
Jin X, Fault tolerant finite-time leader-follower formation control for autonomous surface vessels with LOS range and angle constraints, Automatica, 2016, 68: 228–236.
Du H, Zhu W, Wen G, et al., Finite-time formation control for a group of quadrotor aircraft, Aerospace Science and Technology, 2017, 69: 609–616.
Li S, Wang X, and Zhang L, Finite-time output feedback tracking control for autonomous underwater vehicles, IEEE Journal of Oceanic Engineering, 2015, 40(3): 727–751.
Defoort M, Polyakov A, Demesure G, et al., Leader-follower fixed-time consensus for multi-agent systems with unknown non-linear inherent dynamics, IET Control Theory and Applications, 2015, 9(14): 2165–2170.
Polyakov A, Nonlinear feedback design for fixed-time stabilization of linear control systems, IEEE Transactions on Automatic Control, 2012, 57(8): 2106–2110.
Tian B, Zuo Z, Yan X, et al., A fixed-time output feedback control scheme for double integrator systems, Automatica, 2017, 80: 17–24.
Zuo Z, Nonsingular fixed-time consensus tracking for second-order multi-agent networks, Automatica, 2015, 54: 305–309.
Zhang L J, Qi X, and Pang Y J, Adaptive output feedback control based on DRFNN for AUV, Ocean Engineering, 2009, 36(9–10): 716–722.
Gao Z and Guo G, Velocity free leader-follower formation control for autonomous underwater vehicles with line-of-sight range and angle constraints, Information Sciences, 2019, 486: 359–378.
Jiang B, Hu Q, and Friswell M I, Fixed-time attitude control for rigid spacecraft with actuator saturation and faults, IEEE Transactions on Control Systems Technology, 2016, 24(5): 1892–1898.
Zuo Z and Tie L, Distributed robust finite-time nonlinear consensus protocols for multi-agent systems, International Journal of Systems Science, 2016, 47(6): 1366–1375.
Farrell J A, Polycarpou M, and Sharma M, Command filtered backstepping, IEEE Transactions on Automatic Control, 2009, 54(6): 1391–1395.
Hu Z, Ma C, and Zhang L, Formation control of impulsive networked autonomous underwater vehicles under fixed and switching topologies, Neurocomputing, 2015, 147: 291–298.
Wondergem M, Lefeber E, Pettersen K Y, et al., Output feedback tracking of ships, IEEE Transactions on Control Systems Technology, 2011, 19(2): 442–448.
Bliek L, Verstraete H R, Verhaegen M, et al., Online optimization with costly and noisy measurements using random Fourier expansions, IEEE Transactions on Neural Networks and Learning Systems, 2018, 29(1): 167–182.
Gandomi A H, Yang X S, and Alavi A H, Cuckoo search algorithm: A metaheuristic approach to solve structural optimization problems, Engineering with Computers, 2013, 29(1): 17–35.
Sedghi F, Arefi M M, Abooee A, et al., Adaptive robust finite-time nonlinear control of a typical autonomous underwater vehicle with saturated inputs and uncertainties, IEEE/ASME Transactions on Mechatronics, 2021, 26(5): 2517–2527.
Gao Z and Guo G, Command filtered path tracking control of saturated ASVs based on time-varying disturbance observer, Asian Journal of Control, 2020, 22(3): 1197–1210.
Yu Y, Guo C, and Li T, Finite-time los path following of unmanned surface vessels with time-varying sideslip angles and input saturation, IEEE/ASME Transactions on Mechatronics, 2022, 27(1): 463–474.
Li S and Wang X, Finite-time consensus and collision avoidance control algorithms for multiple FUVs, Automatica, 2013, 49: 3359–3367.
Fossen T I and T Perez T, Marine systems simulator (MSS). URL: https://github.com/cyber-galactic/MSS, 2004.
Author information
Authors and Affiliations
Corresponding author
Additional information
This work was supported by the National Natural Science Foundation of China under Grant Nos. U1808205 and 62173079, the Natural Science Foundation of Hebei Province under Grant No. F2020501018, and the Youth Foundation of Hebei Educational Committee under Grant No. QN2020522.
Rights and permissions
About this article
Cite this article
Gao, Z., Zhang, Y. & Guo, G. Fixed-Time Leader-Following Formation Control of Fully-Actuated Underwater Vehicles Without Velocity Measurements. J Syst Sci Complex 35, 559–585 (2022). https://doi.org/10.1007/s11424-022-1502-0
Received:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11424-022-1502-0