Research Progress and Prospect of Rotor Flying Manipulator

Li, Sheng Zhi; Wang, Qing Tao; Di, Bao Jun

doi:10.1109/icrca55033.2022.9828937

Cited by 1 publication

(1 citation statement)

References 37 publications

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“…Zhong et al (2021) proposed a fuzzy adaptive PID terminal sliding mode controller, which utilized the advantages of PID and a terminal sliding mode control to improve the convergence speed of the control algorithm and reduce steady-state errors. Li and Wang (2022) constructed the structure model of the industrial manipulator control system. The Kalman filter method was used to identify the structural parameters of the manipulator, and the fuzzy PID stabilizing controller was used to optimize the configuration of the automatic control parameters of the manipulator to improve the adaptive control performance.…”

Section: Introductionmentioning

confidence: 99%

Manipulator Control Based on Adaptive RBF Network Approximation

Xin-di

2023

International Journal of Information Technologies and Systems Approach

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With the popularization of intelligent manufacturing, manipulator has found ever wider application in various industries. A manipulator requires a real-time and fast control algorithm in order to improve the accuracy in all kinds of precise operations. This paper proposes an algorithm based on adaptive radial basis function (RBF) for approximating the parameters of the manipulator, and the adaptive equations are designed to automatically adjust the weight of RBF. Proportional integral (PI) robust based on dynamic error tracking is used in controller to reduce the steady state errors and enhance the anti-interference performance of the system. The global asymptotic stability of the system is demonstrated by defining an integraltype Lyapunov function. Finally, MATLAB is used to simulate the angular positions tracking and angular velocities tracking of the double joints manipulator. The results show that the manipulator can track the ideal output signal quickly and accurately and has good anti-interference performance.

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Section: Introductionmentioning

confidence: 99%

Manipulator Control Based on Adaptive RBF Network Approximation

Xin-di

2023

International Journal of Information Technologies and Systems Approach

View full text Add to dashboard Cite

show abstract

Research Progress and Prospect of Rotor Flying Manipulator

Cited by 1 publication

References 37 publications

Manipulator Control Based on Adaptive RBF Network Approximation

Manipulator Control Based on Adaptive RBF Network Approximation

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