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Tracking control for flexible joint robots based on adaptive fuzzy compensation with uncertain parameters
Author(s) -
Huang Huayuan,
Pan Hongtao,
Cheng Yong
Publication year - 2021
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/acs.3276
Subject(s) - control theory (sociology) , robustness (evolution) , fuzzy logic , fuzzy control system , torque , adaptive control , lyapunov function , exponential stability , computer science , control engineering , engineering , artificial intelligence , control (management) , nonlinear system , biochemistry , chemistry , physics , quantum mechanics , gene , thermodynamics
Summary This article presents a control scheme for flexible joint robots which has uncertain parameters based on adaptive fuzzy compensation. Considering the unknown parameters, the proposed state feedback control approach utilizes measured variables to establish a cascade structure that is based on simplified dynamics. After reducing the number of fuzzy rules, the adaptive fuzzy logic system is added as compensation to decrease the approximated errors, and the robust terms are also used to enhance the robustness of closed‐loop system. Then, the global asymptotic stability could be confirmed through Lyapunov stability principle and Barbalat's lemma. Compared with the other two controllers, the proposed control method has not only higher position accuracy and better dynamic performance but also robustness to the approximation of motor inertia, friction torque and link torque. Some simulation experiments are conducted to show the validity of the proposed scheme.