A Review on Robust Control of Robot Manipulators for Future Manufacturing

Son, Jeongwoo; Kang, Hyunah; Kang, Sang Hoon

doi:10.1007/s12541-023-00812-9

Cited by 11 publications

(1 citation statement)

References 115 publications

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“…The realization of this method depends on the accurate robot dynamic model. However, the robot system is very complex with many uncertainties, including the error of dynamic parameters of links, unmodeled dynamics, joint friction errors, and other uncertainties in the system itself [11][12][13], as well as being affected by external uncertainties such as environmental disturbances [14] and variable loads on the end-effector [15]. Therefore, it is difficult to obtain a complete and accurate dynamic model of the robot, which restricts this model-based control method.…”

Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Chen,

Ding,

Chen

et al. 2024

Applied Sciences

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The introduction of a dynamic model in robot trajectory tracking control design can significantly improve its trajectory tracking accuracy, but there are many uncertainties in the robot dynamic model which can be dealt with through robust control and adaptive control. The prevailing robust control as well as adaptive control methods require real-time computation of robot dynamics, but the extreme complexity of the robot dynamics equations makes it difficult to apply these methods in real industrial systems. To this end, this article proposes a robust adaptive control method based on the desired trajectory, which uses the desired trajectory to compute most of the control terms offline, including the robot’s nominal dynamics and regression matrices, and substantially reduces the need for real-time computation of the feedback signals. The robust term modifies the perturbation of the inertial parameters of the links, the adaptive term learns the friction coefficients of the joints online, and an additional compensation term is designed to satisfy the Lyapunov stability condition of the system. Finally, taking a universal manipulator as the experimental platform, the control performances of different control methods are compared to show the feasibility of the controller and the effective reduction in real-time computational complexity.

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Section: Introductionmentioning

confidence: 99%

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Chen,

Ding,

Chen

et al. 2024

Applied Sciences

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Integrating Virtual Twin and Deep Neural Networks for Efficient and Energy-Aware Robotic Deburring in Industry 4.0

Rahul,

Chiddarwar

2023

Int. J. Precis. Eng. Manuf.

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Vibration-Damped Tool Holders in Industrial Robotic Machining Systems

Kim,

Noe,

Choi

et al. 2023

Int. J. Precis. Eng. Manuf.

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Since the introduction of automation systems has begun to be applied to most industries with the development of technology, the utilization of industrial robots is increasing every year. However, the processing field a such as milling and Rough Cutting processing process occurs vibration from large processing load. Since industrial robots basically have low stiffness, they are vulnerable to vibration generated from processing loads when processing. In this paper, multi-axis active spindle holder of high stiffness was developed to improve precision and quality deterioration due to vibration generated from a processing load. If an active spindle holder of high stiffness is applied, it can increase the dynamic stiffness of the robot by blocking vibrations in the low-frequency range at the end effector before they are transmitted from the spindle to the robot, and as a result, it is expected to improve precision and quality. The performance evaluation of the active spindle holder manufactured based on the design was proceeded, and it was verified that the active spindle holder developed to compensate for the shortcomings of industrial robots was made with moving range and high stiffness of 200 Hz more. Furthermore, machining experiments confirmed an improvement in quality of more than 10%.

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A Review on Robust Control of Robot Manipulators for Future Manufacturing

Cited by 11 publications

References 115 publications

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Nonlinear Robust Adaptive Control of Universal Manipulators Based on Desired Trajectory

Integrating Virtual Twin and Deep Neural Networks for Efficient and Energy-Aware Robotic Deburring in Industry 4.0

Vibration-Damped Tool Holders in Industrial Robotic Machining Systems

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