In the extreme power environment of flexible transmission line, wind load, high voltage and strong electromagnetic interference, the motion performance of the robot manipulator is strongly affected by the extreme environment. Therefore, this study aims to improve the manipulator motion control performance of power cable maintenance robot and effectively reduce the influence of specific operation environment on the robot manipulator motion posture.
The mathematical model under three typical operation conditions, namely, flexible line, wind load and strong electromagnetic field have been established, correspondingly the mapping relationship between different environment parameters and robot operation conditions are also given. Based on the nonlinear approximation feature of neural network, a back propagation (BP) neural network is adopted to solve the posture control problems. The power cable line sag, robot tile angle caused by wind load and spatial field strength are the input signals of the BP network in the robot motion posture control method.
Through the training and learning of the BP network, the output control variables are used to compensate the actual robot operation posture. The simulation experiment verifies the effectiveness of the proposed algorithm, and compared with the conventional proportional integral differential (PID) control, the method has high real-time performance and sound stability. Finally, field operation experiments further validate the engineering feasibility of the control method, and at the same time, the proposed control method has the remarkable characteristics of sound universality, adaptability and easy expansion.
A multi-layer control architecture which is suitable for smart grid platform maintenance is proposed and a robot system platform for network operation and maintenance management is constructed. The human–machine–environment coordination and integration mode and intelligent power system management platform can be realized which greatly improves the intelligence of power system management. Mathematical models of the robot under three typical operation conditions of flexible wire wind load and strong electromagnetic field are established and the mapping relationship between different environmental parameters and the robot operation conditions is given. Through the non-linear approximation characteristics of BP network, the control variables of the robot joints can be obtained and the influence of extreme environment on the robot posture can be compensated. The simulation results of MATLAB show that the control algorithm can effectively restrain the influence of uncertain factors such as flexible environment, wind load and strong electromagnetic field on the robot posture. It satisfied the design requirements of fast response, high tracking accuracy and good stability of the control system. Field operation tests further verify the engineering practicability of the algorithm.
Funding: This work was supported by the Hubei Provincial Department of Education Research Project (B2019067) and Wuhan Textile University, Research Project Fund (National Project Cultivation Plan, 2019) and State Grid Hunan Electric Power Company Science and Technology Project.
Retraction notice: The publishers of Industrial Robot wish to retract the article “Motion posture control for power cable maintenance robot in typical operation conditions” by W. Jiang, M.H. Peng, Y. Yan, G. Wu, A. Zhang, L. Yu and H.J. Li which appeared in Volume 46, issue 5, 2019.
It has come to our attention that there are concerns that the peer review process may have been compromised, and that as a result, the findings may not be relied upon.
The authors of this paper would like to note that they do not agree with the content of this notice.
The publishers of the journal sincerely apologize to the readers.
Jiang, W., Peng, M.H., Yan, Y., Wu, G., Zhang, A., Yu, L. and Li, H.J. (2019), "Motion posture control for power cable maintenance robot in typical operation conditions", Industrial Robot, Vol. 46 No. 5, pp. 631-641. https://doi.org/10.1108/IR-01-2019-0015
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