Research of Advanced Control Algorithms for Robotic Manipulators in Precision Manufacturing

Authors

  • Qi Zhang School of Construction Machinery, Chang'an University, Xi'an, Shaanxi, China

DOI:

https://doi.org/10.54097/y39dcq02

Keywords:

Precision Manufacturing; Robotic Manipulator; Advanced Control Algorithm; Adaptive Control; PID Control.

Abstract

In the global trend of transformation towards intelligent and precision manufacturing, robotic manipulators, as core equipment for flexible production, high-precision assembly, and complex process machining in the field of precision manufacturing, their control performance is crucial. However, traditional control algorithms struggle to maintain stable high-precision control effects when facing parameter variations, external disturbances, and complex constraints, becoming a key bottleneck restricting technological breakthroughs. This paper focuses on the development of advanced control algorithms for robotic manipulators in precision manufacturing and proposes a hybrid control strategy integrating adaptive mechanisms and robust compensation, aiming to ensure trajectory tracking accuracy while enhancing the system's ability to suppress external disturbances. By improving the PID control algorithm with the introduction of friction compensation and designing an adaptive robust control algorithm based on the recursive least squares method and Lyapunov stability theory, the problems of parameter uncertainty and external disturbances are effectively solved. Experimental results show that robotic manipulators adopting the adaptive control algorithm exhibit higher control precision, faster response speed, and stronger robustness in complex precision assembly tasks and scenarios with environmental interference. This provides a new direction for high-precision control of robotic manipulators in the field of precision manufacturing and promotes the integration of control theory and advanced manufacturing technology.

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References

[1] Son J, Kang H, Kang S H. A review on robust control of robot manipulators for future manufacturing[J]. International Journal of Precision Engineering and Manufacturing, 2023, 24(6): 1083-1102.

[2] Tinoco V, Silva M F, Santos F N, et al. A review of advanced controller methodologies for robotic manipulators[J]. International Journal of Dynamics and Control, 2025, 13(1): 36.

[3] Rawat D, Gupta M K, Sharma A. Intelligent control of robotic manipulators: a comprehensive review[J]. Spatial Information Research, 2023, 31(3): 345-357.

[4] Mo K, Liu W, Shen F, et al. Precision kinematic path optimization for high-dof robotic manipulators utilizing advanced natural language processing models[C]//2024 5th International Conference on Electronic Communication and Artificial Intelligence (ICECAI). IEEE, 2024: 649-654.

[5] Han X, Wu K, Hui N. Co-Optimization of Vibration Suppression and Data Efficiency in Robotic Manipulator Dynamic Modeling[J]. Applied Sciences, 2025, 15(14): 7679.

[6] Luo D, Cai Z, Jiang D, et al. Research on Parameter Identification Method for Robotic Manipulators Joint Friction Model Based on PINN[C]//2024 IEEE International Conference on Advanced Intelligent Mechatronics (AIM). IEEE, 2024: 948-953.

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Published

19-01-2026

How to Cite

Zhang, Q. (2026). Research of Advanced Control Algorithms for Robotic Manipulators in Precision Manufacturing. Highlights in Science, Engineering and Technology, 160, 533-538. https://doi.org/10.54097/y39dcq02