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Design of Lower Limb Exoskeleton Control System Based on Chaotic Mapping PSO Algorithm
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Liu-yi LING1, 2, Yi-ming LIU2, *, Qi ZHANG1
Science Technology and Engineering | 2025, 25(14) : 5913 - 5923
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Science Technology and Engineering | 2025, 25(14): 5913-5923
Papers·Automation and Computational Technology
Design of Lower Limb Exoskeleton Control System Based on Chaotic Mapping PSO Algorithm
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Liu-yi LING1, 2, Yi-ming LIU2, *, Qi ZHANG1
Affiliations
  • 1. School of Electrical and Information Engineering, Anhui University of Technology, Huainan 232001, China
  • 2. School of Artificial Intelligence, Anhui University of Technology, Huainan 232001, China
Published: 2025-05-18 doi: 10.12404/j.issn.1671-1815.2404017
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A simplified lower-limb exoskeleton model was established for the prototype, and the D-H parameter method was used to perform dynamic analysis. Joint angles were measured experimentally and used as inputs for the controller. To address the robot's trajectory tracking problem, traditional PID control was employed, showing good tracking performance but slow response and parameter tuning speed. Although PSO(particle swarm optimization) accelerated the parameter tuning, issues with low convergence accuracy and local optimum traps persisted. Therefore, a PID control based on a chaotic-mapping improved PSO algorithm was designed. The results show that the randomness was enhanced, the parameter tuning speed was increased, and the tracking error was reduced. Simscape was used for visual simulation of joint angles, and the control performance was further validated through various experiments.

lower limb rehabilitation robot  /  improve particle swarm optimization  /  PID control  /  trajectory tracking  /  simulink simulation
Liu-yi LING, Yi-ming LIU, Qi ZHANG. Design of Lower Limb Exoskeleton Control System Based on Chaotic Mapping PSO Algorithm[J]. Science Technology and Engineering, 2025 , 25 (14) : 5913 -5923 . DOI: 10.12404/j.issn.1671-1815.2404017
Year 2025 volume 25 Issue 14
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Article Info
doi: 10.12404/j.issn.1671-1815.2404017
  • Receive Date:2024-05-30
  • Online Date:2025-07-09
  • Published:2025-05-18
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  • Received:2024-05-30
  • Revised:2025-02-14
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Affiliations
    1. School of Electrical and Information Engineering, Anhui University of Technology, Huainan 232001, China
    2. School of Artificial Intelligence, Anhui University of Technology, Huainan 232001, China
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表12种不同金属材料的力学参数

Family
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Number of
genus
种数
Number of
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占总种数比例
Percentage of
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种数
Number of
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鹅膏菌科Amanitaceae 2 11 5.26 鹅膏菌属 Amanita 10 4.78
小菇科 Mycenaceae 2 12 5.74 丝盖伞属 Inocybe 5 2.39
多孔菌科 Polyporaceae 8 14 6.70 蜡蘑属 Laccaria 5 2.39
红菇科 Russulaceae 3 23 11.00 小皮伞属 Marasmius 6 2.87
小菇属 Mycena 11 5.26
光柄菇属 Pluteus 5 2.39
红菇属 Russula 17 8.13
栓菌属 Trametes 5 2.39
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