Aiming at the requirements of lightweight, low energy consumption and low inertia of the manipulators for autonomous underwater vehicles, this article presents a novel underwater cable-driven manipulator for autonomous underwater vehicles. Thanks to the cable-driven mechanism, the motors are installed remotely from joints, which can reduce the disturbance of the motion of the manipulator to the system and extend the operation time under the premise of limited energy. Cable–sheath mechanism is used to realize the motors to be fixedly mounted on the base (postposition). A prototype named Polaris-II is assembled, and experiments are carried out with the time-delay control scheme. Although the control effect of a single time-delay controller is good, there exist large errors caused by the reversing of joints. Therefore, a fuzzy compensator is designed and added to the time-delay controller to suppress the large errors. The experimental results show that the time-delay controller with a fuzzy compensator has a good inhibitory effect on the large errors while maintaining good control effect.
ShenX. Study on key technique for coordinated manipulation for dual manipulators in simulated deepwater environment. PhD Thesis, Huazhong University of Science and Technology, Wuhan, China, 2013.
2.
KondoHUraT. Navigation of an AUV for investigation of underwater structures. Control Eng Pract2004; 12(12): 1551–1559.
3.
BogueR. Underwater robots: a review of technologies and applications. Ind Robot2009; 36(3): 6–12.
4.
RibasDRidaoPTurettaA, et al. I-AUV mechatronics integration for the TRIDENT FP7 project. IEEE/ASME T Mech2015; 20(5): 2583–2592.
5.
RidaoPCarrerasMRibasD, et al. Intervention AUVs: the next challenge. Annu Rev Control2015; 40: 227–241.
6.
FernándezJJPratsMSanzPJ, et al. Grasping for the seabed: developing a new underwater robot arm for shallow-water intervention. IEEE Robot Autom Mag2013; 20(4): 121–130.
7.
HanJChungWK. Active use of restoring moments for motion control of an underwater vehicle-manipulator system. IEEE J Oceanic Eng2014; 39(1): 100–109.
8.
SarkarNPodderTK. Coordinated motion planning and control of autonomous underwater vehicle-manipulator systems subject to drag optimization. IEEE J Oceanic Eng2001; 26(2): 228–239.
9.
WangY. Research on coordinated control of autonomous underwater vehicle-manipulator systems. PhD Thesis, Zhejiang University, Hangzhou, China, 2016.
10.
ZhangNShangWCongS. Geometry-based trajectory planning of a 3-3 cable-suspended parallel robot. IEEE T Robot2017; 33(2): 484–491.
11.
WangYChenJYanF, et al. Adaptive super-twisting fractional-order nonsingular terminal sliding mode control of cable-driven manipulators. ISA T2019; 86: 163–180.
12.
LeeJKChoiCHYoonKH, et al. Design and evaluation of cable-driven manipulator with motion-decoupled joints. In: Proceedings of the international conference on smart manufacturing application, Gyeonggi-do, South Korea, 9–11 April 2008, pp.575–580. New York: IEEE.
13.
WangYLiBYanF, et al. Practical adaptive fractional-order nonsingular terminal sliding mode control for a cable-driven manipulator. Int J Robust Nonlin2019; 29(5): 1396–1417.
14.
RooksB. The harmonious robot. Ind Robot2006; 33(2): 125–130.
15.
ShangWZhangBZhangB, et al. Synchronization control in the cable space for cable-driven parallel robots. IEEE T Ind Electron2019; 66(6): 4544–4554.
16.
SoekadarSRWitkowskiMGómezC, et al. Hybrid EEG/EOG-based brain/neural hand exoskeleton restores fully independent daily living activities after quadriplegia. Sci Robot2016; 1(1). DOI: 10.1126/scirobotics.aag3296.
17.
CuiXChenWJinX, et al. Design of a 7-DOF cable-driven arm exoskeleton (CAREX-7) and a controller for dexterous motion training or assistance. IEEE/ASME T Mech2016; 22(1): 161–172.
18.
RusDTolleyMT. Design, fabrication and control of soft robots. Nature2015; 521(7553): 467–475.
19.
LucaADSicilianoBZolloL. PD control with on-line gravity compensation for robots with elastic joints: theory and experiments. Automatica2005; 41(10): 1809–1819.
20.
ReineckeJChalonMFriedlW, et al. Guiding effects and friction modeling for tendon driven systems. In: Proceedings of the IEEE international conference on robotics & automation, Hong Kong, China, 31 May–7 June 2014, pp.6726–6732. New York: IEEE.
21.
LensTKirchhoffJvon StrykO. Dynamic modeling of elastic tendon actuators with tendon slackening. In: Proceedings of the IEEE-RAS international conference on humanoid robots, Osaka, Japan, 29 November–1 December 2012, pp.779–784. New York: IEEE.
22.
SongYEKimCYLeeMC. Sliding mode control with sliding perturbation observer for surgical robots. In: Proceedings of the IEEE international conference on automation science & engineering, Seoul, South Korea, 5–8 July 2009, pp.2153–2158. New York: IEEE.
23.
BabaghasabhaRKhosraviMATaghiradHD. Adaptive robust control of fully constrained cable robots: singular perturbation approach. Nonlinear Dynam2016; 85(1): 607–620.
24.
ChatterjeeAChatterjeeRMatsunoF, et al. Augmented stable fuzzy control for flexible robotic arm using LMI approach and neuro-fuzzy state space modeling. IEEE T Ind Electron2008; 55(3): 1256–1270.
25.
WangYYanFChenJ, et al. A new adaptive time-delay control scheme for cable-driven manipulators. IEEE T Ind Inform. Epub ahead of print 17 October 2019. DOI: 10.1109/TII.2018.2876605.
26.
Youcef-ToumiKItoO. A time delay controller for systems with unknown dynamics. In: Proceedings of the 1988 American control conference, Atlanta, GA, 15–17 June 2009. New York: IEEE.
27.
WangYChenBWuH. Joint space tracking control of underwater vehicle-manipulator systems using continuous nonsingular fast terminal sliding mode. Proc IMechE, Part M: J Engineering for the Maritime Environment2018; 232(4): 448–458.
28.
DengWYaoJMaD. Robust adaptive precision motion control of hydraulic actuators with valve dead-zone compensation. ISA T2017; 70: 269–278.
29.
ChenZYaoBWangQ. Accurate motion control of linear motors with adaptive robust compensation of nonlinear electromagnetic field effect. IEEE/ASME T Mech2013; 18(3): 1122–1129.
30.
ChenZYaoBWangQ. μ-Synthesis-based adaptive robust control of linear motor driven stages with high-frequency dynamics: a case study with comparative experiments. IEEE/ASME T Mech2015; 20(3): 1482–1490.
31.
JinMKangSChangP. Robust compliant motion control of robot with nonlinear friction using time-delay estimation. IEEE T Ind Electron2008; 55(1): 258–269.
32.
JinMLeeJAhnK. Continuous non-singular terminal sliding-mode control of shape memory alloy actuators using time delay estimation. IEEE/ASME T Mech2015; 20(2): 899–909.
33.
JinMLeeJTsagarakisN. Model-free robust adaptive control of humanoid robots with flexible joints. IEEE T Ind Electron2017; 64(2): 1706–1715.
34.
JinMLeeJChangP, et al. Robust control of robot manipulators using inclusive and enhanced time delay control. IEEE/ASME T Mech2017; 22(5): 2141–2152.
35.
WangYJiangSChenB, et al. A new continuous fractional-order nonsingular terminal sliding mode control for cable-driven manipulators. Adv Eng Softw2018; 119: 21–29.
36.
WangYYanFJiangS, et al. Time delay control of cable-driven manipulators with adaptive fractional-order nonsingular terminal sliding mode. Adv Eng Softw2018; 121: 13–25.
37.
WangYChenBWuH. Practical continuous fractional-order nonsingular terminal sliding mode control of underwater hydraulic manipulators with valve deadband compensators. Proc IMechE, Part M: J Engineering for the Maritime Environment2018; 232(4): 459–469.
38.
WangYYanFZhuK, et al. A new practical robust control of cable-driven manipulators using time-delay estimation. Int J Robust Nonlin. Epub ahead of print 16 April 2019. DOI: 10.1002/rnc.4566.
39.
AhemSWangHTianY. Model-free control using time delay estimation and fractional-order nonsingular fast terminal sliding mode for uncertain lower-limb exoskeleton. J Vib Control2018; 24(22): 5273–5290.
40.
AhemSWangHTianY. Robust adaptive fractional-order terminal sliding mode control for lower-limb exoskeleton. Asian J Control2019; 21(1): 473–482.
41.
KaliYSaadMBenjellounK, et al. Super-twisting algorithm with time delay estimation for uncertain robot manipulators. Nonlinear Dynam2018; 93(2): 557–569.
42.
KaliYSaadMBenjellounK. Optimal super-twisting algorithm with time delay estimation for robot manipulators based on feedback linearization. Robot Auton Syst2018; 108: 87–99.
43.
ChoYMuhammadSCheongJ. Kinematic analysis of tendon driven robot mechanism for heavy weight handling. In: Proceedings of the international conference on ubiquitous robots & ambient intelligence, Goyang, South Korea, 28–30 October 2015, pp.91–94. New York: IEEE
44.
LensTKunzJVon StrykO, et al. BioRob-arm: a quickly deployable and intrinsically safe, light-weight robot arm for service robotics applications. In: Proceedings of the 41st international symposium on robotics (ISR 2010)/6th German conference on robotics (ROBOTIK 2010), Munich, 7–9 June 2010, pp.905–910. New York: IEEE.
45.
XuWWangYJiangS, et al. Kinematic analysis of a newly designed cable-driven manipulator. T Can Soc Mech Eng2018; 42(2): 125–135.
46.
ChenLWangXTianF. Tendon-sheath actuated robots and transmission system. In: Proceedings of the international conference on mechatronics & automation, Changchun, China, 9–12 August 2009, pp.3173–3178. New York: IEEE.
47.
ZhangGWangX. Design of automatic insertion system for a tendon-sheath-driven searching and rescuing robot. Appl Mech Mater2014; 532: 175–178.
48.
BeiraRSengulAHaraM, et al. Tendon-based transmission for surgical robotics: systematic experimental friction modeling. In: Proceedings of the international conference on applied bionics and biomechanics (ICABB-2010), Venice, 14–16 October 2010, https://infoscience.epfl.ch/record/161282/files/Paper.pdf
49.
LottiFTiezziPVassuraG, et al. Development of UB hand 3: early results. In: Proceedings of the 2005 IEEE international conference on robotics and automation, Barcelona, 18–22 April 2005, pp.4488–4493. New York: IEEE.
50.
JinMLeeJChangP, et al. Practical nonsingular terminal sliding-mode control of robot manipulators for high-accuracy tracking control. IEEE T Ind Electron2009; 56(9): 3593–3601.
51.
WangYGuLXuY, et al. Practical tracking control of robot manipulators with continuous fractional-order nonsingular terminal sliding mode. IEEE T Ind Electron2016; 63(10): 6194–6204.
52.
WangYZhuKYanF, et al. Adaptive super-twisting nonsingular fast terminal sliding mode control for cable-driven manipulators using time-delay estimation. Adv Eng Softw2019; 128: 113–124.
53.
LiuFCLiangLHGaoJJ. Fuzzy PID control of space manipulator for both ground alignment and space applications. Int J Autom Comput2014; 11(4): 353–360.
54.
KimJChangPJinM. Fuzzy PID controller design using time-delay estimation. T I Meas Control2017; 39(9): 1329–1338.
