Structural error and friction compensation control of a 2(3PUS + S) parallel manipulator

Shan, Xianlei

doi:10.1016/j.mechmachtheory.2018.02.004

Cited by 23 publications

(9 citation statements)

References 17 publications

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“…Based on the parameter identification experiments of the 2(3PUS+S) parallel manipulator, 24 the main friction coefficients are obtained, as shown in Table 2.…”

Section: Simulation and Experimentsmentioning

confidence: 99%

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Shan

2018

Proceedings of the Institution of Mechanical Engineers, Part K:

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Clearance, friction, and local elastic and plastic deformation of joint, which can be called joint effects, may cause nonlinear dynamic behaviour of mechanisms. In the paper, nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator was studied. There are 10 spherical joints in the 2(3PUS+S) parallel manipulator, and the dynamic characteristics of the spherical joints directly affect the overall output performance since they are connected to the moving platforms. Therefore, the joint effects of spherical joint and its effect are studied. To study the effect of the irregular clearance (size of the clearance varies with the attitude) of spherical joint due to manufacturing tolerance and wear, the spherical surface is approximated as an ellipsoid. In addition, the contact force models of spherical joint with variable contact stiffness were established under dry friction and lubrication condition, respectively. And then considering the contact forces of the spherical joints, the overall dynamic model of the 2(3PUS+S) parallel manipulator was established. Based on the overall dynamic model, the influence of joint effects on the dynamic characteristics of the 2(3PUS+S) parallel manipulator was studied, and the correctness of theoretical models was verified through experiments. The results from the simulation and experiments indicate that joint effects can cause nonlinear dynamic characteristics and have important influence on the dynamic performance of the 2(3PUS+S) parallel manipulator.

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“…Based on the parameter identification experiments of the 2(3PUS+S) parallel manipulator, 24 the main friction coefficients are obtained, as shown in Table 2.…”

Section: Simulation and Experimentsmentioning

confidence: 99%

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Shan

2018

Proceedings of the Institution of Mechanical Engineers, Part K:

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“…In terms of friction compensation, there are two types of schemes [23]: friction model-based and friction non-model-based schemes. The concluding methodology is employed when precise friction modeling is complicated or unnecessary, such as for variable structure control [24], PD control [25], and neural network control [26]. The model-based methodology [27] may be used if the friction parameter can be accurately identified to a certain degree.…”

Section: Introductionmentioning

confidence: 99%

Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation

et al. 2022

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In robotic manipulators, feedback control of nonlinear systems with fast finite-time convergence is desirable. However, because of the parametric and model uncertainties, the robust control and tuning of the robotic manipulators pose many challenges related to the trajectory tracking of the robotic system. This research proposes a state-of-the-art control algorithm, which is the combination of fast integral terminal sliding mode control (FIT-SMC), robust exact differentiator (RED) observer, and feedforward neural network (FFNN) based estimator. Firstly, the dynamic model of the robotic manipulator is established for the n degrees of freedom (DoFs) system by taking into account the dynamic LuGre friction model. Then, a FIT-SMC with friction compensation-based nonlinear control has been proposed for the robotic manipulator. In addition, a RED observer is developed to get the estimates of robotic manipulator joints' velocities. Since the dynamic friction state of the LuGre friction model is unmeasurable, FFNN is established for training and estimating the friction torque. The Lyapunov method is presented to demonstrate the finite-time sliding mode enforcement and state convergence for a robotic manipulator. The proposed control approach has been simulated in the MATLAB/Simulink environment and compared with the system with no observer to characterize the control performance. Simulation results obtained with the proposed control strategy affirm its effectiveness for a multi-DoF robotic system with model-based friction compensation having an overshoot and a settling time less than 1.5% and 0.2950 seconds, respectively, for all the joints of the robotic manipulator.INDEX TERMS robotic manipulator, robust exact differentiator, feedforward neural network, fast integral sliding mode control, LuGre friction model, autonomous articulated robotic educational platform.

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“…Besides, the PM consists of several kinematic branched-chains and various motion joints, the elastic deformation of the motion components, the clearance, friction, and contact deformation for the motion joints will affect the dynamic characteristics and motion accuracy of the robot [10,11]. A lot of studies have been carried out on the optimization of structure and control parameters [12,13], motion coupling control [14], disturbance suppression or compensation [15,16] for PMs. Dynamic modeling methods for PMs include Newton-Euler method, Lagrange method, virtual C The Author(s), 2021.…”

Section: Introductionmentioning

confidence: 99%

Rigid–flexible coupling dynamics analysis with joint clearance for a 5-DOF hybrid polishing robot

Guo

Wang

2021

Robotica

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SUMMARY Considering the polishing requirements for high-precision aspherical optical mirrors, a hybrid polishing robot composed of a serial–parallel manipulator and a dual rotor grinding system is proposed. Firstly, based on the kinematics of serial components, the equivalent load model for the parallel manipulator is established. Then, the elastodynamic model of kinematic branched-chains of the parallel manipulator is established by using the spatial beam element, and the rigid–flexible coupling dynamic model of the polishing robot is obtained with Kineto-elasto dynamics theory. Further, considering the dynamic properties of the joint clearance, the rigid–flexible coupling dynamic model with the joint clearance for the polishing robot is established. Finally, the equivalent load distribution of the parallel manipulator is analyzed, and the effect of the branched-chain elasticity and joint clearance on the motion error of the polishing robot is studied. This article provides a theoretical basis for improving the motion accuracy and dynamic performance of the hybrid polishing robot.

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Structural error and friction compensation control of a 2(3PUS + S) parallel manipulator

Cited by 23 publications

References 17 publications

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation

Rigid–flexible coupling dynamics analysis with joint clearance for a 5-DOF hybrid polishing robot

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Structural error and friction compensation control of a 2(3PUS + S) parallel manipulator

Cited by 23 publications

References 17 publications

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Nonlinear dynamic behaviour of joint effects on a 2(3PUS+S) parallel manipulator

Adaptive FIT-SMC Approach for an Anthropomorphic Manipulator With Robust Exact Differentiator and Neural Network-Based Friction Compensation

Rigid–flexible coupling dynamics analysis with joint clearance for a 5-DOF hybrid polishing robot

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Structural error and friction compensation control of a 2(3PUS + S) parallel manipulator