Documenti accessibili
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Informazioni generali |
| Autore |
Le, Tien Dung; Kang, Hee-Jun; Suh, Young-Soo |
| Pubblicato |
InTech Open Access Publisher, 2013
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| edizione |
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| Volume |
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| ISBN |
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| Abstract |
This paper proposes a novel chattering free
neuro‐sliding mode controller for the trajectory
tracking control of two degrees of freedom (DOF)
parallel manipulators which have a complicated
dynamic model, including modelling uncertainties,
frictional uncertainties and external disturbances. A
feedforward neural network (NN) is combined with an
error estimator to completely compensate the large
nonlinear uncertainties and external disturbances of
the parallel manipulators. The online weight tuning
algorithms of the NN and the structure of the error
estimator are derived with the strict theoretical
stability proof of the Lyapunov theorem. The upper
bound of uncertainties and the upper bound of the
approximation errors are not required to be known in
advance in order to guarantee the stability of the
closed‐loop system. The example simulation results
show the effectiveness of the proposed control strategy
for the tracking control of a 2‐DOF parallel
manipulator. It results in its being chattering‐free, very
small tracking errors and its robustness against
uncertainties and external disturbances. |
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International Journal of Advanced Robotic Systems
Autore: Ottaviano, Erika; Ceccarelli, Marco; Husty, Manfred; Yu, Sung-Hoon; Kim, Yong-Tae; Park, Chang-Woo; Hyun, Chang-Ho; Chen, Xiulong; Feng, Weiming; Sun, Xianyang; Gao, Qing; Grigorescu, Sorin M.; Pozna, Claudiu; Liu, Wanli; Zhankui, Wang; Guo, Meng; Fu, Guoyu; Zhang, Jin; Chen, Wenyuan; Peng, Fengchao; Yang, Pei; Chen, Chunlin; Ding, Rui; Yu, Junzhi; Yang, Qinghai; Tan, Min; Polden, Joseph; Pan, [...]
Pubblicato: 2004
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