摘要
This paper presents a dynamic model and performance constraint control of a line-driven soft robotic arm.The dynamics model of the soft robotic arm is established by combining the screw theory and the Cosserat theory.The unmodeled dynamics of the system are considered,and an adaptive neural network controller is designed using the backstepping method and radial basis function neural network.The stability of the closed-loop system and the boundedness of the tracking error are verified using Lyapunov theory.The simulation results show that our approach is a good solution to the motion constraint problem of the line-driven soft robotic arm.
基金
supported by the National Natural Science Foundation of China(62103039,62073030)
the Scientific and Technological Innovation Foundation of Shunde Graduate School
University of Science and Technology Beijing(USTB)(BK21BF003)
the Korea Institute of Energy Technology Evaluation and Planning through the Auspices of the Ministry of Trade
Industry and Energy
Republic of Korea
(20213030020160)
the Science and Technology Planning Project of Guangzhou City(202102010398,202201010758)
the Guangzhou University-Hong Kong University of Science and Technology Joint Research Collaboration Fund(YH202205)
Beijing Top Discipline for Artificial Intelligent Science and Engineering
University of Science and Technology Beijing。
