Design of novel sliding-mode controller for high-velocity AUV with consideration of residual dead load

Abstract

This work focuses on motion control of high-velocity autonomous underwater vehicle (AUV). Conventional methods are effective solutions to motion control of low-and-medium-velocity AUV. Usually not taken into consideration in the control model, the residual dead load and damping force which vary with the AUV’s velocity tend to result in difficulties in motion control or even failure in convergence in the case of high-velocity movement. With full consideration given to the influence of residual dead load and changing damping force upon AUV motion control, a novel sliding-mode controller (SMC) is proposed in this work. The stability analysis of the proposed controller is carried out on the basis of Lyapunov function. The sea trials results proved the superiority of the sliding-mode controller over sigmoid-function-based controller (SFC). The novel controller demonstrated its effectiveness by achieving admirable control results in the case of high-velocity movement.

Keywords

autonomous underwater vehicle / sliding-mode control / stability analysis / residual dead load / sigmoid-function-based control

References

[1] VuM T, ChioH S, KangJ, JiD H, JeongS K. A study on hovering motion of the underwater vehicle with umbilical cable [J]. Ocean Engineering, 2017, 135: 137-157

[2] PanY-he. Heading toward artificial intelligence 2.0 [J]. Engineering, 2016, 2: 409-413

[3] AlessandroM, GianlucaA. Experiments on Sampling/patrolling with two autonomous underwater vehicles [J]. International Journal of Naval Architecture and Ocean Engineering, 2016, 8(3): 243-251

[4] XiangX-b, LapierreL, JouvencelB. Smooth transition of AUV motion control: From fully-actuated to under-actuated configuration [J]. Robotics and Autonomous Systems, 2015, 67: 14-22

[5] JooM G, QuZ. An autonomous underwater vehicle as an underwater glider and its depth control [J]. International Journal of Control, Automation and Systems, 2015, 13(7): 1212-1220

[6] LiY, JiangY-q, WangL-f, CaoJ, ZhangG-cheng. Intelligent PID guidance control for AUV path tracking [J]. Journal of Central South University, 2015, 22: 3440-3449

[7] HosseinN E, VahidA, MohammadD. A time delay controller included terminal sliding mode and fuzzy gain tuning for underwater vehicle-manipulator systems [J]. Ocean Engineering., 2015, 107: 97-107

[8] IshaqueK, AbdullahS S, AyobS M, SalamZ. A simplified approach to design fuzzy logic controller for an underwater vehicle [J]. Ocean Engineering, 2011, 38: 271-284

[9] BagheriA, KarimiT, AmanifardN. Tracking performance control of a cable communicated underwater vehicle [J]. Applied Soft Computing, 2010, 10: 908-918

[10] HuZ-l, MaC, ZhangL-x, AarneH, TasawarH, BashirA. Formation control of impulsive networked autonomous underwater vehicles under fixed and switching topologies [J]. Neurocomputing, 2015, 147: 291-298

[11] KimD, ChoiH S, KimJ Y, ParkJ H, TranN H. Trajectory generation and sliding-mode controller design of an underwater vehicle-manipulator system with redundancy [J]. International Journal of Precision Engineering and Manufacturing, 2015, 16(7): 1561-1570

[12] Javadi-MoghaddamJ, BagheriA. An adaptive neuro-fuzzy sliding mode based genetic algorithm control system for under water remotely operated vehicle [J]. Expert Systems with Applications, 2010, 137: 647-660

[13] FangM-c, WangS-m, WuM-c, LinY-Hsien. Applying the self-tuning fuzzy control with the image detection technique on the obstacle-avoidance for autonomous underwater vehicles [J]. Ocean Engineering, 2015, 93: 11-24

[14] LiuX-m, XuY-ru. S control of automatic underwater vehicles [J]. Ocean Engineering, 2001, 19(3): 81-84

[15] SunY-s, WanL, GanY, JiangC-meng. Design of motion control of dam safety inspection underwater vehicle [J]. Journal of Central South University, 2012, 19(6): 1522-1529

[16] JiangC-m, WanL, SunY-shan. Design of motion control system of pipeline detection AUV [J]. Journal of Central South University, 2017, 24(3): 637-646

[17] TranN H, ChoiH S, BaeJ H, OhJ Y, ChoJ R. Design, control, and implementation of a new auv platform with a mass shifter mechanism [J]. International Journal of Precision Engineering and Manufacturing, 2015, 16(7): 1599-1608

[18] RezazadeganF, ShojaeK I. A novel approach to 6-DOF adaptive trajectory tracking control of an auv in the presence of parameter uncertainties [J]. Ocean Engineering, 2015, 107: 246-258

[19] HeB, WanL, JiangD-p, ZhangG-cheng. Fuzzy parameter self-optimized s-surface controller based on the prediction model [J]. Journal of Harbin Engineering University, 2014, 3: 267-273

[20] JianX-x, ChenL, ChangC-Hang. Tuning of fuzzy PI controllers based on gain/phase margin specifications and ITAE index [J]. ISA Transactions, 1996, 35(1): 79-91

[21] LiY, ZhangL, WanL, LiangXiao. Optimization of S-surface controller for autonomous underwater vehicle with immune-genetic algorithm [J]. Journal of Harbin Institute of Technology, 2008, 15(3): 404-410

[22] PetrichJ, StilwellD J. Robust control for an autonomous underwater vehicle that suppresses pitch and yaw coupling [J]. Ocean Engineering, 2011, 38: 197-204

[23] LiJ, GaoH, ZhangS-j, ChangS-a, ChenJ-x, LiuZ-hua. Self-localization of autonomous underwater vehicles with accurate sound travel time solution [J]. Computers & Electrical Engineering, 2016, 50: 26-38