Research on Position Control of Robotic Arm Based on Inversion Method
Main Article Content
Abstract
The research on robotic arm position control is not only a key component of the development of robot technology, but also an important force to promote the process of industrial automation and intelligence. The basic principle of the inversion control method is to transform the control problem of a nonlinear system into a control problem of a linear system by constructing the virtual control input of the system, thereby simplifying the design process of the controller. On this basis, a position control strategy based on inversion method was proposed for the mathematical model of the manipulator. The strategy fully considers the dynamic characteristics and nonlinear factors of the robotic arm, designs the corresponding controller, and proves the stability of the closed-loop system. The Simulnk platform in MATLAB software is used to design the controller based on the inversion method and simulate the analysis, and the results show that the robotic arm based on the inversion controller has a good improvement in tracking accuracy, response speed and anti-interference ability.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
Hu S ,Wan Y ,Liang X . Adaptive nonsingular fast terminal sliding mode trajectory tracking control for robotic manipulators with model feedforward compensation[J]. Nonlinear Dynamics,2025,(prepublish):1-19.
ZHANG Pingshe,HE Zhiwei. Research on motion control of multi-degree-of-freedom manipulator[J].Science and Technology Innovation and Productivity,2025,46(03):100-102.)
Zhang Y ,He L ,Chen J , et al. Neural Network Adaptive Hierarchical Sliding Mode Control for the Trajectory Tracking of a Tendon-Driven Manipulator[J]. Chinese Journal of Mechanical Engineering,2025,38(1):18-18.
Wang H ,Jiao X ,Wu S , et al. Model-Less Tracking Control for Continuum Manipulators Based on Fuzzy Adaptive Zeroing Neural Networks[J]. International Journal of Fuzzy Systems,2025,(prepublish):1-19.
Zhang W . Predefined-Time Fuzzy Control for Robotic Manipulators Driven by Compliant Actuators[J]. International Journal of Fuzzy Systems,2025,(prepublish):1-10.
Armenta M M ,Avelar A C ,Gandarilla I , et al. Solving trajectory tracking of robot manipulators via PID control with neural network compensation[J]. Soft Computing,2025,29(2):1-15.
Wang J ,Cui Y . Adaptive neural network tracking control for robotic manipulator with input dead zone and function constraints on states[J]. Nonlinear Dynamics,2025,(prepublish):1-19.
Yang Y ,Su Q ,Hui W , et al. Adaptive model-free finite-time tracking control for flexible-link manipulator with parametric and non-parametric uncertainties[J]. Nonlinear Dynamics,2025,(prepublish):1-17.
Zhao K ,Xie Y ,Xu S , et al. Adaptive neural appointed-time prescribed performance control for the manipulator system via barrier Lyapunov function[J]. Journal of the Franklin Institute,2025,362(2):107468-107468.
LI Xiyuan, LIN Chunqing, CHEN Hailei, et al. Abnormal vibration control at the end of manipulator arm based on PID parameter optimization[J].Machinery Manufacturing and Automation,2024,53(06):251-256.DOI:10.19344/j.cnki.issn1671-5276.2024.06.050.
Jiaqing F ,Lei Z ,Dongyu T . Integrated sliding mode control of robot manipulator based on fuzzy adaptive RBF[J]. Xibei Gongye Daxue Xuebao/Journal of Northwestern Polytechnical University,2024,42(6):1099-1110.
PANG Aimin,WANG Zhen,MA Shuangbao. Adaptive neural network inversion control of flexible manipulator[J].Mechanical Design and Manufacturing,2024,(06):309-314.DOI:10.19356/j.cnki.1001-3997.2024.06.008.
Sheikh M S ,Jafar M S ,S.M. S H , et al. Sliding-surface dynamic control of a continuum manipulator with large workspace[J]. Control Engineering Practice,2023,141
Tao X ,Youqun Z ,Fen L , et al. Backstepping sliding-mode control for active suspension system matching mechanical elastic wheel with uncertainties[J]. Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering,2022,236(12):2696-2710.
Yuhang L ,Lei Z ,Jiaxin Z , et al. Backstepping Adaptive Trajectory Tracking Control of Manipulator with Uncertainties of Model and State[J]. Journal of Physics: Conference Series,2022,2224(1):
Guiying L ,Shuyang W ,Zhigang Y . Adaptive nonlinear observer–based sliding mode control of robotic manipulator for handling an unknown payload[J]. Proceedings of the Institution of Mechanical Engineers,2021,235(3):302-312.
Hongyu C ,Xiucheng D ,Yong Y , et al. Backstepping Sliding Mode Control of Uncertainty Flexible Joint Manipulator with Actuator Saturation[J]. Journal of Physics: Conference Series,2021,1828(1):012165-.
HUANG Hua. Research on modeling and control of flexible joint manipulator[D].Hunan University of Technology,2014.