A Method of Applying 81-Rule Fuzzy Control For Three-Linked Acrobot
Corressponding author's email:
hainvd@hcmute.edu.vnDOI:
https://doi.org/10.54644/jte.76.2023.1291Keywords:
Gymnastic robot, Genetic algorithm, Under-actuated system, Acrobot, Fuzzy controlAbstract
Acrobot, which is also called gymnastic robot, is a single input-multi output (SIMO) system which imitates motion of a barbell athlete. However, two links of this model are just equivalent to body and hand of athlete. To imitate better motion of athlete, three-linked acrobot- a complicated multi input-multi output (MIMO) under-actuated system – is developed. Parts of barbell athlete including leg, body and hand, are modelled well by this new system. In this paper, we present a method to apply an 81-rule fuzzy algorithm, which is popularly used for invert pendulum systems, to balance this model at upward equilibrium point. Instead of using a complicated 729-rule fuzzy controller which is set by knowledge of experts, we use more simple fuzzy structure. Through genetic algorithm (GA), the pre-processing and post-processing coefficients of fuzzy controller are chosen. With these suitable coefficients, our fuzzy controller is proved to work well through Matlab/Simulink simulation.
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References
S. Nemitha, B. Vijaya Bhaskar, and R. Kumar, “A Comparative Study of Inverted Pendulum,” in Proceedings of the International Conference on Soft Computing Systems, Advances in Intelligent Systems and Computing (Springer), pp. 593-602, 2016.
N. V. D. Hai, N. T. Van, and N. M. Tam, “Application of fuzzy and PID algorithm in gantry crane control,” Journal of Technical Education Science, no. 44A, pp. 48–53, 2017.
V. D. H. Nguyen et al., “Experimental Fuzzy Control for Tower Crane,” Journal of Science and Technology Education - Ho Chi Minh City University of Technology and Education, no. 68, pp. 36–47, 2022.
H. T. Hoang, "Smart Control System," (in Vietnamese), VNU-HCM Publishing House.
T. T. H. Le et al., “Fuzzy Controller for Rotary Inverted Pendulum,” Robotica & Management, vol. 23, no. 2, pp. 16-20, 2018.
R. Tedrake, “Underactuated Robotics: Algorithms for Walking, Running, Swimming, Flying, and Manipulation” (Course Notes for MIT 6.832).
H. C. Tran et al., “Genetic Algorithm Implementation for Optimizing Linear Quadratic Algorithm to Control Acrobot Robotic System,” Robotica & Management, vol. 23, no. 1, pp. 31-36, 2018.
V. D. H. Nguyen et al., “A Method of PD-Fuzzy Control for Acrobot,” International Journal of Robotica and Management, vol. 26, no. 2, pp. 28-34, Dec. 2021.
T. Henmi et al., “Motion Control of Underactuated Linkage Robot based on Gymnastic Skill,” Electr Eng Jpn, Wiley, pp. 1–9, 2018.
D. H. Lee et al., “Dynamics analysis and experiment of a 3-link gymnastic robot,” in 3rd International Conference on Control, Automation and Robotics (ICCAR), pp. 174-179, 2017.
N. T. M. Nguyet et al., “Survey and compare sliding PD and LQR control for three-link acrobot system,” (in Vietnamese), Scientific magazine of Tien Giang University, no. 12, pp. 50-59, 2022.
D. T. Giang et al., “LQR control for three-step Acrobot system,” (in Vietnamese), Scientific magazine of Tien Giang University, no. 11, pp. 22-29, 2021.
S. Celikovsky et al., “Embedding the generalized Acrobot into the n-link with a cyclic variable and its application to walking design,” in European Control Conference (ECC), pp. 682-689, 2013.
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