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IJMERR 2022 Vol.11(2): 73-78

Sagging Cable Analysis and Evaluation of 4-degree-of- freedom Cable Robot Using Adaptive Neural Fuzzy Algorithm

Tuong Phuoc Tho and Nguyen Truong Thinh
Department of Mechatronics, Ho Chi Minh City University of Technology and Education, Thu Duc City, Ho Chi Minh City, Viet Nam

Abstract—One of the most important problems in robot modeling and control of cable robots is the problem of inverse kinematics, that is, using the coordinate data of the end effector to calculate the corresponding joint variables. Especially with regard to the kinematics of the cable robot, the sagging of the driven cable can have a significant effect on the calculation of the cable length, and this is more evident when the cable length is large, for example in construction or agriculture applications, where needs a large workspace. The determination of cable deflection considers modeling the cable as a chain model rather than calculating the cable length as a straight-line model. Furthermore, due to the structure and constraints of cable robots or Cable Driven Parallel robots (CDPRs), the system modeling and simulation becomes complicated, thereby increasing the computation time. In this paper, we propose an algorithm of Adaptive Neural Fuzzy Inference System (ANFIS) that is used to solve the cable sag problem for the 4-cable robots. This model was applied to estimate the cable sag for medium-sized cable robots with low travel speed and does not take into account the impact of cable elasticity. A simulation model was conducted and the results showed the advantages of this method in increasing the probability of convergence with small errors. The results of computation and experiment are analyzed to evaluate the effectiveness of the proposed model

Index Terms—Cable robots, forward kinematics, inverse kinematics, cable sagging, ANFIS

Cite: Tuong Phuoc Tho and Nguyen Truong Thinh, "Sagging Cable Analysis and Evaluation of 4-degree-of- freedom Cable Robot Using Adaptive Neural Fuzzy Algorithm," International Journal of Mechanical Engineering and Robotics Research, Vol. 11, No. 2, pp. 73-78, February 2022. DOI: 10.18178/ijmerr.11.2.73-78

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