Lightweight Delta robot is typical high-speed and high-precision industrial parallel robot. However, under high-speed condition, because of the lightweight components, it will inevitably lead to the vibration of Delta robot, which reduces the position accuracy and positioning efficiency. To solve this problem comprehensively, this article considers the process vibration and residual vibration of Delta robot, and the intelligent shaping vibration suppression control system is designed by using trajectory planning method of improved trapezoidal mode, shaping control method, and fast terminal sliding mode controller, and the detailed experimental analysis is carried out. The experimental results show that the proposed intelligent shaping vibration suppression control method can well suppress the process vibration and residual vibration of Delta robot, which can effectively improve the operation stability, work efficiency, and position accuracy of Delta robot.
AbdullahiAMMohamedZSelamatH, et al. (2018) Adaptive output-based command shaping for sway control of a 3D overhead crane with payload hoisting and wind disturbance. Mechanical Systems and Signal Processing98: 157–172.
2.
AdhikaryNMahantaC (2018) Sliding mode control of position commanded robot manipulators. Control Engineering Practice81: 183–198.
3.
AmerAFSallamEAElawadyWM (2011) Adaptive fuzzy sliding mode control using supervisory fuzzy control for 3 DOF planar robot manipulators. Applied Soft Computing11(8): 4943–4953.
4.
GasparettoAZanottoV (2008) A technique for time-jerk optimal planning of robot trajectories. Robotics and Computer-Integrated Manufacturing24(3): 415–426.
5.
GasparettoAZanottoV (2010) Optimal trajectory planning for industrial robots. Advances in Engineering Software41(4): 548–556.
6.
HerzigNMoreauRRedarceT, et al. (2018) Nonlinear position and stiffness Backstepping controller for a two Degrees of Freedom pneumatic robot. Control Engineering Practice73: 26–39.
7.
IzadbakhshA (2016) Robust control design for rigid-link flexible-joint electrically driven robot subjected to constraint: theory and experimental verification. Nonlinear Dynamics85(2): 751–765.
8.
KimJCroftEA (2018) Preshaping input trajectories of industrial robots for vibration suppression. Robotics and Computer-Integrated Manufacturing54: 35–44.
9.
KojimaHIedaSKasaiS (2014) Frequency-tuning input-shaped manifold-based switching control for underactuated space robot equipped with flexible appendages. Acta Astronautica101: 42–54.
10.
KorayemMHBamdadM (2009) Dynamic load-carrying capacity of cable-suspended parallel manipulators. The International Journal of Advanced Manufacturing Technology44(7): 829–840.
11.
KorayemMHBamdadMTourajizadehH, et al. (2012) Analytical design of optimal trajectory with dynamic load-carrying capacity for cable-suspended manipulator. The International Journal of Advanced Manufacturing Technology60(1): 317–327.
12.
KorayemMHIraniMNekooSR (2011) Load maximization of flexible joint mechanical manipulator using nonlinear optimal controller. Acta Astronautica69(7): 458–469.
13.
KorayemMHNekooSR (2015) Finite-time state-dependent Riccati equation for time-varying nonaffine systems: Rigid and flexible joint manipulator control. ISA Transactions54: 125–144.
14.
KorayemMHShafeiAM (2013) Application of recursive Gibbs-Appell formulation in deriving the equations of motion of N-viscoelastic robotic manipulators in 3D space using Timoshenko Beam Theory. Acta Astronautica83: 273–294.
15.
KorayemMHTourajizadehH (2011) Maximum DLCC of spatial cable robot for a predefined trajectory within the workspace using closed loop optimal control approach. Journal of Intelligent & Robotic Systems63(1): 75–99.
16.
LiWPLuoBHuangH (2016) Active vibration control of flexible joint manipulator using input shaping and adaptive parameter auto disturbance rejection controller. Journal of Sound and Vibration363: 97–125.
17.
MansouriIOualiM (2009) A new homogeneous manipulability measure of robot manipulators, based on power concept. Mechatronics19(6): 927–944.
18.
MansouriIOualiM (2011) The power manipulability - A new homogeneous performance index of robot manipulators. Robotics and Computer-Integrated Manufacturing27(2): 434–449.
19.
MohamedZTokhiMO (2004) Command shaping techniques for vibration control of a flexible robot manipulator. Mechatronics14(1): 69–90.
20.
NageshraoSPLopesGADJeltsemaD, et al. (2014) Passivity-based reinforcement learning control of a 2-DOF manipulator arm. Mechatronics24(8): 1001–1007.
21.
PereiraETraperoJRDíazIM, et al. (2012) Adaptive input shaping for single-link flexible manipulators using an algebraic identification. Control Engineering Practice20(2): 138–147.
22.
PiedrafitaRComínDBeltránJR (2018) Simulink implementation and industrial test of input shaping techniques. Control Engineering Practice79: 1–21.
23.
UtkinVI (2003) Variable structure systems with sliding modes. IEEE Transactions on Automatic Control22(2): 212–222.
24.
WuMMeiJZhaoY, et al. (2020) Vibration reduction of delta robot based on trajectory planning. Mechanism and Machine Theory153: 104004.
25.
YangXCuiJLaoD, et al. (2016) Input shaping enhanced active disturbance rejection control for a twin rotor multi-input multi-output system (TRMS). ISA Transactions62: 287–298.
26.
YoungKDUtkinVIOzgunerU (1999) A control engineer's guide to sliding mode control. IEEE Trans.control Syst.technol7(3): 328–342.
27.
ZargarbashiSHHKhanWAngelesJ (2012a) The Jacobian condition number as a dexterity index in 6R machining robots. Robotics and Computer-Integrated Manufacturing28(6): 694–699.
28.
ZargarbashiSHHKhanWAngelesJ (2012b) Posture optimization in robot-assisted machining operations. Mechanism and Machine Theory51(51): 74–86.
29.
ZeinaliMNotashL (2010) Adaptive sliding mode control with uncertainty estimator for robot manipulators. Mechanism and Machine Theory45(1): 80–90.
30.
ZhangYHuangRLouY, et al. (2012) Dynamics based time-optimal smooth motion planning for the delta robot. In: 2012 IEEE international conference on robotics and biomimetics (ROBIO), Guangzhou, China, 11–14 December. 2012, pp. 1789–1794. IEEE.
31.
ZhengKHuYWuB (2018) Model-free development of control systems for a multi-degree-of-freedom robot. Mechatronics53: 262–276.
32.
ZhengKHuYWuB (2019a) Trajectory planning of multi-degree-of-freedom robot with coupling effect. Journal of Mechanical Science and Technology33(1): 413–421.
33.
ZhengKHuYWuB, et al. (2019b) New trajectory control method for robot with flexible bar-groups based on workspace lattices. Robotics and Autonomous Systems111: 44–61.
34.
ZhengKHuYYuW (2020) A novel parallel recursive dynamics modeling method for robot with flexible bar-groups. Applied Mathematical Modelling77: 267–288.
35.
ZhengKZhangQ (2016) Comprehensive analysis of the position error and vibration characteristics of Delta robot. Advanced Robotics30(20): 1322–1340.
36.
ZhouTGuoHXuJ, et al. (2017) Adaptive robust control with input shaping technology for solar array drive system. Acta Astronautica140: 264–272.
